Sebastian Pardo Guerra | Applied Mathematics | Best Researcher Award

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Dr. Sebastian Pardo Guerra | Applied Mathematics | Best Researcher Award

University of California, San Diego at Center for Engineered Natural Intelligence, United States

Dr. Sebastián Pardo Guerra 🎓 is a distinguished mathematician and researcher at the Center for Engineered Natural Intelligence, University of California San Diego 🧠. With a Ph.D. from UNAM, his expertise spans pure mathematics—particularly module theory, lattice theory, and category theory—and their innovative applications in neuroscience, information theory, and quantum systems 🔬. He has published extensively in high-impact journals 📚, with several feature papers and editor’s picks in 2024–2025. A seasoned lecturer and active conference presenter 🎤, Dr. Pardo Guerra bridges theoretical depth with interdisciplinary innovation. His work reflects a unique synthesis of mathematical abstraction and real-world relevance, earning him recognition in both academic and applied domains 🌐. His scholarly excellence, international engagement, and commitment to advancing mathematical frontiers make him a strong candidate for top research honors 🏆.

Professional Profile 

🎓 Education

Dr. Sebastián Pardo Guerra holds a Ph.D. in Mathematics from the National Autonomous University of Mexico (UNAM) 🎓, where he also earned his M.S. and B.S. degrees in Mathematics. His academic journey reflects a deep commitment to foundational studies, with theses exploring Galois Theory, Abelian groups, and lattice preradicals 📘. His doctoral dissertation, On the Big Lattice of Lattice Preradicals, showcases early engagement with complex algebraic structures. Through prestigious CONACYT fellowships for both his master’s and doctoral studies 🏅, he demonstrated academic excellence and promise. His education laid a rigorous foundation for blending theoretical elegance with applied insight, positioning him to make substantial contributions at the intersection of algebra, logic, and emerging scientific domains 🔍.

💼 Professional Experience

Dr. Pardo Guerra is a researcher at the Center for Engineered Natural Intelligence, University of California San Diego (UCSD) 🧠, with a trajectory that includes appointments as a lecturer and postdoctoral researcher at UCSD and UNAM. From 2012 to 2019, he served as a mathematics lecturer at UNAM 🇲🇽, followed by postdoctoral roles in bioengineering and applied mathematics at UCSD 🌐. He currently contributes to cutting-edge projects integrating category theory with neuroscience and network theory. His dual focus on research and teaching spans over a decade of academic engagement, including recent instruction in Linear Algebra, Precalculus, and Vector Calculus 🧮. This combination of pedagogical strength and high-level research underpins his influential presence in both academic and applied mathematics spheres 🔧.

📚 Research Interests

Dr. Pardo Guerra’s research encompasses a compelling blend of pure and applied mathematics. In the pure domain, he focuses on module theory, lattice theory, and category theory 🧩—exploring structural properties and their implications in algebraic systems. In the applied space, he delves into neuroscience, information theory, and quantum information, applying advanced categorical frameworks to model complex, dynamic systems 🌐. His innovative use of preradicals to redefine information entropy and analyze network topologies exemplifies his unique methodological approach 🧠. By bridging abstract mathematics with emerging scientific challenges, his research offers novel insights into both foundational theory and interdisciplinary applications, contributing to the evolution of intelligent systems and computational structures ⚙️📊.

🏅 Awards and Honors

Dr. Pardo Guerra has received notable honors throughout his academic career, including the prestigious CONACYT Fellowships for both his M.S. and Ph.D. programs in Mexico 🇲🇽. These competitive awards recognize academic excellence and research potential among top Mexican scholars. His recent papers have earned “Feature Paper” and “Editor’s Choice” selections in international journals like Mathematics 📰—a testament to the originality and relevance of his work. His consistent presence at respected conferences such as BLAST, Ohio State–Denison Math Conference, and UCSD Colloquia further affirms his reputation within the global mathematics community 🌍. These accolades highlight his innovative thinking and valuable contributions to contemporary mathematical discourse 🏆.

🛠️ Research Skills

Dr. Pardo Guerra brings a powerful set of research skills combining deep theoretical insight with interdisciplinary modeling capabilities 🧠. He is adept at constructing and analyzing abstract structures within lattice theory, module theory, and category theory—fields requiring a high degree of mathematical precision 🔬. His work applies these constructs to neural networks, graph theory, and information systems, utilizing tools like preradicals, entropy models, and Markov categories. He is also proficient in academic writing, publishing, and presenting in both Spanish and English, and skilled in engaging audiences through lectures, seminars, and collaborative forums 🧾🎤. As a reviewer for Mathematical Reviews, he contributes to the peer-review process, underscoring his commitment to scholarly rigor and intellectual advancement ⚖️.

Publications Top Note 📝

Title: On the Graph Isomorphism Completeness of Directed and Multidirected Graphs
Authors: S. Pardo-Guerra, V.K. George, G.A. Silva
Year: 2025
Citations: 10
Source: Mathematics, Volume 13, Issue 2, Article 228

Title: Extending Undirected Graph Techniques to Directed Graphs via Category Theory
Authors: S. Pardo-Guerra, V.K. George, V. Morar, J. Roldan, G.A. Silva
Year: 2024
Citations: 7
Source: Mathematics, Volume 12, Issue 9, Article 1357

Title: Some Isomorphic Big Lattices and Some Properties of Lattice Preradicals
Authors: S. Pardo-Guerra, H.A. Rincón-Mejía, M.G. Zorrilla-Noriega
Year: 2020
Citations: 5
Source: Journal of Algebra and Its Applications, Volume 19, Issue 7, Article 2050140

Title: Big Lattices of Hereditary and Natural Classes of Linear Modular Lattices
Authors: S. Pardo-Guerra, H.A. Rincón-Mejía, M.G. Zorrilla-Noriega
Year: 2021
Citations: 2
Source: Algebra Universalis, Volume 82, Issue 4, Article 52

Title: On Preradicals, Persistence, and the Flow of Information
Authors: S. Pardo-Guerra, G.A. Silva
Year: 2024
Source: International Journal of General Systems, Volume 53, Issues 7–8, Pages 1121–1145

Title: On Torsion Theories and Open Classes of Linear Modular Lattices
Authors: F. González-Bayona, S. Pardo-Guerra, H.A. Rincón-Mejía, et al.
Year: 2024
Source: Communications in Algebra, Volume 52, Issue 1, Pages 371–391

Title: On the Lattice of Conatural Classes of Linear Modular Lattices
Authors: S. Pardo-Guerra, H.A. Rincón-Mejía, M.G. Zorrilla-Noriega, et al.
Year: 2023
Source: Algebra Universalis, Volume 84, Issue 4, Article 29

Title: A Categorical Framework for Quantifying Emergent Effects in Network Topology
Authors: G.A.S. Johnny Jingze Li, S. Pardo-Guerra, Kalyan Basu
Year: 2025
Source: Neural Computation (in press)

Title: On Semi-Projective Modular Lattices
Authors: F.G. Bayona, S.P. Guerra, M.G.Z. Noriega, H.A.R. Mejía
Source: International Electronic Journal of Algebra, Pages 1–35

🧾 Conclusion

Dr. Sebastián Pardo Guerra is a dynamic and forward-thinking researcher whose contributions span theoretical depth and applied innovation 🌟. With solid academic credentials, international teaching and research experience, and a growing portfolio of impactful publications, he exemplifies excellence in mathematical sciences 📈. His work not only advances abstract algebraic theory but also pioneers new applications in intelligent systems and complex networks 🧠💡. Recognized through awards, invited talks, and feature publications, Dr. Pardo Guerra is well-positioned as a leading voice in contemporary mathematical research. His diverse expertise, professional integrity, and global academic engagement make him an outstanding candidate for high-level honors such as the Best Researcher Award 🏅.

Charalampos Patrikakis | Data Science | Best Researcher Award

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Prof. Dr. Charalampos Patrikakis | Data Science | Best Researcher Award

Director, Consert lab at University of West Attica Greece

Professor Charalampos Z. Patrikakis is a distinguished academic at the University of West Attica (UniWA), specializing in the design of interconnected electronic systems and data-driven services 📡💡. As Director of the Computer Network Services Research Laboratory and Chair of UniWA’s Innovation and Start-up Entrepreneurship Committee 🚀, he bridges advanced research with real-world impact. He leads the MSc Program in Artificial Intelligence and Deep Learning 🤖 and co-founded the spinoff THINGENIOUS, emphasizing tech transfer and innovation. A Senior Member and Distinguished Contributor of IEEE 🌐, he serves as Editor-in-Chief of IEEE IT Professional Magazine and actively mentors through IEEE Student Branch and global committees 🎓. His contributions span academia, policy, and innovation, positioning him as a thought leader in digital transformation, AI, and trustworthy systems 🔍📊.

Professional Profile 

🎓 Education

Professor Charalampos Z. Patrikakis holds a strong academic foundation in Electrical and Computer Engineering, having completed his undergraduate and graduate studies in Greece’s premier technical institutions 🏛️. His educational journey laid the groundwork for a deep engagement in networked systems, AI, and intelligent service design 🧠. Over the years, he has continued his intellectual development through participation in advanced research programs and postdoctoral initiatives, expanding his expertise into interdisciplinary domains. His commitment to lifelong learning is evident in his leadership of postgraduate programs and mentorship of early-career researchers 📘. This educational background not only supports his academic excellence but also empowers his contributions in innovation, policy, and industry-focused technological development 🎯.

💼 Professional Experience

With an extensive career in higher education and applied research, Professor Patrikakis serves as a Professor at the University of West Attica and Director of the Computer Network Services Research Laboratory 🖥️. He has previously led the Information Transmission-Processing and Networks Division and is currently Chair of UniWA’s Committee on Technology Transfer, Innovation, and Start-up Entrepreneurship 🚀. His experience also spans advisory roles in national policy, having served the Greek Deputy Minister of Development on research matters (2006–2007) 📋. He is Editor-in-Chief of IEEE IT Professional Magazine and actively contributes to IEEE global leadership as a Senior Member and Distinguished Contributor 🌍. His professional roles demonstrate his unique ability to bridge academia, innovation, and policy for technological advancement 🔧📡.

🔬 Research Interests

Professor Patrikakis’ research spans several cutting-edge fields including interconnected electronic systems, IoT architectures, data processing, and AI-driven service design 🤖📶. He is particularly interested in the trustworthiness of social networks, ethical AI, and the integration of deep learning algorithms into real-world applications 🌐. Through his leadership in the MSc Program in Artificial Intelligence and Deep Learning, he actively explores emerging topics in smart systems, adaptive learning, and secure network protocols 🔍🔐. His interdisciplinary focus bridges computing, communication systems, and human-centric applications, with a strong orientation toward technological impact and innovation. By leading national and international collaborations, he contributes to shaping future-ready digital ecosystems aligned with sustainable and ethical digital transformation goals 🌱📊.

🏅 Awards and Honors

Professor Patrikakis has received multiple honors recognizing his dedication to academia, innovation, and IEEE leadership 🏆. As a Senior Member of IEEE, Distinguished Contributor, and Distinguished Visitor of the IEEE Computer Society, he has earned global recognition for technical leadership and community engagement 🌍. He has also been appointed Chair of several key IEEE committees, including the Special Interest Group on Trustworthiness in Social Networks. His role as Editor-in-Chief of IEEE IT Professional Magazine further emphasizes the trust and esteem placed in him by the international research community 📝. These accolades highlight not only his academic and technical prowess but also his ability to inspire and lead in both educational and professional domains 🎖️.

🧪 Research Skills

Professor Patrikakis brings advanced research skills in system architecture design, data analytics, AI integration, and secure communications 🔐📊. His capabilities extend to managing large-scale research labs, supervising MSc and PhD students, and translating research into startups through successful commercialization strategies 🚀. He is proficient in applying machine learning and deep learning models to practical challenges, fostering cross-disciplinary collaboration and innovation 💻🤝. He excels in project planning, grant acquisition, and strategic R&D management, positioning him as a leader in both theoretical and applied research. His editorial work and IEEE leadership roles also reflect strong skills in scientific communication, peer review, and community building 📚🌟.

Publications Top Note 📝

  • Title: A complete farm management system based on animal identification using RFID technology
    Authors: A.S. Voulodimos, C.Z. Patrikakis, A.B. Sideridis, V.A. Ntafis, E.M. Xylouri
    Year: 2010
    Citations: 385
    Source: Computers and Electronics in Agriculture, 70(2), 380–388

  • Title: Distributed denial of service attacks
    Authors: C. Patrikakis, M. Masikos, O. Zouraraki
    Year: 2004
    Citations: 157
    Source: The Internet Protocol Journal, 7(4), 13–35

  • Title: A cooperative fog approach for effective workload balancing
    Authors: A. Kapsalis, P. Kasnesis, I.S. Venieris, D.I. Kaklamani, C.Z. Patrikakis
    Year: 2017
    Citations: 125
    Source: IEEE Cloud Computing, 4(2), 36–45

  • Title: PerceptionNet: A deep convolutional neural network for late sensor fusion
    Authors: P. Kasnesis, C.Z. Patrikakis, I.S. Venieris
    Year: 2019
    Citations: 48
    Source: Proceedings of the 2018 Intelligent Systems and Applications

  • Title: Cloud federation and the evolution of cloud computing
    Authors: D.G. Kogias, M.G. Xevgenis, C.Z. Patrikakis
    Year: 2016
    Citations: 37
    Source: Computer, 49(11), 96–99

  • Title: Deep learning empowered wearable-based behavior recognition for search and rescue dogs
    Authors: P. Kasnesis, V. Doulgerakis, D. Uzunidis, D.G. Kogias, S.I. Funcia, et al.
    Year: 2022
    Citations: 35
    Source: Sensors, 22(3), 993

  • Title: Application of blockchain technology in dynamic resource management of next generation networks
    Authors: M. Xevgenis, D.G. Kogias, P. Karkazis, H.C. Leligou, C. Patrikakis
    Year: 2020
    Citations: 33
    Source: Information, 11(12), 570

  • Title: Publish/subscribe over information centric networks: A Standardized approach in CONVERGENCE
    Authors: N.B. Melazzi, S. Salsano, A. Detti, G. Tropea, L. Chiariglione, A. Difino, et al.
    Year: 2012
    Citations: 32
    Source: Future Network & Mobile Summit

  • Title: Security and privacy in pervasive computing
    Authors: C. Patrikakis, P. Karamolegkos, A. Voulodimos, M.H. Abd Wahab, et al.
    Year: 2007
    Citations: 31
    Source: IEEE Pervasive Computing, 6(4), 73–75

  • Title: Cognitive friendship and goal management for the social IoT
    Authors: P. Kasnesis, C.Z. Patrikakis, D. Kogias, L. Toumanidis, I.S. Venieris
    Year: 2017
    Citations: 28
    Source: Computers & Electrical Engineering, 58, 412–428

  • Title: Toward a blockchain-enabled crowdsourcing platform
    Authors: D.G. Kogias, H.C. Leligou, M. Xevgenis, M. Polychronaki, E. Katsadouros, et al.
    Year: 2019
    Citations: 27
    Source: IT Professional, 21(5), 18–25

  • Title: On the benefits of deep convolutional neural networks on animal activity recognition
    Authors: E. Bocaj, D. Uzunidis, P. Kasnesis, C.Z. Patrikakis
    Year: 2020
    Citations: 24
    Source: International Conference on Smart Systems and Technologies, 83–88

  • Title: Autonomic communication
    Authors: A.V. Vasilakos, M. Parashar, S. Karnouskos, W. Pedrycz
    Year: 2009
    Citations: 23
    Source: Springer Science & Business Media

  • Title: Serious games: an attractive approach to improve awareness
    Authors: S. Sorace, E. Quercia, E. La Mattina, C.Z. Patrikakis, L. Bacon, G. Loukas, et al.
    Year: 2018
    Citations: 22
    Source: Community-Oriented Policing and Technological Innovations, 1–9

  • Title: Changing mobile data analysis through deep learning
    Authors: P. Kasnesis, C.Z. Patrikakis, I.S. Venieris
    Year: 2017
    Citations: 20
    Source: IT Professional, 19(3), 17–23

  • Title: An ontology-based smart production management system
    Authors: D.T. Meridou, A.P. Kapsalis, M.E.C. Papadopoulou, E.G. Karamanis, et al.
    Year: 2015
    Citations: 19
    Source: IT Professional, 17(6), 36–46

  • Title: Using personalized mashups for mobile location based services
    Authors: A.S. Voulodimos, C.Z. Patrikakis
    Year: 2008
    Citations: 19
    Source: International Wireless Communications and Mobile Computing Conference

  • Title: Intelligent performance prediction: the use case of a Hadoop cluster
    Authors: D. Uzunidis, P. Karkazis, C. Roussou, C. Patrikakis, H.C. Leligou
    Year: 2021
    Citations: 18
    Source: Electronics, 10(21), 2690

  • Title: Combating fake news with transformers: a comparative analysis of stance detection and subjectivity analysis
    Authors: P. Kasnesis, L. Toumanidis, C.Z. Patrikakis
    Year: 2021
    Citations: 18
    Source: Information, 12(10), 409

✅ Conclusion

Professor Charalampos Z. Patrikakis exemplifies the modern research leader—deeply scholarly, highly innovative, and globally engaged 🌐. His academic achievements, combined with real-world impact through innovation, mentorship, and professional service, mark him as a transformative figure in the fields of AI, IoT, and secure communication systems 🤖💡. With a strong commitment to interdisciplinary research, educational excellence, and societal relevance, he contributes meaningfully to shaping the future of digital technology and its applications 🚀. His balanced expertise in academia, industry, and policy makes him an ideal role model and a worthy candidate for high-level recognition, including the Best Researcher Award 🏅📈.

Owais Khan | Applied Mathematics | Best Researcher Award

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Assist. Prof. Dr. Owais Khan | Applied Mathematics | Best Researcher Award

Assistant Professor at Integral University India

Dr. Owais Khan is a distinguished researcher and educator in Mathematics, with a strong focus on Artificial Intelligence, Data Science, and Computational Methods 🧠📊. He holds a Ph.D. and has contributed extensively through impactful publications in reputed international journals 📚. Dr. Khan’s academic journey is marked by innovative teaching methodologies and interdisciplinary research that bridges theory and application across science and technology 🔬💡. He has participated in global conferences, fostering collaborations that advance mathematical innovation 🌐🤝. His work continues to inspire the next generation of scholars, reflecting his dedication to academic excellence and research leadership 🎓🏅. Passionate about solving real-world problems through mathematics, Dr. Khan’s vision aligns with emerging trends in intelligent systems and digital transformation, making him a leading voice in modern mathematical science 🔎💻.

Professional Profile 

Education 🎓📘

Dr. Owais Khan earned his Ph.D. in Mathematics with a specialization in Artificial Intelligence and Computational Techniques, establishing a strong academic foundation. His educational journey includes a Master’s and Bachelor’s degree in Mathematics from prestigious institutions 🏛️. Throughout his academic path, he consistently excelled, earning scholarships and accolades for his analytical aptitude and research excellence. He has also completed advanced certification programs in Data Science and Machine Learning, reinforcing his interdisciplinary expertise 🤖📈. Dr. Khan’s education has equipped him with a blend of theoretical knowledge and computational skills, making him adept at tackling complex scientific challenges. His commitment to lifelong learning and continuous improvement is evident in his engagement with emerging educational platforms and professional development opportunities globally 🌍📚.

Professional Experience 🧑‍🏫💼

Dr. Owais Khan has held esteemed academic and research positions across top universities and research institutes. With years of experience as a faculty member, he has taught a wide range of undergraduate and postgraduate courses in Mathematics, Data Science, and AI 📊📐. In addition to teaching, he has served as a research mentor and thesis advisor, guiding scholars in advanced computational research 🔍👨‍🎓. Dr. Khan has contributed to curriculum development and interdisciplinary program design, enhancing academic structures. He also worked on funded projects involving AI-based modeling and predictive analytics. His collaborative approach has led to partnerships with institutions across disciplines, enriching his academic influence. His professional journey reflects a balance between teaching, research, and institutional leadership, underscoring his role as a multifaceted educator and scientist 🌟🏢.

Research Interest 🔬💡

Dr. Khan’s research interests lie at the intersection of Mathematics, Artificial Intelligence, and Data-Driven Science. His work explores mathematical modeling, optimization, neural networks, fuzzy logic, and machine learning applications in real-world systems 🧠📉. He is particularly focused on predictive analytics, intelligent algorithms, and AI-supported decision-making systems. His current projects delve into computational simulations, pattern recognition, and smart data analysis across environmental, medical, and engineering domains ⚙️🌿🩺. Dr. Khan’s research is characterized by an interdisciplinary framework, aiming to translate theoretical models into practical innovations. His vision is to advance intelligent systems that solve contemporary challenges through mathematically grounded solutions. By integrating traditional mathematical tools with modern AI paradigms, Dr. Khan pushes the frontiers of applied mathematics and scientific discovery 🚀📚.

Awards and Honors 🏆🎖️

Dr. Owais Khan has received several prestigious awards in recognition of his academic excellence and research contributions. He has been honored with Best Research Paper Awards, Young Scientist Awards, and Academic Excellence Awards from reputed scientific forums and institutions 🌟📜. His innovative work in artificial intelligence and mathematical modeling has earned accolades both nationally and internationally. He has also received travel grants and research fellowships for participation in global conferences and collaborative projects 🌍✈️. Dr. Khan is frequently invited as a keynote speaker, reviewer, and editorial board member for international journals and symposiums, further underscoring his scholarly impact 🧾🗣️. These honors reflect his dedication to pushing the boundaries of research and mentoring the next generation of scientists in his field 🧑‍🔬🏅.

Research Skills 🛠️🧪

Dr. Khan possesses a versatile set of research skills, combining theoretical mathematical expertise with advanced computational proficiency. He is adept in programming languages such as Python, R, and MATLAB, which he applies to develop and test AI algorithms and data models 💻📊. His analytical capabilities span differential equations, numerical methods, statistical analysis, and optimization. He is skilled in using tools like TensorFlow, Scikit-learn, and SPSS for machine learning and statistical computing 🤖📈. Dr. Khan is also experienced in LaTeX for professional documentation and publishing. His collaborative research methodology and proficiency in data interpretation enable high-impact scientific outputs. He excels in research design, literature synthesis, hypothesis testing, and experimental validation, making him a well-rounded and innovative contributor to multidisciplinary research 🔍📂.

Publications Top Note 📝

  • Title: Computable solution of fractional kinetic equations using Mathieu-type series
    Authors: O. Khan, N. Khan, D. Baleanu, K.S. Nisar
    Year: 2019
    Citations: 22
    Source: Advances in Difference Equations

  • Title: A novel densely packed 4×4 MIMO antenna design for UWB wireless applications
    Authors: O. Khan, S. Khan, S.N.K. Marwat, N. Gohar, M. Bilal, M. Dalarsson
    Year: 2023
    Citations: 16
    Source: Sensors, Volume 23(21), Article 8888

  • Title: Computation of new class of integrals involving generalized Galue type Struve function
    Authors: M. Kamarujjama, O. Khan
    Year: 2018
    Citations: 16
    Source: Journal of Computational and Applied Mathematics, Volume 351, Pages 228–236

  • Title: Fractional calculus formulas for Mathieu-type series and generalized Mittag-Leffler function
    Authors: O. Khan, S. Araci, M. Saif
    Year: 2020
    Citations: 15
    Source: Journal of Mathematics and Computational Science, Volume 20, Pages 122–130

  • Title: A type of fractional kinetic equations associated with the (p; q)-extended beta-hypergeometric and confluent hypergeometric functions
    Authors: O. Khan, N.N.U. Khan, J. Choi, K.S. Nisar
    Year: 2021
    Citations: 12
    Source: Nonlinear Functional Analysis and Applications, Volume 26(2), Pages 381–392

  • Title: Certain integral transforms involving the product of Galue type Struve function and Jacobi polynomial
    Authors: O. Khan, M. Kamarujjama, N.U. Khan
    Year: Not Specified
    Citations: 12
    Source: Palestine Journal of Mathematics, Volume 6, Pages 1–9

  • Title: The generalized p‑k‑Mittag‑Leffler function and solution of fractional kinetic equations
    Authors: O. Khan, M. Kamarujjama, N.U. Khan
    Year: 2019
    Citations: 11
    Source: The Journal of Analysis, Pages 1–18

  • Title: Construction of partially degenerate Laguerre-Genocchi polynomials with their applications
    Authors: T. Usman, M. Aman, O. Khan, K.S. Nisar, S. Araci
    Year: 2020
    Citations: 9
    Source: American Institute of Mathematical Sciences

  • Title: Fractional calculus of generalized pk-Mittag-Leffler function using Marichev–Saigo–Maeda operators
    Authors: M. Kamarujjama, N.U. Khan, O. Khan
    Year: 2019
    Citations: 9
    Source: Arab Journal of Mathematical Sciences, Volume 25(2), Pages 156–168

  • Title: Estimation of certain integrals with extended multi-index Bessel function
    Authors: M. Kamarujjama, N.U. Khan, O. Khan
    Year: 2019
    Citations: 9
    Source: Malaya Journal of Matematik, Volume 7(2), Pages 206–212

  • Title: A novel kind of beta logarithmic function and their properties
    Authors: N.U. Khan, S. Husain, O. Khan
    Year: 2022
    Citations: 8
    Source: Hacettepe Journal of Mathematics and Statistics, Volume 52(4), Pages 945–955

  • Title: Extended Type k-Mittag–Leffler Function and Its Applications
    Authors: M. Kamarujjama, N.U. Khan, O. Khan, J.J. Nieto
    Year: 2019
    Citations: 7
    Source: International Journal of Applied and Computational Mathematics, Volume 5, Pages 1–14

  • Title: Fractional calculus of a product of multivariable Srivastava polynomial and multi-index Bessel function in the kernel F-3
    Authors: O. Khan, N. Khan, K.S. Nisar, M. Saif, D. Baleanu
    Year: 2020
    Citations: 4
    Source: Not specified (likely a mathematics journal)

  • Title: Unified approach to the certain integrals of k-Mittag-Leffler type function of two variables
    Authors: O. Khan, N. Khan, K.A. Sooppy
    Year: 2019
    Citations: 2
    Source: Transactions of the National Academy of Sciences of Azerbaijan. Series of Physical-Technical and Mathematical Sciences, Volume 39, Pages 98–108

  • Title: Evaluation of Transforms and Fractional Calculus of New Extended Wright Function
    Authors: N.U. Khan, M.I. Khan, O. Khan
    Year: 2022
    Citations: 1
    Source: International Journal of Applied and Computational Mathematics, Volume 8, Pages 1–14

  • Title: Certain finite integrals involving generalized Wright function
    Authors: N.U. Khan, M.I. Khan, O. Khan
    Year: 2021
    Citations: 1
    Source: Advanced Mathematical Models & Applications, Volume 6(3)

  • Title: Fractional operators and solution of fractional kinetic equations involving generalized hypergeometric function
    Authors: T. Usman, N. Khan, O. Khan, D.A. Juraev
    Year: 2024
    Source: Palestine Journal of Mathematics, Volume 13(3)

  • Title: A novel kind of beta logarithmic function and their properties
    Authors: K. Nabiullah, S. Husain, K. Owais
    Year: 2023
    Source: Hacettepe Journal of Mathematics and Statistics, Pages 1–12

Conclusion 🧾✅

Dr. Owais Khan stands out as a dynamic mathematician, educator, and AI researcher whose work bridges theory and application. His multifaceted profile—from academic excellence and international recognition to interdisciplinary research and technical mastery—illustrates his role as a leader in modern scientific inquiry 🌐📘. With a forward-thinking mindset, he continues to explore how mathematical reasoning can power intelligent systems and solve pressing global challenges. His contributions in academia, research, and professional service reflect his commitment to knowledge advancement and societal betterment 🧠💡. Dr. Khan remains a source of inspiration to peers and students alike, continually striving for excellence in education, research, and innovation. His journey embodies a blend of intellect, innovation, and integrity, shaping the future of mathematics and artificial intelligence 🌟📚.

Sedaghat Shahmorad Moghanlou | Applied Mathematics | Best Researcher Award

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Prof. Sedaghat Shahmorad Moghanlou | Applied Mathematics | Best Researcher Award

Applied Math. Department at University of Tabriz, Iran

Prof. Sedaghat Shahmorad 🎓, a distinguished scholar in Applied Mathematics at the University of Tabriz 🇮🇷, specializes in numerical analysis, particularly integro-differential equations. With over two decades of academic experience 🧠, he has significantly contributed to the field through extensive teaching, research, and leadership. He has supervised numerous M.Sc. and Ph.D. theses 🎓📚 and authored multiple scholarly books and impactful journal articles 📖📝. His work on the Tau method and approximation techniques has earned recognition in computational mathematics 🧮. As Head of the Applied Mathematics Department and former Dean, he has demonstrated strong administrative and academic leadership 👨‍🏫📊. Prof. Shahmorad’s dedication to advancing numerical methods and mentoring future mathematicians makes him a highly deserving candidate for the Best Researcher Award 🏆🔬.

Professional Profile 

Education 🎓📘

Prof. Sedaghat Shahmorad earned his B.Sc. in Applied Mathematics from the University of Tabriz 🇮🇷, followed by an M.Sc. and Ph.D. in Numerical Analysis from the same institution. His academic journey has been marked by excellence in mathematical modeling and computational theory 📊. With a solid foundation in numerical methods and integro-differential equations, he developed deep expertise in solving complex mathematical problems 💡. Throughout his academic training, Prof. Shahmorad received high honors, standing out for his analytical acumen and innovation 🧠. His commitment to lifelong learning and scholarly development has shaped a distinguished academic and research career, reinforcing his role as a leading expert in numerical mathematics 📐🔍.

Professional Experience 👨‍🏫🏢

Prof. Shahmorad brings over two decades of academic and leadership experience in Applied Mathematics at the University of Tabriz 🎓. He has served as the Head of the Department of Applied Mathematics and formerly as the Dean of the Faculty of Mathematical Sciences 🏛️. In addition to his teaching duties, he has led multiple research projects, supervised numerous postgraduate students, and contributed to curriculum development 📚. His strong leadership and mentorship have made a lasting impact on the academic community 👥. He has also participated in editorial boards, conferences, and international collaborations 🌐. His professional trajectory reflects his deep commitment to both teaching and research excellence, making him a vital contributor to the advancement of numerical mathematics 🔬📈.

Research Interest 🔍📐

Prof. Shahmorad’s research focuses on numerical analysis, especially the development of efficient methods for solving integro-differential and delay differential equations 🔢. He is renowned for his work on Tau methods, spectral techniques, and high-order approximation algorithms, which have broad applications in engineering, physics, and applied sciences ⚙️🌌. His studies aim to bridge theoretical rigor with computational feasibility, providing tools for real-world problem-solving 💻📊. He also explores fractional calculus, integral transforms, and mathematical modeling of dynamic systems. His interdisciplinary research contributes significantly to advancing both applied and pure mathematical domains 📘🧪. Prof. Shahmorad’s innovative methodologies continue to influence emerging trends in computational mathematics and inspire the next generation of researchers around the globe 🌍.

Award and Honor 🏆🎖️

Prof. Sedaghat Shahmorad has received multiple awards and honors recognizing his academic excellence, innovative research, and outstanding mentorship 🏅📚. Notably, he has been acknowledged as a Top Researcher at the University of Tabriz and by national science organizations in Iran 🇮🇷. His contributions to numerical mathematics, especially in solving integro-differential equations, have earned accolades from peer-reviewed journals and international conference bodies 🧾🌟. He has also received honors for excellence in teaching and student supervision, highlighting his role as a mentor par excellence 👨‍🏫🌱. These awards are a testament to his impactful research output, dedication to knowledge dissemination, and continued service to the academic community 🎓🧠.

Research Skill 🧠💻

Prof. Shahmorad possesses advanced skills in mathematical modeling, numerical simulations, and algorithm development. He is proficient in implementing spectral and collocation methods, particularly the Tau method, to tackle complex integro-differential systems with precision 🔢📈. His expertise extends to fractional differential equations, delay systems, and applied analysis using computational tools like MATLAB and Mathematica 🖥️⚙️. With a strong command over linear algebra, integral transforms, and functional analysis, he develops robust algorithms that are widely cited and applied in science and engineering 🔍📚. His problem-solving approach blends theoretical insight with computational strategy, fostering innovation and practical applications in numerical mathematics 📘🚀.

Publications Top Note 📝

  • Title: Solving a class of auto-convolution Volterra integral equations via differential transform method
    Authors: Sedaghat Shahmorad, et al.
    Year: 2025
    Source: Journal of Mathematical Modeling

  • Title: Approximate solution of multi-term fractional differential equations via a block-by-block method
    Authors: Sedaghat Shahmorad, et al.
    Year: 2025
    Citations: 1
    Source: Journal of Computational and Applied Mathematics

  • Title: Convergence analysis of Jacobi spectral tau-collocation method in solving a system of weakly singular Volterra integral equations
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Citations: 1
    Source: Mathematics and Computers in Simulation

  • Title: Theoretical and numerical analysis of a first-kind linear Volterra functional integral equation with weakly singular kernel and vanishing delay
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Citations: 1
    Source: Numerical Algorithms

  • Title: Double weakly singular kernels in stochastic Volterra integral equations with application to the rough Heston model
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Applied Mathematics and Computation

  • Title: Existence, uniqueness and blow-up of solutions for generalized auto-convolution Volterra integral equations
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Applied Mathematics and Computation

  • Title: The application of fuzzy transform method to the initial value problems of linear differential–algebraic equations
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Mathematical Sciences

  • Title: Solving fractional differential equations using cubic Hermit spline functions
    Authors: Sedaghat Shahmorad, et al.
    Year: 2024
    Source: Filomat (Open Access)

  • Title: Solving 2D-integro-differential problems with nonlocal boundary conditions via a matrix formulated approach
    Authors: Sedaghat Shahmorad, et al.
    Year: 2023
    Citations: 1
    Source: Mathematics and Computers in Simulation

  • Title: Review of recursive and operational approaches of the Tau method with a new extension
    Authors: Sedaghat Shahmorad, et al.
    Year: 2023
    Source: Computational and Applied Mathematics

Conclusion ✨📜

Prof. Sedaghat Shahmorad stands as a prominent figure in numerical analysis, combining deep theoretical knowledge with computational expertise 🌐📊. His dedication to teaching, mentoring, and advancing numerical methodologies has significantly shaped the field and inspired scholars across disciplines 🧠🎓. With a rich portfolio of research, leadership roles, and academic honors, he exemplifies excellence in mathematics and its real-world applications 🧾🏅. His work not only contributes to scientific understanding but also provides tools for innovation across technology and engineering sectors 🧬⚙️. As a visionary academic and skilled researcher, Prof. Shahmorad continues to influence future directions in computational and applied mathematics with distinction 🌟📘.

Ovidiu Racorean | Information Theory | Best Researcher Award

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Dr. Ovidiu Racorean | Information Theory | Best Researcher Award

Expert at DGTI, Romania

Dr. Ovidiu Racorean is a distinguished senior researcher specializing in quantum information theory, theoretical physics, and quantum finance. 🌌 His innovative work explores complex concepts such as temporal wormholes, entanglement entropy, and the application of quantum mechanics to financial markets 📈. With a strong interdisciplinary approach, he bridges physics and economics, contributing novel hypotheses that deepen our understanding of black holes and market dynamics. 🕳️💹 Dr. Racorean has a solid publication record, including impactful papers in respected journals and preprints, showcasing his active research presence. 📚 Beyond academia, he engages in science communication, making advanced scientific ideas accessible to the public. 🗣️ Fluent in English and Romanian, he holds a position at Romania’s Ministry of Finance, where he applies theoretical insights to practical challenges. His work exemplifies innovation, rigor, and dedication, marking him as a leading candidate for the Best Researcher Award. 🏆

Professional Profile 

Education 🎓

Dr. Ovidiu Racorean completed his B.Sc. and M.Sc. degrees in Economics at the prestigious Bucharest Academy of Economic Studies (ASE), Romania. His academic foundation in economics provided a unique perspective that he later combined with advanced concepts in quantum physics. This strong educational background enabled him to pursue interdisciplinary research at the intersection of theoretical physics, quantum information, and financial markets. His rigorous training in economics and quantitative methods supports his innovative work in quantum finance and econophysics, reflecting a rare blend of expertise that spans both social sciences and hard sciences. This diverse education underpins his ability to address complex problems from multiple angles, fostering groundbreaking research that challenges traditional disciplinary boundaries.

Professional Experience 💼

Dr. Racorean currently serves as a Senior Researcher at the General Directorate of Information Technology within Romania’s Ministry of Finance. In this role, he focuses on applying principles from quantum mechanics and information theory to both theoretical physics and financial systems. His work involves developing novel frameworks that integrate quantum phenomena with economic modeling, a pioneering area that bridges two traditionally separate domains. Over the years, Dr. Racorean has contributed significant theoretical insights on black hole thermodynamics and quantum finance, advancing knowledge within these specialized fields. His position in a governmental institution also highlights his ability to translate complex scientific theories into practical applications relevant to national financial technology infrastructure.

Research Interests 🔬

Dr. Ovidiu Racorean’s research spans several cutting-edge domains including quantum information theory, the AdS/CFT correspondence, temporal wormholes, and the arrow of time in physics. He also focuses on entanglement entropy and spacetime geometry, investigating fundamental aspects of the universe through quantum mechanics. Additionally, his interests extend to the emerging field of quantum finance and econophysics, where he explores the parallels between quantum phenomena and market behaviors. Dr. Racorean’s work on black hole thermodynamics further reflects his commitment to understanding complex systems via interdisciplinary methods. This diverse portfolio demonstrates his dedication to bridging physics and economics, leveraging quantum principles to reveal new insights across both theoretical and applied sciences.

Awards and Honors 🏅

While specific awards and honors for Dr. Ovidiu Racorean have not been explicitly listed, his academic and professional contributions position him as a strong candidate for prestigious recognition. His innovative research outputs, including influential publications in theoretical physics and quantum finance, reflect a trajectory of excellence and impact. Participation in notable scientific discussions and his role at a key governmental institution further underscore his leadership in the field. Given his pioneering hypotheses and interdisciplinary approach, Dr. Racorean is well poised to receive awards that honor innovation at the intersection of physics and economics. Recognition for his work would celebrate his dedication to advancing knowledge and bridging complex scientific domains.

Research Skills 🧪

Dr. Racorean exhibits a sophisticated mastery of quantum mechanics, theoretical physics, and advanced mathematical modeling, with strong expertise in quantum information theory and spacetime geometry. His skills extend to applying quantum principles to financial systems, demonstrating proficiency in econophysics and quantum finance modeling. He is adept at hypothesis development, critical analysis, and interdisciplinary research design. Dr. Racorean also possesses experience in scientific communication and publication, contributing regularly to high-level research discussions and public science platforms. His ability to synthesize complex physical theories with economic data reflects strong analytical and computational skills, making him uniquely qualified to drive innovation in emerging quantum applications both within theoretical and practical frameworks.

Publications Top Notes 📝

  • Title: Spacetime manipulation of quantum information around rotating black holes
    Author : O. Racorean
    Year : 201
    Citations: 5
    Source: Annals of Physics 398, 254-264

  • Title: Crossing Stocks and the Positive Grassmannian I: The Geometry behind Stock Market
    Author: O. Racorean
    Year : 2014
    Ci: 5
    Source: arXiv preprint arXiv:1402.1281

  • Title: Quantum Gates and Quantum Circuits of Stock Portfolio
    Author: O. Racorean
    Year: 2015
    Citations: 4
    Source: arXiv preprint arXiv:1507.02310

  • Title: Braided and Knotted Stocks in the Stock Market: Anticipating the flash crashes
    Author: O. Racorean
    Year: 2014
    Citations: 4
    Source: arXiv preprint arXiv:1404.6637

  • Title: Quantum entanglement, two-sided spacetimes and the thermodynamic arrow of time
    Author : O. Racorean
    Year : 2019
    Citations :
    Source: arXiv preprint arXiv:1904.04012

  • Title : How much you
    Autho: O. Racorean
    Year: 2013
    Citations: 3
    Source: arXiv preprint arXiv:1307.6727

  • Title: Decoding Stock Market Behavior with the Topological Quantum Computer
    Author: O. Racorean
    Year: 2014
    Citations: 2
    Source: arXiv preprint arXiv:1406.3531

  • Title: Time-independent pricing of options in range bound markets
    Author : O. Racorean
    Year : 2013
    Citations: 2
    Source: arXiv preprint arXiv:1304.6846

  • Title: Creation of single-photon entangled states around rotating black holes
    Author: O. Racorean
    Year: 2018
    Citations: 1
    Source: New Astronomy 59, 65-70

  • Title: Are Financial Markets an aspect of Quantum World?
    Author : O. Racorean
    Year : 2013
    Citations : 1
    Source: arXiv preprint arXiv:1305.1559

  • Title: The reversal of time effect in the bulk of the traversable wormholes
    Author: O.S. Racorean
    Year: 2025
    Citations: –
    Source: Available at SSRN

  • Title: Behind the horizon
    Author: O.S. Racorean
    Year: 2023
    Citations: –
    Source: Available at SSRN 4637408

  • Title: Eternal black holes and temporal quantum correlations
    Author: O. Racorean
    Year: 2023
    Citations: –
    Source: arXiv preprint arXiv:2304.00982

  • Title: Eternal black holes and quantum temporal correlations
    Author : O. Racorean
    Year : 2023
    Quote: –
    Source: arXiv e-prints, arXiv:2304.00982

  • Title: The Born rule in a timeless universe
    Author: O. Racorean
    Year: 2022
    Citations: –
    Source: arXiv preprint arXiv:2203.07074

  • Title: Quantum entanglement and the non-orientability of spacetime
    Author: O. Racorean
    Year: 2020
    Citations: –
    Source: arXiv preprint arXiv:2009.04990

  • Title: AdS/CFT correspondence: the fountain of quantum youth
    Author: O. Racorean
    Year: 2020
    Citations: –
    Source: arXiv preprint arXiv:2003.09228

  • Title: Quantum gates implementation by X-ray single-photons around rotating black holes
    Author : O. Racorean
    Year : 2017
    Citations: –
    Source: arXiv preprint arXiv:1702.04640

  • Title: Is the Stock Market a Quantum Computational Virtual Reality?
    Author: O.S. Racorean
    Year: 2015
    Citations: –
    Source: Available at SSRN 2665882

  • Title: Correct usage of transmission coefficient for timing the market
    Author: O. Racorean
    Year: 2013
    Citations: –
    Source: arXiv preprint arXiv:1307.5975

Conclusion ✔️

Dr. Ovidiu Racorean stands out as a visionary researcher whose interdisciplinary work bridges quantum physics and finance with remarkable originality. His innovative hypotheses on temporal wormholes and the quantum behavior of markets demonstrate both depth and creativity. With a robust publication record and a pivotal role at Romania’s Ministry of Finance, he combines theoretical rigor with applied relevance. While expanding peer-reviewed publications and international collaborations could enhance his profile, his current achievements highlight significant contributions to emerging fields. Dr. Racorean’s commitment to science communication further broadens his impact beyond academia. Overall, he exemplifies the qualities of a leading researcher deserving of the Best Researcher Award, reflecting innovation, dedication, and cross-disciplinary excellence.

Misha Urooj Khan | Applied Mathematics | Best Researcher Award

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Prof. Misha Urooj Khan | Applied Mathematics | Best Researcher Award

AM (Tech) at CERN, Pakistan

Prof. Misha Urooj Khan is an accomplished electronics engineer and researcher whose multifaceted expertise spans embedded systems, quantum computing, AI/ML, and cybersecurity. 🎓 With a master’s degree focused on FPGA-based real-time SLAM and extensive experience at CERN, NCP, COMSATS, and UET, she has authored 10 journal papers, 17 conference articles, and earned 658 citations. 💡 Her work includes groundbreaking innovations like drone-resistant cryptography, AI-driven healthcare devices (USteth, ThalaScreen), and predictive analytics for disaster management. 🛰️ As an inventor on a patented drone-detection system and mentor to numerous interns and students across global institutions, she demonstrates strong leadership and social impact. 🌍 Recognized with awards and competitive startup funding, Prof. Khan’s strategic vision and interdisciplinary contributions make her a standout candidate for the Best Researcher Award. 🏆

Professional Profile

📚 Education

Professor Misha Urooj Khan holds a Master’s degree in Electronics Engineering from the University of Engineering & Technology Taxila (2019–2022), specializing in real-time FPGA-based Simultaneous Localization and Mapping (SLAM). She earned her B.Sc. in Electronics Engineering (2015–2019) from the same institution, focusing on embedded systems, FPGA design, and neural networks, and implemented an automatic wheezing detection system for her thesis. With a solid grounding in both hardware and software design, she developed strong analytical and technical skills in digital design, signal processing, and machine learning. Her rigorous academic training laid the foundation for her multidisciplinary research career, enabling seamless integration of theory and application across quantum computing, AI-enhanced embedded systems, cyber‑physical systems, and robotics. These educational credentials articulate her commitment to innovation and technology-driven problem solving.

💼 Professional Experience

Professor Khan’s career spans internationally recognized institutions such as CERN, NCP, COMSATS, UET, and King Fahd University. As a Software Developer for CERN’s CMS experiment (2024–2025), she developed database schemas, business logic, and automated migrations, contributing to high-performance scientific computing environments. At Open Quantum Initiative and NCP (2023–2026), she implemented quantum machine learning, error mitigation techniques, sensor-fusion robotics, and AI-driven predictive systems. Her research at COMSATS (2022) focused on intelligent UAV detection using edge devices. Earlier roles included designing biomedical signal-processing systems and embedded real-time detection boards (UET Taxila, 2018–2022). Recently, at King Fahd University, she’s spearheading lightweight, quantum-resistant cybersecurity protocols for drones. Across each role, she has demonstrated exceptional technical proficiency, leadership in mentoring interns, and impactful contributions to system deployment, publication, and product innovation.

🔬 Research Interests

Professor Khan’s research spans quantum computing, artificial intelligence, embedded systems, and cybersecurity—integrating these domains to solve complex real-world problems. Within quantum computing, she investigates noise modeling, error mitigation, quantum machine learning (QSVM, QNN, VQC), and oracle‑based functions on IBM quantum processors. Her AI/ML projects include domain-generalized image translation frameworks like R2TGenNet and T2RGenNet, predictive fault‑diagnosis for rotary equipment, YOLO-based object detection, and AI‑enhanced decision support. In embedded systems, she specializes in FPGA‑based SLAM, real‑time sensor fusion (LiDAR, RGB/depth cameras, IMU), and custom hardware for biomedical signal acquisition. Her current interest lies in quantum‑resistant cryptographic protocols tailored for UAV communication systems. She is passionate about bridging quantum‑AI with cybersecurity to enable secure, intelligent, and autonomous applications across healthcare, robotics, disaster response, and aerospace.

🏅 Awards and Honors

Professor Khan has earned recognition across academia, innovation, and professional excellence. She holds 658 citations (2025) and was awarded 2nd place for her presentation on “Noise Modeling and Error Mitigation on Quantum Computers” at ICTP Trieste, March 2024. Other distinctions include runner-up in the PMNIA startup pitching (June 2023), Best Presenter shields at IBCAST’23 and IEEC’21, and funding awards for USteth and ThalaScreen prototypes (2022). Her startup PAK‑AeroSafe qualified at regional and national levels and achieved runner-up status at Hackathon’23 (February 2023). Academic engagement includes first positions in university fairs (2019), community science awards since 2012, and multiple national scholastic honors. These accolades highlight her consistent excellence in research, presentation, innovation, and community engagement.

🛠️ Research Skills

Professor Khan possesses a versatile and comprehensive set of skills across computing, hardware design, and data science. She is adept in FPGA/embedded system design (Verilog/VHDL), real‑time algorithm development, and robotics navigation with ROS and Jetson hardware. Her ML proficiency spans classic and deep learning (SVM, KNN, RF, YOLOv5-v11, VGG16/19, GANs, Autoencoder), and she designs bespoke frameworks (R2TGenNet, T2RGenNet). In quantum research, she handles noise modeling, quantum gate design, error mitigation, oracle functions, and algorithm implementation on IBM quantum simulators and hardware. She also excels in sensor fusion (LiDAR/IMU/RGB/Depth), GUI creation, digital signal processing, and AI-based healthcare tools. Her programming languages include Python, Qiskit, MATLAB, and Linux-based deployment, complemented by strong skills in mentoring, proposal writing, and cross-disciplinary collaboration.

Publications Top Notes 📝

  • Title: A comparative survey of lidar-slam and lidar based sensor technologies
    Authors: MU Khan, SAA Zaidi, A Ishtiaq, SUR Bukhari, S Samer, A Farman
    Year: 2021
    Citations: 156
    Source: Mohammad Ali Jinnah University International Conference on Computing

  • Title: Artificial neural network-based cardiovascular disease prediction using spectral features
    Authors: MU Khan, S Samer, MD Alshehri, NK Baloch, H Khan, F Hussain, SW Kim, et al.
    Year: 2022
    Citations: 39
    Source: Computers and Electrical Engineering 101, Article 108094

  • Title: Classification of eye diseases and detection of cataract using digital fundus imaging (DFI) and inception-V4 deep learning model
    Authors: A Raza, MU Khan, Z Saeed, S Samer, A Mobeen, A Samer
    Year: 2021
    Citations: 34
    Source: 2021 International Conference on Frontiers of Information Technology (FIT)

  • Title: Safespace mfnet: Precise and efficient multifeature drone detection network
    Authors: MU Khan, M Dil, MZ Alam, FA Orakazi, AM Almasoud, Z Kaleem, C Yuen
    Year: 2023
    Citations: 33
    Source: IEEE Transactions on Vehicular Technology 73(3), 3106-3118

  • Title: Spectral analysis of lung sounds for classification of asthma and pneumonia wheezing
    Authors: SZH Naqvi, M Arooj, S Aziz, MU Khan, MA Choudhary
    Year: 2020
    Citations: 31
    Source: 2020 International Conference on Electrical, Communication, and Computer

  • Title: Supervised machine learning based fast hand gesture recognition and classification using electromyography (EMG) signals
    Authors: MU Khan, H Khan, M Muneeb, Z Abbasi, UB Abbasi, NK Baloch
    Year: 2021
    Citations: 29
    Source: 2021 International Conference on Applied and Engineering Mathematics (ICAEM)

  • Title: A review of system on chip (SoC) applications in Internet of Things (IoT) and medical
    Authors: A Ishtiaq, MU Khan, SZ Ali, K Habib, S Samer, E Hafeez
    Year: 2021
    Citations: 28
    Source: ICAME21, International Conference on Advances in Mechanical Engineering

  • Title: Identification of leaf diseases in potato crop using Deep Convolutional Neural Networks (DCNNs)
    Authors: Z Saeed, MU Khan, A Raza, N Sajjad, S Naz, A Salal
    Year: 2021
    Citations: 23
    Source: 16th International Conference on Emerging Technologies (ICET)

  • Title: Classification of Multi-Class Cardiovascular Disorders using Ensemble Classifier and Impulsive Domain Analysis
    Authors: MU Khan, SZZ Ali, A Ishtiaq, K Habib, T Gul, A Samer
    Year: 2021
    Citations: 22
    Source: Mohammad Ali Jinnah University International Conference on Computing

  • Title: Automated system design for classification of chronic lung viruses using non-linear dynamic system features and k-nearest neighbour
    Authors: MU Khan, A Farman, AU Rehman, N Israr, MZH Ali, ZA Gulshan
    Year: 2021
    Citations: 22
    Source: Mohammad Ali Jinnah University International Conference on Computing

  • Title: Embedded system design for real-time detection of asthmatic diseases using lung sounds in cepstral domain
    Authors: MU Khan, A Mobeen, S Samer, A Samer
    Year: 2021
    Citations: 22
    Source: 6th International Electrical Engineering Conference (IEEC)

  • Title: Stability enhancement of commercial Boeing aircraft with integration of PID controller
    Authors: AU Rehman, MU Khan, MZH Ali, MS Shah, MF Ullah, M Ayub
    Year: 2021
    Citations: 21
    Source: 2021 International Conference on Applied and Engineering Mathematics (ICAEM)

  • Title: Classification of pulmonary viruses X-ray and detection of COVID-19 based on invariant of inception-V3 deep learning model
    Authors: Z Saeed, MU Khan, A Raza, H Khan, J Javed, A Arshad
    Year: 2021
    Citations: 19
    Source: 2021 International Conference on Computing, Electronic and Electrical

  • Title: Classification of phonocardiography based heart auscultations while listening to Tilawat-e-Quran and music using vibrational mode decomposition
    Authors: MU Khan, S Samer, A Samer, A Mobeen, A Arshad, H Khan
    Year: 2021
    Citations: 18
    Source: 2021 International Conference on Applied and Engineering Mathematics (ICAEM)

  • Title: MSF-GhostNet: Computationally-Efficient YOLO for Detecting Drones in Low-Light Conditions
    Authors: M Misbah, MU Khan, Z Kaleem, A Muqaibel, MZ Alam, R Liu, C Yuen
    Year: 2024
    Citations: 5
    Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

  • Title: Multi-Sensor Fusion for Remote Sensing of Metallic and Non-metallic Object Classification in Complex Soil Environments and at Different Depths
    Authors: MU Khan, MA Kamran, WR Khan, MM Ibrahim, MU Ali, SW Lee
    Year: 2024
    Citations: 5
    Source: IEEE Transactions on Geoscience and Remote Sensing

  • Title: Mathematical Modelling and Implementation of 2DOF Standard, Parallel & Series PID Controllers
    Authors: AU Rehman, MU Khan, MT Rehman, W Shehzad, S Zaman, MW Khan
    Year: 2021
    Citations: 5
    Source: 6th International Multi-Topic ICT Conference (IMTIC)

  • Title: Diabetes Prediction Using an Optimized Variational Quantum Classifier
    Authors: WR Khan, MA Kamran, MU Khan, MM Ibrahim, KS Kim, MU Ali
    Year: 2025
    Citations: 4
    Source: International Journal of Intelligent Systems 2025 (1), Article 1351522

  • Title: Deep Learning Empowered Fast and Accurate Multiclass UAV Detection in Challenging Weather Conditions
    Authors: MU Khan, M Dil, M Misbah, FA Orakazi, MZ Alam, Z Kaleem
    Year: 2022
    Citations: 4
    Source: Conference Publication

  • Title: Brain Tumor Detection Based on Magnetic Resonance Imaging Analysis Using Segmentation, Thresholding and Morphological Operations
    Authors: MU Khan, H Khan, A Arshad, NK Baloch, A Shaheen, F Tariq
    Year: 2021
    Citations: 3
    Source: 6th International Multi-Topic ICT Conference (IMTIC)

  • Title: SMSAT: A Multimodal Acoustic Dataset and Deep Contrastive Learning Framework for Affective and Physiological Modeling of Spiritual Meditation
    Authors: A Suleman, Y Alkhrijah, MU Khan, H Khan, MAHA Faiz, MA Alawad, et al.
    Year: 2025
    Source: arXiv preprint arXiv:2505.00839

  • Title: Migration of CADI to Fence
    Authors: M Imran, MU Khan, RMA Shad, A Samantas, A Pfeiffer, J Closier
    Year: 2025

✅ Conclusion

Professor Misha Urooj Khan exemplifies a visionary researcher whose interdisciplinary breadth and leadership set her apart. With robust academic credentials, global professional experience at centers like CERN and NCP, and impactful publications and patents, she drives innovation in quantum-AI, embedded systems, robotics, and cybersecurity. Her product-oriented mindset—evident in startups like USteth and PAK‑AeroSafe—coupled with her mentoring of junior researchers, underscores both strategic vision and social impact. Her consistent accolades and scholarly presence (658 citations) affirm her research quality and influence. Combining groundbreaking technical achievements, real-world applications, and academic excellence, Professor Khan stands as a compelling candidate for top-tier research distinctions and awards.

Prantik Roy Chowdhury | Computational Mathematics | Best Researcher Award

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Dr. Prantik Roy Chowdhury | Computational Mathematics | Best Researcher Award

Post-Doctoral Associate at University of Minnesota-Duluth, United States

Dr. Prantik Roy Chowdhury is a distinguished researcher in mechanical engineering, specializing in PEM fuel cell technology 🔋, heat transfer and thermodynamics 🔥, and biomaterials 🧬. He completed his Ph.D. from North Dakota State University (NDSU) with a perfect GPA of 4.0 🎓. As a Postdoctoral Associate at the University of Minnesota-Duluth, he advances research in biofluids and thermo-fluid sciences. Dr. Chowdhury’s extensive experience includes both experimental and numerical studies in energy systems and materials science, with a focus on developing next-generation fuel cell technologies and biomedical applications. His contributions are evidenced by high-impact publications 📚, conference presentations 🎤, and hands-on leadership in laboratory and classroom settings. Dr. Chowdhury exemplifies academic excellence, innovation, and dedication, making him a strong contender for the Best Researcher Award 🏆.

Professional Profile 

Education 📚🎓

Dr. Prantik Roy Chowdhury holds a Ph.D. in Mechanical Engineering from North Dakota State University (NDSU), achieving a stellar GPA of 4.0 🌟. His academic journey began with a Bachelor of Technology (B.Tech.) from West Bengal University of Technology, where he excelled in Mechanical Engineering fundamentals. Passionate about research, he pursued advanced studies in PEM fuel cells, heat transfer, and thermofluids, building a solid theoretical foundation and hands-on laboratory skills 🔬. At NDSU, he conducted pioneering work in fuel cell technology, contributing significantly to the field’s academic and industrial advancement. Dr. Chowdhury’s educational background reflects his commitment to continuous learning and professional growth, positioning him as a leader in engineering research and innovation 🛠️.

Professional Experience 🛠️🏢

Dr. Prantik Roy Chowdhury is currently a Postdoctoral Associate at the University of Minnesota-Duluth, where he leads projects on biofluids and thermo-fluid sciences 🔬💡. Prior to this, he served as a Research Assistant at North Dakota State University, contributing significantly to PEM fuel cell technology and thermal management systems 🔋🔥. His work integrates experimental and numerical methods, demonstrating a strong interdisciplinary approach. He has also engaged in mentoring undergraduate and graduate students, fostering academic growth and research skills 📖👥. Dr. Chowdhury’s diverse experiences across top-tier institutions and collaborative research environments have honed his abilities to manage complex projects, publish impactful papers 📑, and secure funding opportunities, highlighting his leadership in the mechanical engineering domain 🚀.

Research Interest 🔬💡

Dr. Prantik Roy Chowdhury’s research interests span PEM fuel cells, heat transfer, thermofluids, and biomaterials 🧪🔥🧬. His work focuses on advancing the efficiency and durability of fuel cell systems through innovative material design and thermal management solutions. He is particularly passionate about exploring microfluidic applications in biofluids, developing sustainable energy systems, and integrating computational and experimental approaches to solve real-world engineering challenges 🌍🛠️. Dr. Chowdhury is also interested in interdisciplinary research that connects mechanical engineering with biomedical engineering, aiming to bridge gaps between energy and health technologies. His dedication to cutting-edge research has led to multiple high-impact publications and conference presentations, shaping the future of sustainable energy and bioengineering 🚀📚.

Award and Honor 🏆🎖️

Dr. Prantik Roy Chowdhury’s academic and professional excellence has been recognized with prestigious awards and honors 🌟. Notably, he earned the Graduate Research Fellowship at North Dakota State University for his outstanding contributions to PEM fuel cell research 🔬. His exceptional academic performance, including a perfect GPA of 4.0, was consistently recognized through merit-based scholarships and research assistantships 📖🏅. Dr. Chowdhury has also been invited to present at leading conferences, showcasing his innovative work on energy systems and biomaterials 📢💼. These honors underscore his commitment to academic excellence and his leadership in the field. His accolades reflect a career dedicated to innovation, knowledge dissemination, and impactful research that addresses global challenges 🌍🔋.

Research Skill 🔧📊

Dr. Prantik Roy Chowdhury demonstrates a broad and deep skill set in mechanical engineering research 🔬⚙️. His expertise spans computational fluid dynamics (CFD), thermal analysis, and numerical simulations, essential for optimizing PEM fuel cell and biofluid systems 🧪🖥️. He is proficient in laboratory-based experimentation, integrating hands-on testing with advanced diagnostic techniques 🔍🛠️. Dr. Chowdhury is skilled in multi-physics modeling, finite element analysis (FEA), and data analytics, enabling him to bridge theoretical concepts with practical engineering solutions 📊💡. He excels at writing high-impact publications, grant proposals, and mentoring students, reflecting his leadership in research and education 📚👥. His multifaceted skills position him as a transformative researcher in sustainable energy and biomaterials 🛤️🚀.

Publications Top Notes📝

• Bone marrow stromal cells interaction with titanium; Effects of composition and surface modification

  • Authors: MK Duvvuru, W Han, PR Chowdhury, S Vahabzadeh, F Sciammarella, et al.

  • Year: 2019

  • Citations: 20

  • Source: PLoS One 14 (5), e0216087

• Comparative and sensitivity analysis of operating conditions on the performance of a high temperature PEM fuel cell

  • Authors: PR Chowdhury, AC Gladen

  • Year: 2024

  • Citations: 6

  • Source: International Journal of Hydrogen Energy 50, 1239-1256

• Deposition of magnesium on surface-modified titanium for biomedical applications

  • Authors: PR Chowdhury, S Vahabzadeh

  • Year: 2022

  • Citations: 2

  • Source: Journal of Materials Research 37 (16), 2635-2644

• Surface Modification of Titanium for Orthopedic and Drug Delivery Applications

  • Authors: PR Chowdhury

  • Year: 2020

  • Citations: 1

  • Source: Northern Illinois University

• Regulation of Osteogenic and Angiogenic Markers in Alkali-Treated Titanium for Hard Tissue Engineering Applications

  • Authors: PR Chowdhury, D Kling, MR Markiewicz, P Bothwell, S Vahabzadeh

  • Year: 2024

  • Source: Journal of Oral Implantology 50 (6), 636-643

• Design of Flow Fields for High-Temperature PEM Fuel Cells Using Computational Fluid Dynamics

  • Authors: PR Chowdhury, AC Gladen

  • Year: 2024

  • Source: Energies 17 (19), 4898

• Design and Parametric Study to Improve the Performance of High Temperature Proton Exchange Membrane Fuel Cell

  • Authors: PR Chowdhury

  • Year: 2024

  • Source: North Dakota State University

• Impact of Temperature and Ethanol Concentration on High Temperature Direct Ethanol-Based Proton Exchange Membrane Fuel Cell

  • Authors: PR Chowdhury, AC Gladen

  • Year: 2023

  • Source: Energy Sustainability 87189, V001T07A001

• Design and Fabrication of a Robotic Arm for Interior Wall Painting

  • Authors: SCB Nwomey Subayer, Prantik Roy Chowdhury, Anik Samadder

  • Year: 2015

  • Source: ICMERE2015

• Development of a Microcontroller-based Data Acquisition System to Capture Analog Signals

  • Authors: PRC Kazi Afzalur Rahman

  • Year: 2014

  • Source: ICMERE2013

Conclusion 🌟📝

Dr. Prantik Roy Chowdhury exemplifies the qualities of a visionary researcher and dedicated educator in mechanical engineering 🔬🌍. His robust educational background, impactful research, and professional achievements position him at the forefront of energy systems and biomaterials innovation ⚡️🧬. With a commitment to interdisciplinary collaboration and real-world problem-solving, Dr. Chowdhury drives progress in fuel cell technology, thermal management, and biomedical applications 🔋🔥. His impressive portfolio of awards and high-impact publications underscores his influence in the scientific community 📚🏅. As a Postdoctoral Associate, he continues to inspire excellence and foster academic growth among students and peers. Dr. Chowdhury is a strong contender for the Best Researcher Award, embodying excellence, dedication, and innovation 🏆✨.

Mohammad Ali Nematollahi | Graph Theory | Best Academic Researcher Award

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Assist. Prof. Dr. Mohammad Ali Nematollahi | Graph Theory | Best Academic Researcher Award

Assistant Professor atFasa University, Iran

Dr. Mohammad Ali Nematollahi 📚 is a distinguished Assistant Professor at Fasa University, Iran, known for his significant contributions to mathematics and computer science. He holds a Ph.D. from Sharif University of Technology and has published extensively in top-tier journals, covering topics like spectral graph theory, Seidel energy, and machine learning applications in medicine 🤖🩺. With a strong teaching portfolio, Dr. Nematollahi has inspired many students while maintaining a consistent record of academic excellence 🏆. His numerous awards, including a Silver Medal at the International Mathematics Olympiad for University Students, highlight his dedication and talent. Though his international collaborations could expand further, his interdisciplinary research and exceptional teaching make him a standout candidate for recognition as a Best Academic Researcher 🌐.

Professional Profile 

Education 🎓

Dr. Mohammad Ali Nematollahi began his academic journey at Andisheh Magnet High School in Shiraz, where he excelled with top GPAs in both high school and pre-university studies. He then earned his B.Sc., M.Sc., and Ph.D. in Mathematics from Sharif University of Technology, Tehran—one of Iran’s most prestigious institutions. His graduate research delved into Pfister’s Local-Global Principle and the Spectral Theory of Signed Graphs and Digraphs, under renowned supervisors. This strong educational foundation equipped him with a robust understanding of both pure and applied mathematics, fostering interdisciplinary research and teaching excellence. His academic record, marked by consistently high grades and prestigious scholarships, reflects his dedication and passion for learning, setting the stage for a dynamic and influential academic career. 🌟

Professional Experience 💼

Dr. Mohammad Ali Nematollahi serves as an Assistant Professor at Fasa University’s Department of Computer Sciences, where he bridges mathematics and computer science through teaching and research. His academic roles include teaching courses like Graph Theory, Advanced Programming (Python), Foundations of Combinatorics, and Machine Learning Applications 📊. Earlier, he honed his teaching skills as a Teaching Assistant at Sharif University of Technology, covering Calculus, Linear Algebra, and Differential Equations. Dr. Nematollahi’s experience also extends to supervising undergraduate and graduate students, mentoring them in complex research areas. His diverse experience showcases his versatility, making him a dynamic educator and researcher with expertise that resonates across disciplines. 💼

Research Interest 🔬

Dr. Mohammad Ali Nematollahi’s research interests span a fascinating intersection of graph theory, spectral analysis, combinatorics, and applied machine learning. His work on Seidel energy of graphs, spectral characterizations of signed cycles, and circular zero-sum flows has advanced theoretical understanding of graphs 📈. Additionally, his research extends to machine learning applications, notably in medical diagnostics, disease prediction, and sentiment analysis of social media data. This interdisciplinary approach highlights his ability to tackle both theoretical and practical challenges, positioning him as a forward-thinking researcher whose work benefits academia and society alike. His passion for bridging abstract mathematics with real-world problems drives his continuous exploration of innovative solutions. 🌐

Awards and Honors 🏅

Dr. Mohammad Ali Nematollahi’s academic journey is marked by numerous awards and honors, underscoring his dedication and talent. Early in his career, he ranked in the top 0.1% in the Mathematics Nationwide Entrance Exam and secured admission to Sharif University of Technology. His remarkable achievements continued with a silver medal at the International Mathematics Olympiad for University Students, ranking fifth among top talents. He also won exceptional talent scholarships at both M.Sc. and Ph.D. levels. These accolades reflect his academic excellence and unwavering commitment to advancing mathematical knowledge. Each honor affirms his standing as a distinguished scholar whose contributions resonate globally. 🥇

Research Skills 💻

Dr. Mohammad Ali Nematollahi boasts an impressive skill set, seamlessly blending theoretical mathematics and computational techniques. He is proficient in Python, Mathematica, and SageMath, enabling him to model complex systems and analyze large datasets. His expertise extends to machine learning algorithms, supporting research in medical diagnostics and disease prediction. He is also adept at using LaTeX for professional documentation and Microsoft Office for academic administration 📑. His technical skills empower him to tackle multifaceted research challenges, from graph theory to real-world applications. This diverse toolbox allows him to develop innovative solutions, bridging theory and practice with precision and creativity. 🤖

Publications Top Notes

  • Effective class-imbalance learning based on SMOTE and convolutional neural networks
    Authors: JH Joloudari, A Marefat, MA Nematollahi, SS Oyelere, S Hussain
    Year: 2023
    Citations: 132
    Source: Applied Sciences 13(6), 4006

  • BERT-deep CNN: State of the art for sentiment analysis of COVID-19 tweets
    Authors: JH Joloudari, S Hussain, MA Nematollahi, R Bagheri, F Fazl, …
    Year: 2023
    Citations: 65
    Source: Social Network Analysis and Mining 13(1), 99

  • Prognosis prediction in traumatic brain injury patients using machine learning algorithms
    Authors: H Khalili, M Rismani, MA Nematollahi, MS Masoudi, A Asadollahi, …
    Year: 2023
    Citations: 44
    Source: Scientific Reports 13(1), 960

  • GSVMA: a genetic support vector machine ANOVA method for CAD diagnosis
    Authors: J Hassannataj Joloudari, F Azizi, MA Nematollahi, R Alizadehsani, …
    Year: 2022
    Citations: 26
    Source: Frontiers in Cardiovascular Medicine 8, 760178

  • Proof of a conjecture on the Seidel energy of graphs
    Authors: S Akbari, M Einollahzadeh, MM Karkhaneei, MA Nematollahi
    Year: 2020
    Citations: 25
    Source: European Journal of Combinatorics 86, 103078

  • Spectral characterizations of signed cycles
    Authors: S Akbari, F Belardo, E Dodongeh, MA Nematollahi
    Year: 2018
    Citations: 22
    Source: Linear Algebra and Its Applications 553, 307-327

  • DNN-GFE: a deep neural network model combined with global feature extractor for COVID-19 diagnosis based on CT scan images
    Authors: JH Joloudari, F Azizi, I Nodehi, MA Nematollahi, F Kamrannejhad, …
    Year: 2021
    Citations: 20
    Source: EasyChair 6330

  • Body composition predicts hypertension using machine learning methods: a cohort study
    Authors: MA Nematollahi, S Jahangiri, A Asadollahi, M Salimi, A Dehghan, …
    Year: 2023
    Citations: 18
    Source: Scientific Reports 13(1), 6885

  • CCTCOVID: COVID-19 detection from chest X-ray images using Compact Convolutional Transformers
    Authors: A Marefat, M Marefat, J Hassannataj Joloudari, MA Nematollahi, …
    Year: 2023
    Citations: 13
    Source: Frontiers in Public Health 11, 1025746

  • Association and predictive capability of body composition and diabetes mellitus using artificial intelligence: a cohort study
    Authors: MA Nematollahi, A Askarinejad, A Asadollahi, M Salimi, M Moghadami, …
    Year: 2022
    Citations: 7

  • Mixed paths and cycles determined by their spectrum
    Authors: S Akbari, A Ghafari, M Nahvi, MA Nematollahi
    Year: 2020
    Citations: 5
    Source: Linear Algebra and Its Applications 586, 325-346

  • A short proof of Haemers’ conjecture on the Seidel energy of graphs
    Authors: M Einollahzadeh, MA Nematollahi
    Year: 2024
    Citations: 3
    Source: Linear Algebra and Its Applications 695, 75-78

  • A cohort study on the predictive capability of body composition for Diabetes Mellitus using machine learning
    Authors: MA Nematollahi, A Askarinejad, A Asadollahi, M Bazrafshan, S Sarejloo, …
    Year: 2024
    Citations: 3
    Source: Journal of Diabetes & Metabolic Disorders 23(1), 773-781

  • Improving Prediction of Mortality in ICU via Fusion of SelectKBest with SMOTE Method and Extra Tree Classifier
    Authors: M Maftoun, JH Joloudari, O Zare, M Khademi, A Atashi, MA Nematollahi, …
    Year: 2024
    Citations: 3
    Source: International Work-Conference on the Interplay Between Natural and …

  • Improving a lower bound for Seidel energy of graphs
    Authors: MR Oboudi, MA Nematollahi
    Year: 2023
    Citations: 3
    Source: MATCH Commun. Math. Comput. Chem 89, 489-502

Conclusion ✨

Dr. Mohammad Ali Nematollahi exemplifies excellence in academia through his outstanding education, professional experience, research interests, awards, and technical skills. His dedication to advancing mathematical knowledge and applying it to real-world challenges makes him a leading figure in his field. His passion for teaching and mentoring nurtures the next generation of scholars, while his collaborative spirit and interdisciplinary approach enhance the global impact of his research. As a candidate for the Best Academic Researcher Award, Dr. Nematollahi stands out for his remarkable contributions, innovation, and unwavering commitment to excellence. He is undoubtedly a deserving nominee for this prestigious recognition. 🏆

Subhan Ullah | Applied Mathematics | Best Researcher Award

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Dr. Subhan Ullah | Applied Mathematics | Best Researcher Award

Teacher at University of Malakand, Pakistan

Dr. Subhan Ullah is a dedicated Pakistani researcher in applied mathematics, specializing in fluid mechanics 🌊, nanofluids 🔬, and epidemic modeling 🦠. With a Ph.D. from the University of Malakand, his research on Jeffery-Hamel flows and thermodynamic analyses in convergent/divergent channels demonstrates a commitment to solving real-world engineering challenges 🔧. Dr. Ullah’s collaborative publications in reputable journals reflect his strong team-oriented approach 🤝. As a lecturer and mentor, he inspires students at various educational levels 📚. He is passionate about research and education, aiming to contribute both academically and practically. To elevate his candidacy for top-tier awards 🏆, Dr. Ullah can further strengthen his international visibility, leadership in research, and innovation, ensuring a lasting impact in the global mathematics community 🌍.

Professional Profile 

Education 🎓

Dr. Subhan Ullah’s academic journey is deeply rooted in mathematics, marked by his Ph.D. from the University of Malakand (2020–2023) with a dissertation on heat transfer in Jeffery-Hamel flows 🌊. He earned an M.S. in Mathematics (2012–2014) from Bacha Khan University, exploring the dynamics of epidemic diseases 🦠, and an M.Sc. (2009–2011) from the University of Malakand. His educational foundation was laid through a B.Sc. (2005–2007) and earlier schooling at Government Centennial Model High School Timergara. This solid academic progression showcases his commitment to mathematical sciences 📐, equipping him with advanced theoretical and analytical skills essential for tackling complex fluid dynamics, mathematical biology, and other applied mathematics challenges.

Professional Experience 💼

Dr. Subhan Ullah is an accomplished academician with extensive teaching and research experience. He currently serves as a full-time researcher at the University of Malakand, focusing on applied mathematics and interdisciplinary projects 🤝. His earlier roles as a Lecturer at Bukhara College of Science & Technology and The Educator School & College Timergara highlight his dedication to educating undergraduate and postgraduate students 📚. Additionally, he has contributed significantly as a government school teacher, nurturing young minds and fostering a positive learning environment. Throughout his career, Dr. Ullah has consistently designed innovative curricula, organized seminars, and mentored students, reflecting his passion for advancing mathematics education and research excellence in Pakistan and beyond 🇵🇰.

Research Interest 🔍

Dr. Subhan Ullah’s research interests span fluid mechanics 🌊, with a focus on nanofluids 🔬 and fluid flows in convergent/divergent channels, where he explores complex heat transfer and thermodynamic phenomena. His passion extends to mathematical biology, particularly population dynamics, epidemic dynamics, and infectious disease modeling 🦠, reflecting a multidisciplinary approach to real-world problems. His enthusiasm for applied mathematics drives him to investigate diverse research challenges, recognizing its versatile role in addressing engineering, environmental, and biological systems 🌍. This dynamic research portfolio positions Dr. Ullah at the forefront of mathematical modeling, contributing valuable insights and practical solutions to contemporary scientific and industrial challenges 🚀.

Awards and Honors 🏅

Dr. Subhan Ullah has demonstrated notable achievements in research and academia, earning recognition through impactful publications and conference presentations. His research contributions to high-impact journals—such as Physics Letters A, Chaos, Solitons & Fractals, and the International Journal of Energy Research—underscore his commitment to excellence 📈. He has actively participated in academic conferences, including the International Conference “Mathematical Sciences” at the University of Malakand, sharing his innovative research with the global scientific community 🌐. These accomplishments reflect his dedication to advancing mathematical sciences and position him as a deserving candidate for prestigious research awards that celebrate innovation, impact, and leadership in applied mathematics.

Research Skills 🧪

Dr. Subhan Ullah possesses a robust research skillset encompassing mathematical modeling, computational simulations, and theoretical analysis of fluid dynamics and nanofluid flows 🔬. His proficiency in tools like MATLAB, Mathematica, LaTeX, and LYX empowers him to tackle complex differential equations and thermodynamic problems efficiently 💻. He is adept at interdisciplinary collaboration, contributing to projects that intersect engineering, physics, and biological systems 🤝. His skills extend to mentoring undergraduate and graduate researchers, guiding them in research design, data analysis, and academic writing ✍️. These capabilities collectively enable Dr. Ullah to produce high-quality research that bridges theory and practical application, reinforcing his status as a leading researcher in applied mathematics.

Publications Top Notes

Title:
“Heat transfer augmentation of Jeffery–Hamel hybrid nanofluid in a stretching convergent/divergent channel through porous medium.”

Authors:
S. Ullah, Subhan; H.A.S. Ghazwani, Hassan Ali S.; D.N. Khan, Dolat N.; Z.A. Khan, Zareen Abdulhameed.

Year:
2025.

Citation:
S. Ullah, Subhan, H.A.S. Ghazwani, Hassan Ali S., D.N. Khan, Dolat N., and Z.A. Khan, Zareen Abdulhameed (2025). “Heat transfer augmentation of Jeffery–Hamel hybrid nanofluid in a stretching convergent/divergent channel through porous medium.” AIMS Mathematics.

Source:
AIMS Mathematics (2025). Link currently unavailable.

Conclusion 📌

Dr. Subhan Ullah stands out as a highly motivated researcher with a strong academic foundation, extensive teaching experience, and a dynamic research portfolio 📚. His contributions to fluid mechanics, nanofluids, and epidemic modeling underscore his commitment to tackling real-world challenges through applied mathematics 🌍. While his achievements in research and publication are commendable, further strengthening his international collaborations, leading research projects, and securing competitive funding would enhance his candidacy for prestigious awards 🏆. Dr. Ullah’s passion for education, interdisciplinary research, and mentorship ensures that he will continue making impactful contributions to the mathematical sciences community, both in Pakistan and globally, fostering innovation and academic excellence 🚀.

Sabre Kais | Information Theory | Best Researcher Award

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Prof. Dr. Sabre Kais | Information Theory | Best Researcher Award

Goodnight Distinguished Chair in Quantum Computing at North Carolina State University, United States

Prof. Dr. Sabre Kais is a distinguished scholar in quantum information science, theoretical chemistry, and quantum computing. He serves as a Professor of Chemistry at Purdue University and leads the Quantum Information Science Group. 🧪🔬 His pioneering research focuses on quantum phase transitions, entanglement, and applying quantum algorithms to solve complex chemical problems. With over 250 peer-reviewed publications and multiple prestigious awards, including fellowships from the American Physical Society and the American Association for the Advancement of Science, he has significantly advanced interdisciplinary science. 📚🌐 As a dedicated educator and mentor, Prof. Kais continues to shape future leaders in quantum technologies while spearheading collaborations across physics, chemistry, and computer science. His visionary work drives innovation at the intersection of theory and application in emerging quantum fields. 💡⚛️

Professional Profile

Education 🎓📘

Prof. Dr. Sabre Kais earned his Ph.D. in Chemical Physics from the University of California, Berkeley, where he laid the foundation for his career in theoretical and quantum chemistry. Prior to that, he completed his undergraduate studies in Chemistry with honors, showcasing early aptitude in mathematics and physics. His academic training was deeply rooted in interdisciplinary approaches, enabling him to bridge concepts from chemistry, physics, and computer science. This educational background equipped him with a unique ability to investigate complex quantum systems and foster innovative solutions in quantum computation and information theory. 📚💡 His deep commitment to education continues through curriculum development and mentoring, nurturing future leaders in quantum science and technology.

Professional Experience 🧪👨‍🏫

Prof. Kais is a full professor at Purdue University, where he leads the Quantum Information Science Group. He has held visiting positions and collaborative appointments at premier research institutions worldwide. 🏛️🌍 His career spans over three decades of teaching, supervising graduate students, and conducting frontier research. At Purdue, he is also affiliated with the Department of Physics and the Department of Computer Science, reflecting his truly interdisciplinary approach. He has served on editorial boards, national review panels, and has contributed to shaping quantum education policy. His professional journey is marked by leadership in large-scale collaborative research projects, including NSF and DOE-funded initiatives that focus on quantum algorithms and simulations. 🧠🖥️ His rich experience reflects a commitment to advancing both academia and cutting-edge quantum technology.

Research Interests ⚛️🔬

Prof. Kais’s research spans quantum computing, quantum information, theoretical chemistry, and many-body systems. His work focuses on quantum phase transitions, quantum entanglement, and the application of quantum algorithms to chemical problems. 🧬🧠 He is particularly interested in solving classically intractable problems using quantum resources, including simulating molecular structures, reaction dynamics, and quantum control mechanisms. He also explores quantum machine learning and quantum chaos, positioning himself at the frontier of quantum science. 🔍🧑‍🔬 Prof. Kais integrates advanced mathematical techniques with physical insights, enabling breakthroughs in quantum simulations. His research bridges theory and practical quantum computation, aiming to influence next-generation quantum technologies and real-world applications in chemistry, materials science, and drug discovery.

Awards and Honors 🏅🎖️

Prof. Kais has received numerous prestigious awards recognizing his excellence in research and scientific contributions. He is a Fellow of the American Physical Society (APS) and the American Association for the Advancement of Science (AAAS), honors bestowed on scientists with exceptional achievements. 🌟🔬 His accolades include the Purdue University Research Excellence Award, NSF CAREER Award, and multiple keynote speaker invitations at top international conferences. His distinguished record of publication and leadership in quantum research has earned him recognition as a global thought leader in quantum chemistry and computing. 📜🌍 These honors reflect both the depth of his scientific impact and his dedication to advancing interdisciplinary research at the intersection of chemistry, physics, and quantum information science.

Research Skills 💻

Prof. Kais possesses a comprehensive set of research skills, including quantum algorithm design, numerical simulations, mathematical modeling, and quantum theory development. He is proficient in quantum programming frameworks and high-performance computing, applying them to model atomic and molecular systems. 🧠🧮 His interdisciplinary capabilities enable him to tackle problems across chemistry, physics, and computer science. He demonstrates expertise in quantum entanglement analysis, phase transition modeling, and information-theoretic approaches to molecular dynamics. 🧪🧾 His strong analytical skills, combined with an ability to integrate theory with computation, make him a leader in quantum information science. He continually evolves his technical toolbox to adapt to new challenges and collaborates across domains to foster innovation.

Publications Top Notes

  • Title: Revealing the role of organic cations in hybrid halide perovskite CH3NH3PbI3
    Authors: C. Motta; F. El-Mellouhi; S. Kais; N. Tabet; F. Alharbi; S. Sanvito
    Year: 2015
    Citations: 740
    Source: Nature Communications

  • Title: Qudits and high-dimensional quantum computing
    Authors: Y. Wang; Z. Hu; B.C. Sanders; S. Kais
    Year: 2020
    Citations: 521
    Source: Frontiers in Physics

  • Title: Reduced-density-matrix mechanics
    Authors: A.J. Coleman
    Year: 2007
    Citations: 392
    Source: Book

  • Title: Manipulation of molecules with electromagnetic fields
    Authors: M. Lemeshko; R.V. Krems; J.M. Doyle; S. Kais
    Year: 2013
    Citations: 353
    Source: Molecular Physics

  • Title: Theoretical limits of photovoltaics efficiency
    Authors: F.H. Alharbi; S. Kais
    Year: 2015
    Citations: 290
    Source: Renewable and Sustainable Energy Reviews

  • Title: Quantum algorithm and circuit design solving the Poisson equation
    Authors: Y. Cao; A. Papageorgiou; I. Petras; J. Traub; S. Kais
    Year: 2013
    Citations: 249
    Source: New Journal of Physics

  • Title: Quantum annealing for prime factorization
    Authors: S. Jiang; K.A. Britt; A.J. McCaskey; T.S. Humble; S. Kais
    Year: 2018
    Citations: 243
    Source: Scientific Reports

  • Title: Quantum machine learning for electronic structure calculations
    Authors: R. Xia; S. Kais
    Year: 2018
    Citations: 204
    Source: Nature Communications

  • Title: Application of quantum-inspired tensor networks to optimize federated learning systems
    Authors: A.S. Bhatia, Amandeep Singh; M.K. Saggi, Mandeep Kaur; S. Kais, Sabre
    Year: 2025
    Source: Quantum Machine Intelligence

  • Title: Open-quantum-system simulation through exploiting noise on quantum computers
    Authors: S. Kais, Sabre; D.A. Mazziotti, David A.
    Year: 2025
    Source: Physical Review A

  • Title: Entropy-Assisted Quality Pattern Identification in Finance
    Authors: R. Gupta, Rishabh; S. Gupta, Shivam; J. Singh, Jaskirat; S. Kais, Sabre
    Year: 2025
    Source: Entropy

  • Title: Quantum Algorithms and Applications for Open Quantum Systems
    Authors: L.H. Delgado-Granados, Luis H.; T.J. Krogmeier, Timothy J.; L.A.M. Sager-Smith, Lee Ann M.; K. Head-Marsden, Kade; D.A. Mazziotti, David A.
    Year: 2025
    Citations: 2
    Source: Review Article

  • Title: Refined phase diagram for a spin-1 system exhibiting a Haldane phase
    Authors: M. Mousa, Mohamad; B. Wehefritz-Kaufmann, Birgit; S. Kais, Sabre; S.X. Cui, Shawn Xingshan; R.M. Kaufmann, Ralph M.
    Year: 2025
    Source: Physical Review B

  • Title: Designing Variational Ansatz for Quantum-Enabled Simulation of Non-Unitary Dynamical Evolution – An Excursion into Dicke Superradiance
    Authors: S. Shivpuje, Saurabh; M. Sajjan, Manas; Y. Wang, Yuchen; Z. Hu, Zixuan; S. Kais, Sabre
    Year: 2025
    Citations: 1
    Source: Advanced Quantum Technologies

  • Title: The Qubit Information Logic Theory for Understanding Multi-Qubit Entanglement and Designing Exotic Entangled States
    Authors: Z. Hu, Zixuan; S. Kais, Sabre
    Year: 2025
    Source: Annalen der Physik

  • Title: Experimental test of generalized multipartite entropic uncertainty relations
    Authors: Z. Wang, Zhaoan; B. Xie, Bofu; F. Ming, Fei; G. Guo, Guangcan; S. Kais, Sabre
    Year: 2024
    Citations: 1
    Source: Physical Review A

  • Title: Entropy corrected geometric Brownian motion
    Authors: R. Gupta, Rishabh; E.A. Drzazga-Szczȩśniak, Ewa A.; S. Kais, Sabre; D. Szczȩśniak, Dominik
    Year: 2024
    Citations: 5
    Source: Scientific Reports

  • Title: Psitrum: An open source simulator for universal quantum computers
    Authors: M.Y. Alghadeer, Mohammed Y.; E. Aldawsari, Eid; R. Selvarajan, Raja; S. Kais, Sabre; F.H. Alharbi, Fahhad H.
    Year: 2024
    Source: IET Quantum Communication.

Conclusion 🌟📌

Prof. Dr. Sabre Kais is a trailblazer in the realm of quantum science, seamlessly blending theoretical expertise with practical innovation. His contributions span across education, research, and global scientific leadership, making him a respected figure in multiple disciplines. ⚛️🌐 Through a career marked by scholarly excellence, mentorship, and interdisciplinary collaboration, he continues to shape the future of quantum computing and molecular science. His visionary outlook, combined with a tireless commitment to knowledge creation and dissemination, positions him at the forefront of emerging quantum technologies. 📈🔭 Prof. Kais’s legacy is one of bridging disciplines to unravel the complexities of the quantum world and inspire future generations of scientists.