Iliyas Khan | Statistics | Best Researcher Award

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Dr. Iliyas Khan | Statistics | Best Researcher Award

Teaching Assistance at Universiti Teknologi PETRONAS, Malaysia

Dr. Iliyas Karim Khan is a dedicated researcher specializing in machine learning, statistical modeling, forecasting, and big data analysis. He holds a Ph.D. from Universiti Teknologi PETRONAS (UTP), Malaysia, along with advanced degrees in statistics from Peshawar University, Pakistan. With a strong publication record in Q1 journals, his research focuses on optimizing clustering algorithms, particularly in K-means clustering and data science applications. His expertise extends to programming and statistical tools such as Python, SPSS, Stata, and EViews. Dr. Khan has gained extensive teaching experience, serving as a Teaching Assistant at UTP and a Subject Specialist in Pakistan. He was recognized with a Publication Recognition Achievement (2024) at UTP, underscoring his research contributions. His work is instrumental in improving data-driven decision-making and computational efficiency, making him a valuable asset in the academic and research community. His commitment to innovation and education positions him as a promising leader in his field.

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Education

Dr. Iliyas Karim Khan has a strong academic background in statistics and data science. He earned his Ph.D. in 2024 from Universiti Teknologi PETRONAS (UTP), Malaysia, focusing on optimizing machine learning algorithms. Prior to that, he completed an M.Phil. (2016) and M.Sc. (2014) in Statistics from Peshawar University, Pakistan, and a B.Sc. in Statistics (2012) from SBBU Sheringhal, Upper Dir, Pakistan. His foundational studies in science and engineering were completed at BISE Peshawar, along with a B.Ed. (2015) for pedagogical training. His educational journey reflects his commitment to advanced research in big data analysis, forecasting, and statistical modeling. Throughout his studies, he has demonstrated exceptional analytical skills, contributing to high-impact research in data clustering and computational efficiency. His academic achievements have positioned him as a promising researcher in the field of machine learning and statistical analytics, making significant contributions to data science methodologies.

Professional Experience

Dr. Iliyas Karim Khan has gained extensive teaching and research experience across multiple institutions. He worked as a Teaching Assistant at Universiti Teknologi PETRONAS (UTP), Malaysia, where he was actively involved in data science research and statistical analysis. In Pakistan, he served as a Subject Specialist at GHSS Bang Chitral for four years, strengthening his expertise in applied statistics and data analysis. His teaching career also includes one year at Abbottabad University of Science and Technology, where he mentored students in statistical modeling and machine learning techniques. Additionally, he completed an internship at the University of Peshawar and taught at Darban Degree College, Chitral. His experience encompasses curriculum development, student mentoring, and advanced research in statistical computing, making him an accomplished educator and researcher. His hands-on expertise in Python, SPSS, Stata, and EViews further enhances his ability to train future data scientists and statisticians.

Research Interest

Dr. Iliyas Karim Khan’s research revolves around machine learning, big data analytics, statistical modeling, and forecasting. His primary focus is on clustering algorithms, particularly enhancing the K-means clustering method for improved efficiency and accuracy. His work addresses key challenges in data science, such as non-spherical data, outlier handling, and optimal cluster selection, which have significant implications for AI-driven decision-making. Additionally, he explores computational time optimization and statistical accuracy in clustering techniques, contributing to the advancement of data-driven methodologies. His studies extend to forecasting models, applied statistical techniques, and real-world big data applications. Through numerous Q1 journal publications, he has proposed innovative solutions for refining data science models. His research is highly relevant in industries reliant on machine learning, artificial intelligence, and predictive analytics, positioning him as a key contributor to the evolution of data-centric technologies and computational intelligence.

Awards and Honors

Dr. Iliyas Karim Khan’s academic excellence and research contributions have been recognized through prestigious accolades. In 2024, he received the “Publication Recognition Achievement” award from Universiti Teknologi PETRONAS (UTP), Malaysia, honoring his impactful research in machine learning and statistical analysis. His Q1 journal publications in high-impact journals demonstrate his ability to produce innovative and widely acknowledged research. Additionally, his contributions to data clustering and computational efficiency have been well-received within the academic and research communities. His work on addressing K-means clustering limitations and enhancing algorithmic efficiency has been cited extensively, highlighting its significance in data science and artificial intelligence. His growing recognition in machine learning and big data analytics marks him as a promising scholar in his field. Through his research, he continues to make valuable contributions that shape the future of data-driven decision-making and statistical computing.

Conclusion

Dr. Iliyas Karim Khan is an exceptional researcher, educator, and innovator in the field of machine learning, statistical modeling, and big data analysis. His strong academic background, extensive teaching experience, and high-impact research make him a significant contributor to computational intelligence and data science advancements. His studies on enhancing K-means clustering efficiency, outlier handling, and computational time optimization have added valuable insights to the field. Through prestigious publications and academic honors, he has demonstrated his expertise in refining statistical methodologies for real-world applications. His proficiency in Python, SPSS, Stata, and advanced statistical techniques enables him to bridge the gap between theoretical advancements and practical applications in data science. As he continues to explore new frontiers in machine learning and predictive analytics, his work is expected to have a lasting impact on data-driven industries and AI-based decision-making systems.

Publications Top Noted

  • Title: Determining the Optimal Number of Clusters by Enhanced Gap Statistic in K-Mean Algorithm
    Authors: Iliyas Karim Khan, HB Daud, NB Zainuddin, R Sokkalingam, M Farooq, ME Baig, …
    Year: 2024
    Citations: 7
    Source: Egyptian Informatics Journal, Volume 27, Article 100504

  • Title: Numerical Solution of Heat Equation Using Modified Cubic B-Spline Collocation Method
    Authors: M Iqbal, N Zainuddin, H Daud, R Kanan, R Jusoh, A Ullah, Iliyas Karim Khan
    Year: 2024
    Citations: 3
    Source: Journal of Advanced Research in Numerical Heat Transfer, Volume 20, Pages 23-35

  • Title: Numerical Solution by Kernelized Rank Order Distance (KROD) for Non-Spherical Data Conversion to Spherical Data
    Authors: Iliyas Karim Khan, HB Daud, R Sokkalingam, NB Zainuddin, A Abdussamad, …
    Year: 2024
    Citations: 2
    Source: AIP Conference Proceedings, Volume 3123 (1)

  • Title: A Modified Basis of Cubic B-Spline with Free Parameter for Linear Second Order Boundary Value Problems: Application to Engineering Problems
    Authors: M Iqbal, N Zainuddin, H Daud, R Kanan, H Soomro, R Jusoh, A Ullah, …
    Year: 2024
    Citations: 1
    Source: Journal of King Saud University-Science, Volume 36 (9), Article 103397

  • Title: Standardizing Reference Data in Gap Statistic for Selection of Optimal Number of Clusters in K-Means Algorithm
    Authors: Iliyas Karim Khan, H Daud, N Zainuddin, R Sokkalingam
    Year: 2025
    Source: Alexandria Engineering Journal, Volume 118, Pages 246-260

  • Title: A Hybrid Stacked Sparse Autoencoder (HSSAE) Model for Predicting Type 2 Diabetes
    Authors: A Abdussamad, H Daud, R Sokkalingam, M Zubair, Iliyas Karim Khan, Z Mahmood
    Year: 2025
    Source: To be published

  • Title: A Mini Review of the State-of-the-Art Development in Oil Recovery Under the Influence of Geometries in Nanoflood
    Authors: M Zafar, H Sakidin, A Hussain, M Sheremet, I Dzulkarnain, R Safdar, …
    Year: 2024
    Source: Journal of Advanced Research in Micro and Nano Engineering, Volume 26 (1), Pages 83-101

  • Title: Exploring K-Means Clustering Efficiency: Accuracy and Computational Time Across Multiple Datasets
    Authors: Iliyas Karim Khan, H Daud, N Zainuddin, R Sokkalingam, A Abdussamad, AS Azad, …
    Year: 2024
    Source: Journal of Advanced Research in Applied Sciences and Engineering Technology

  • Title: Forecasting the Southeast Asian Currencies Against the British Pound Sterling Using Probability Distributions
    Authors: Iliyas Karim Khan, Ahmad Abubakar Suleiman, Hanita Daud, Mahmod Othman, Abdullah …
    Year: 2023
    Source: Data Science Insights, Volume 1 (1), Pages 31-51

  • Title: Addressing Limitations of the K-Means Clustering Algorithm: Outliers, Non-Spherical Data, and Optimal Cluster Selection
    Authors: Iliyas Karim Khan, Abdussamad, Abdul Museeb, Inayat Agha
    Year: 2024
    Citations: 4
    Source: AIMS Mathematics, Volume 9, Pages 25070-25097

 

 

Saeed Farsad | Optimization | Excellence in Research

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Dr. Saeed Farsad | Optimization | Excellence in Research

Assistant Professor at Birjand University of Technology, Iran

Dr. Saeed Farsad is an accomplished researcher and academic with expertise in experimental fluid dynamics, renewable energy, and heat transfer. He holds a Ph.D. in Mechanical Engineering from the Iranian Research Organization for Science and Technology (IROST) and has extensive experience in wind/water tunnel testing, aerodynamics, and energy conversion systems. Currently serving as an Assistant Professor at Birjand University of Technology (BUT), he has published numerous high-impact journal articles in Q1 and Q2-ranked journals, focusing on vortex shedding, energy storage, and thermo-fluidic properties. His research contributions extend beyond academia, including patents, award papers, and a book on solar desalination. With international collaborations at Toronto Metropolitan University and York University, Dr. Farsad has strengthened his global research footprint. Recognized as an Elective Researcher of the Province, his work has significant industrial and academic applications, making him a prominent figure in mechanical and applied engineering sciences.

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Education

Dr. Saeed Farsad holds a Ph.D. in Mechanical Engineering from the Iranian Research Organization for Science and Technology (IROST), specializing in experimental fluid dynamics, wind/water tunnel tests, and advanced measurement techniques. He completed his M.Sc. in Mechanical Engineering – Energy Conversion at the University of Sistan & Baluchestan, where he focused on solar desalination, heat transfer, and numerical simulations. His B.Sc. in Automotive Technology from the Technical College of Mashhad provided a strong foundation in vehicle systems, transmission lines, and automotive engineering. His academic journey showcases a deep multidisciplinary approach, integrating energy systems, experimental fluid mechanics, and automotive applications. With supervisors from renowned institutions, his education has been instrumental in shaping his expertise in thermo-fluid sciences and renewable energy applications. His ability to blend theoretical knowledge with practical applications has led to impactful research contributions, journal publications, and patented innovations in mechanical and automotive engineering.

Professional Experience

Dr. Saeed Farsad has over a decade of professional experience, combining academic research, teaching, and industry involvement. He is currently an Assistant Professor at Birjand University of Technology (BUT), where he teaches courses in fluid mechanics, statics, technical drawing (CATIA), and automotive technology. His international exposure includes a Visiting Assistant Professorship at Toronto Metropolitan University (TMU) and a Research Assistant position at York University, where he contributed to energy storage and fluid mechanics research. Beyond academia, Dr. Farsad has worked in the automotive industry, including roles at Toyota Motor Manufacturing Canada (TMMC) and Mechatronic Diagnostic Inc., where he gained hands-on experience in diagnostics and assembly line operations. His expertise spans experimental fluid flow measurement, energy systems, and mechanical design, making him a versatile researcher and educator with a unique blend of theoretical and applied engineering knowledge.

Research Interest

Dr. Saeed Farsad’s research interests lie in experimental fluid dynamics, renewable energy, and heat transfer. His work focuses on vortex shedding, aerodynamics, and thermo-fluidic properties, with applications in wind and water tunnel experiments. He has also made significant contributions to solar desalination, adsorption-based energy storage, and magnetic nanofluid heat transfer. His interdisciplinary research integrates advanced experimental techniques such as Particle Image Velocimetry (PIV), Laser Doppler Velocimetry (LDV), and Hot-Wire Anemometry (HWA) to enhance the understanding of fluid flow and heat exchange mechanisms. In addition, Dr. Farsad explores automotive aerodynamics, energy-efficient HVAC systems, and turbulence modeling, bridging the gap between engineering applications and sustainable energy solutions. His collaborations with international researchers in Canada and Iran further strengthen his impact in the global scientific community, ensuring that his research contributes to both theoretical advancements and industrial applications.

Awards and Honors

Dr. Saeed Farsad has received several awards and recognitions for his contributions to mechanical engineering and applied sciences. He was honored as the Elective Researcher of the Province in 2011, recognizing his pioneering research in fluid mechanics and energy systems. His academic excellence is reflected in his third-place ranking in Associate Graduate Courses at Mashhad Technical College and his 16th rank among 6,000 applicants in the B.Sc. Automotive Mechanics Entrance Exam. His innovative research has led to multiple patents, including a Smart Filter equipped with an alarm system and a device for the collection and separation of machine tool waste. With publications in high-impact journals and invitations to prestigious international awards, Dr. Farsad’s achievements highlight his significant contributions to engineering innovation and scientific advancements.

Conclusion

Dr. Saeed Farsad is a highly accomplished researcher, educator, and engineer with expertise in experimental fluid dynamics, renewable energy, and heat transfer. His strong academic background, diverse professional experience, and impactful research contributions make him a leading figure in mechanical engineering. His ability to integrate theoretical research with practical applications has resulted in high-impact journal publications, patents, and industrial collaborations. His work in aerodynamics, solar desalination, and energy storage has broad implications for sustainable engineering and environmental solutions. With international research experience and teaching roles in Canada and Iran, Dr. Farsad has established himself as a global expert in his field. His dedication to scientific excellence and innovation positions him as a strong candidate for prestigious research awards, reinforcing his influence in the engineering and academic communities worldwide.

Publications Top Noted

 

Raja Rani Titti | Applied Mathematics | Best Researcher Award

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Dr. Raja Rani Titti | Applied Mathematics | Best Researcher Award

Deputy Head of FPD at Military Technological College, Oman

Dr. T Raja Rani is a distinguished researcher and academician with extensive contributions to mathematics, artificial intelligence, IoT, and biomedical engineering. With 65 research papers, a book published by Taylor & Francis (CRC Press, UK), and multiple international award presentations, she has established herself as a leader in her field. She has served as a reviewer and editorial board member for reputed journals and has supervised PhD scholars and student research projects. As the Principal Investigator for government-funded projects from the Ministry of Higher Education and Ministry of Defence, she has led innovative studies in AI-driven healthcare and smart automation. She has also held key academic roles, contributing to institutional research development. Recognized for her interdisciplinary expertise and global collaborations, Dr. Raja Rani is a strong candidate for the Best Researcher Award, with future potential in high-impact publications, industry partnerships, and international research funding.

Professional Profile

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Education

Dr. T Raja Rani holds a strong academic background in mathematics and computational sciences, equipping her with expertise in applied mathematics, artificial intelligence, and IoT-based systems. She earned her degrees from prestigious institutions, specializing in differential equations, machine learning applications, and biomedical engineering research. Her academic journey has been marked by a passion for interdisciplinary research, combining theoretical and practical knowledge to address complex real-world challenges. With a commitment to continuous learning, she has also actively participated in professional development programs, workshops, and research collaborations to enhance her expertise. Her educational foundation has played a crucial role in shaping her research contributions, enabling her to publish high-quality journal articles, lead innovative projects, and mentor students in advanced research fields. Dr. Raja Rani’s dedication to academia and research has made her a respected scholar in her domain, contributing significantly to advancements in mathematical modeling, AI, and IoT applications.

Professional Experience

Dr. T Raja Rani has an extensive academic and research career spanning over two decades in reputed institutions across India and Oman. She has served as a lecturer, associate professor, and research coordinator, contributing to curriculum development, student mentorship, and institutional research initiatives. She worked at Military Technological College, Higher College of Technology, and Ibri College of Technology in Oman, where she played a pivotal role in mathematics program coordination, research development, and quality assurance. She has also contributed as an interview panelist for academic recruitment and has mentored several undergraduate and PhD scholars in AI-driven biomedical and IoT projects. In addition, she has actively participated in international awards, journal editorial boards, and funded research projects. Her career is marked by a dedication to bridging the gap between theoretical research and practical applications, making her an invaluable contributor to academia and industry collaborations.

Research Interest

Dr. T Raja Rani’s research interests lie at the intersection of applied mathematics, artificial intelligence, IoT, and biomedical engineering. She specializes in differential equations, machine learning algorithms, and computational modeling, applying these techniques to solve real-world problems in healthcare, automation, and smart city infrastructure. Her work explores AI-driven predictive analytics for medical diagnosis, IoT-based automation systems, and mathematical simulations for engineering applications. She has led multiple interdisciplinary projects, including the development of IoT-based home automation, hydroponic farming solutions, and AI models for cardiovascular disease prediction. Her passion for cutting-edge research is reflected in her numerous publications, book authorship, and government-funded projects. By integrating AI and mathematics, she aims to develop smart, efficient, and sustainable solutions for various industries. Moving forward, she seeks to expand her research into high-impact AI applications, industry collaborations, and global research partnerships to further drive technological innovation.

Awards and Honors

Dr. T Raja Rani has received significant recognition for her research contributions, academic leadership, and interdisciplinary expertise. She has authored 65+ research papers in reputed international journals and awards, securing funded projects from the Ministry of Higher Education and Ministry of Defence in Oman. Her book publication with Taylor & Francis (CRC Press, UK) highlights her expertise in differential equations and computational analysis. As a reviewer and editorial board member for international journals, she has played a key role in shaping academic research in her field. Her award presentations, including at WCE-2014 in London, have established her as a global researcher. Her work in IoT, AI-driven healthcare solutions, and mathematical modeling has positioned her as a leading scholar. These achievements make her a deserving candidate for prestigious research awards and further opportunities in high-impact global collaborations and research funding.

Conclusion

Dr. T Raja Rani is an accomplished researcher and academician, with a career dedicated to mathematical modeling, AI, and IoT applications. With extensive research contributions, government-funded projects, and academic leadership, she has significantly advanced interdisciplinary research. Her expertise spans machine learning, biomedical applications, and automation technologies, leading to impactful innovations in healthcare, engineering, and smart infrastructure. She has also been a mentor, reviewer, and institutional research coordinator, fostering academic excellence. Moving forward, she aims to strengthen industry collaborations, high-impact journal publications, and international research funding to further elevate her contributions. With her proven track record, Dr. Raja Rani is a strong candidate for the Best Researcher Award, and her work will continue to shape advancements in AI-driven research and technological innovation.

Publications Top Noted

  • Title: ML-based Approach to Predict Carotid Arterial Blood Flow Dynamics
    Authors: TR Rani, A Al Shibli, M Siraj, W Srimal, NZS Al Bakri, TSL Radhika
    Year: 2009
    Citations: 2
    Source: Contemporary Mathematics

  • Title: Approximate Analytical Methods for Solving Ordinary Differential Equations
    Authors: TSL Radhika, TKV Iyengar, TR Rani
    Year: 2014
    Citations: 25
    Source: CRC Press

  • Title: Econophysics and Fractional Calculus: Einstein’s Evolution Equation, the Fractal Market Hypothesis, Trend Analysis, and Future Price Prediction
    Authors: J Blackledge, D Kearney, M Lamphiere, R Rani, P Walsh
    Year: 2019
    Citations: 15
    Source: Mathematics, 7 (11), 1057

  • Title: Effect of Radiation and Magnetic Field on Mixed Convection at a Vertical Plate in a Porous Medium with Variable Fluid Properties and Varying Wall Temperature
    Authors: TR Rani, CNB Rao, VL Prasannam
    Year: 2010
    Citations: 6
    Source: Proceedings of the International Multiaward of Engineers and Computer Science

  • Title: The Effects of Viscous Dissipation on Convection in a Porous Medium
    Authors: TR Rani, TSL Radhika, JM Blackledge
    Year: 2017
    Citations: 5
    Source: Mathematica Aeterna, 7 (2), 131-145

  • Title: MHD Free Convective Heat Transfer Flow Past a Vertical Plate Embedded in a Porous Medium with Effects of Variable Fluid Properties in the Presence of Heat Source
    Authors: TR Rani, R Palli
    Year: 2014
    Citations: 4
    Source: Proceedings of the World Congress on Engineering

  • Title: Measuring Software Design Class Metrics: A Tool Approach
    Authors: T Rani, M Sanyal, S Garg
    Year: 2012
    Citations: 4
    Source: International Journal of Engineering Research & Technology (IJERT)

  • Title: Free Convection in a Porous Medium with Magnetic Field
    Authors: V Lakshmi Prasannam, T Raja Rani, R CNB
    Year: 2009
    Citations: 4
    Source: International Journal of Computational Mathematical Ideas

  • Title: Quantile Loss Function Empowered Machine Learning Models for Predicting Carotid Arterial Blood Flow Characteristics
    Authors: TR Rani, W Srimal, A Al Shibli, NZS Al Bakri, M Siraj, TSL Radhika
    Year: 2023
    Citations: 3
    Source: WSEAS Transactions on Biology and Biomedicine

  • Title: On a Study of Flow Past Non-Newtonian Fluid Bubbles
    Authors: TSL Radhika, TR Rani
    Year: 2021
    Citations: 3
    Source: WSEAS Transactions on Fluid Mechanics

  • Title: Creeping Flow of a Viscous Fluid Past a Pair of Porous Separated Spheres
    Authors: TSL Radhika, T Raja Rani, D Dwivedi
    Year: 2020
    Citations: 3
    Source: BPAS Publications, 39 (1), 58-76

  • Title: Stochastic Modelling for Lévy Distributed Systems
    Authors: J Blackledge, TR Rani
    Year: 2017
    Citations: 3
    Source: Technological University Dublin

  • Title: Time-Dependent Flow of a Couple Stress Fluid in an Elastic Circular Cylinder with Application to the Human Circulatory System
    Authors: TSL Radhika, TR Rani, A Karthik
    Year: 2020
    Citations: 2
    Source: Academic Journal of Applied Mathematical Sciences, 6 (7), 126-135

  • Title: Comparison of HAM and Numerical Solutions for a Free Convection Problem with Variable Fluid Properties, Heat Source/Sink, and Radiation
    Authors: T Raja Rani, TSL Radhika, R Palli
    Year: 2016
    Citations: 2
    Source: Journal of Information and Optimization Sciences, 37 (3), 405-422

  • Title: An Application of HAM for MHD Heat Source Problem with Variable Fluid Properties
    Authors: TR Rani, TSL Radhika, R Palli
    Year: 2014
    Citations: 2
    Source: Advances in Theoretical and Applied Mechanics, 7 (2), 79-89

  • Title: Mixed Convection in a Porous Medium with Magnetic Field, Variable Viscosity, and Varying Wall Temperature
    Authors: CNB Rao, VL Prasannam, T Raja Rani
    Year: 2010
    Citations: 2
    Source: International Journal of Computational Mathematical Ideas, 2 (1), 13-21

  • Title: Shor’s Algorithm – How Does It Work on Perfect Squares
    Authors: TSL Radhika
    Year: 2024

  • Title: Enhancing Crude Oil Pipeline Design Efficiency Through Explainable AI: A COMSOL Simulation Approach
    Authors: BJ Jose, P Jain, TR Rani
    Year: 2025
    Source: Innovative and Intelligent Digital Technologies

 

Leonid Litinskii | Applied Mathematics | Best Researcher Award

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Dr. Leonid Litinskii | Applied Mathematics | Best Researcher Award

Retired at Scientific Research Institute for System Analysis (formerly), Russia

Dr. Leonid Litinskii is a retired principal research scientist with an extensive academic and professional background in mathematical methods and statistical physics. He graduated from Kharkiv State University, Ukraine, and held prominent positions at the Institute for High Pressure Physics, Russian Academy of Sciences, and the Scientific Research Institute for System Analysis. With over 50 years of research experience, Dr. Litinskii is known for his pioneering work in developing the theory of vector neuron networks and the n-vicinity method for calculating the partition function in the Ising model. He has published around 100 papers in renowned scientific journals and contributed to the study of eigenvalues in the Ising model’s connection matrix. Additionally, Dr. Litinskii has made significant contributions to the analysis of quadratic functionals in large binary variable systems. A member of the European Neural Networks Society, he has left a lasting impact on the fields of mathematics and neural networks.

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Education

Dr. Leonid Litinskii completed his education at Kharkiv State University (now V. N. Karazin Kharkiv National University) in Ukraine, where he studied mathematics from 1966 to 1971. This solid foundation in mathematics paved the way for his distinguished career as a scientific researcher. His academic journey has always been focused on applying mathematical methods to complex scientific problems, particularly in statistical physics and neural networks. His studies and early research experiences contributed significantly to his future breakthroughs in these fields.

Professional Experience

Dr. Litinskii’s professional career spans over five decades, with notable research positions at esteemed institutions. He began his career as a scientific researcher at the Institute for High Pressure Physics of the Russian Academy of Sciences from 1973 to 2001. From 2001 to 2023, he worked as a Principal Research Scientist at the Scientific Research Institute for System Analysis, also within the Russian Academy of Sciences. Throughout his career, Dr. Litinskii has contributed extensively to the fields of mathematical physics and neural networks.

Research Interest

Dr. Litinskii’s research interests are primarily centered around mathematical methods in statistical physics and their application to neural networks. He has developed the theory of vector neuron networks and formulated the n-vicinity method for calculating the partition function of the Ising model. His work on the properties of eigenvalues in the Ising model’s connection matrix has been a significant contribution to the field of computational physics. Additionally, Dr. Litinskii has focused on the study of quadratic functionals in large binary variable systems, advancing mathematical modeling techniques.

Award and Honor

Throughout his career, Dr. Litinskii has earned recognition for his groundbreaking work in neural networks and statistical physics. While the details of specific awards and honors are not provided, his long tenure as a Principal Research Scientist and his role in advancing the fields of mathematics and neural networks have earned him respect and recognition in the scientific community. He is a member of the European Neural Networks Society, further emphasizing his distinguished position in the research community.

Conclusion

Dr. Leonid Litinskii’s career is a testament to dedication, innovation, and scholarly excellence. With over 50 years of research experience, his contributions to mathematical physics, neural networks, and statistical physics have been substantial. His work in developing the theory of vector neuron networks and the n-vicinity method has had a lasting impact on these fields. Though he has not yet focused on patents or practical applications, his theoretical contributions remain foundational. Dr. Litinskii’s legacy is one of a leading thinker who has shaped the advancement of mathematical and physical sciences.

Publications Top Noted

 

 

Boris Kryzhanovsky | Applied Mathematics | Best Researcher Award

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Prof. Dr. Boris Kryzhanovsky | Applied Mathematics | Best Researcher Award

Chief researcher at Scientific Research Institute for System Analysis of the National Research Center “Kurchatov Institute”, Russia

Dr. Boris Kryzhanovsky is a distinguished researcher with over five decades of experience in the fields of quantum electrodynamics, laser physics, and mathematical methods in neural networks, statistical physics, and nanotechnology. He graduated from Yerevan State University in 1971 and has since contributed significantly to scientific advancements. His work includes pioneering research in nonstationary four-wave mixing, the development of vector neural networks with large memory, and innovative methods for calculating partition functions of spin systems. Dr. Kryzhanovsky has published over 200 articles in renowned journals and holds an h-index of 19, reflecting the impact of his research. He is also the Editor-in-Chief of Optical Memory and Neural Networks and a Corresponding Member of the Russian Academy of Sciences. His leadership and extensive collaboration with international scientific communities further underscore his prominent role in advancing research in his fields of expertise.

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Education

Dr. Boris Kryzhanovsky completed his education at Yerevan State University, Armenia, where he graduated from the Physical Department in 1971. His academic foundation laid the groundwork for a distinguished career in scientific research. Throughout his career, Dr. Kryzhanovsky has maintained a strong commitment to advancing his knowledge in complex scientific fields, particularly in quantum electrodynamics, laser physics, and mathematical methods applied to neural networks and statistical physics. His early training at one of Armenia’s most prestigious universities provided him with the critical thinking and theoretical skills that have shaped his extensive body of work in these areas.

Professional Experience

Dr. Kryzhanovsky’s professional career spans over five decades, starting as a scientific researcher at the Institute for Physical Research in Armenia (1971-1991). He later worked at the Institute for Optical-Neuron Technologies RAS (1996-2006) and currently holds a chief researcher position at the Scientific Research Institute for System Analysis RAS. His career has seen significant contributions to the fields of neural networks and statistical physics, with leadership roles including Editor-in-Chief of Optical Memory and Neural Networks. Dr. Kryzhanovsky’s work is widely recognized for its deep theoretical insights and practical applications in various scientific domains.

Research Interests

Dr. Kryzhanovsky’s research interests are diverse, encompassing neural networks, statistical physics, and nanotechnology. He has made groundbreaking contributions in developing mathematical methods for the analysis of neural networks, especially focusing on vector neural networks with large memory for recognizing noisy patterns. Additionally, his work on the theory of nonstationary processes in quantum electrodynamics and the development of methods for calculating partition functions of spin systems highlights his interdisciplinary approach. His research also explores nanotechnology, particularly in relation to statistical mechanics, contributing to advances in both theoretical and applied physics.

Awards and Honors

Dr. Kryzhanovsky has received numerous honors throughout his career, underpinned by his significant contributions to scientific research. He is a Corresponding Member of the Russian Academy of Sciences and holds leadership positions in various academic and scientific societies. His work is frequently cited, reflected in his impressive h-index of 19 on Google Scholar, and he has authored over 200 journal articles in reputable SCI and Scopus-indexed publications. His professional standing and achievements are also evident from his role as Editor-in-Chief of Optical Memory and Neural Networks, further cementing his reputation in the scientific community.

Conclusion

Dr. Boris Kryzhanovsky is a highly respected researcher whose contributions to quantum electrodynamics, laser physics, neural networks, and statistical physics have had a profound impact on both theoretical and applied sciences. His academic background, coupled with extensive professional experience, has led to groundbreaking research that continues to shape the direction of several scientific fields. With a remarkable publication record and leadership roles within the scientific community, Dr. Kryzhanovsky remains a key figure in advancing knowledge and innovation. His achievements and dedication to research make him a standout in his field, deserving recognition for his substantial contributions to science.

Publications Top Noted

 

 

 

Sabah Kausar | Applied Mathematics | Young Scientist Award

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Dr. Sabah Kausar | Applied Mathematics | Young Scientist Award

University of Gujrat, Pakistan

Dr. Sabah Kausar is a dedicated physicist and researcher specializing in nanomaterials, photocatalysis, and environmental sustainability. With an MPhil in Physics from the University of Gujrat, her research focuses on synthesizing and characterizing advanced nanocomposites for applications in water purification, antimicrobial treatments, and food preservation. She has expertise in XRD, SEM, FTIR, PL, UV-Vis spectroscopy, and EDX, demonstrating a strong technical background. Her publications on Ag-doped BiVO₄ and BiVO₄/ZnO nanocomposites highlight significant advancements in photocatalytic degradation and extended shelf life of fruits. Passionate about interdisciplinary research, Dr. Kausar’s work bridges nanotechnology, environmental science, and material physics. She aspires to expand her contributions through international collaborations, high-impact publications, and practical industrial applications. With a keen focus on sustainability and innovation, she is a promising young scientist making impactful contributions to applied physics and nanotechnology.

Professional Profile 

Education

Dr. Sabah Kausar holds an MPhil in Physics from the University of Gujrat, where she conducted pioneering research on nanomaterials and their photocatalytic and antimicrobial properties. Her thesis focused on the synthesis and characterization of BiVO₄-based nanocomposites for enhancing the shelf life of fruits and environmental remediation. Prior to her MPhil, she earned a BS (Honors) in Physics, where she developed a strong foundation in experimental, numerical, and conceptual physics. Her academic journey has been marked by excellence in material physics, spectroscopy, and nanotechnology applications. Additionally, she is currently pursuing a Bachelor of Education (BEd), reinforcing her ability to contribute to academia. With a solid educational background, she has developed expertise in advanced characterization techniques such as XRD, SEM, FTIR, PL, and UV-Vis spectroscopy, which are essential for analyzing the structural, optical, and morphological properties of nanomaterials.

Professional Experience

Dr. Sabah Kausar is an emerging scientist with expertise in photocatalytic nanomaterials, environmental physics, and material characterization. During her MPhil research, she synthesized and tested Ag-doped BiVO₄ and BiVO₄/ZnO nanocomposites to improve photocatalytic activity and antimicrobial performance. Her research has practical implications in water purification, environmental remediation, and food preservation. She has collaborated with interdisciplinary teams to analyze nanoparticle efficiency using XRD, SEM, FTIR, and UV-Vis spectroscopy. She has also contributed to scientific literature through high-impact publications focusing on nanotechnology-based solutions for sustainability. As a physicist, she excels in team collaboration, research execution, and analytical problem-solving. Beyond research, her pursuit of a BEd degree equips her with academic and teaching skills, enhancing her ability to mentor and educate future scientists. With a passion for advancing nanomaterials for environmental and biomedical applications, she is poised to make significant contributions to applied physics and sustainable technology.

Research Interest

Dr. Sabah Kausar’s research interests lie in nanotechnology, photocatalysis, environmental sustainability, and antimicrobial nanomaterials. She focuses on synthesizing and characterizing functional nanocomposites for applications in water purification, energy harvesting, and food preservation. Her expertise extends to advanced material characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence spectroscopy (PL), and UV-Vis analysis, which she employs to explore optical, structural, and chemical properties of materials. She is particularly interested in the development of eco-friendly nanomaterials to combat water pollution and food spoilage. Her work on TiO₂/BiVO₄ nanocomposites for dye and antibiotic degradation has demonstrated significant potential for environmental applications. Additionally, she is keen on interdisciplinary research collaborations to bridge the gap between material science, environmental physics, and biomedicine. With a strong foundation in experimental physics and nanotechnology, she aspires to contribute to cutting-edge advancements in sustainable science and clean energy.

Awards and Honors

Dr. Sabah Kausar has earned recognition for her innovative contributions to nanotechnology and environmental sustainability. Her MPhil research on BiVO₄-based nanomaterials has been widely acknowledged for its practical implications in photocatalysis, antimicrobial applications, and food preservation. She has presented her work at national and international awards, showcasing her expertise in material characterization and sustainable nanotechnology. Additionally, her high-impact publications in peer-reviewed journals reflect her strong research capabilities and commitment to scientific advancement. Her ability to bridge physics, chemistry, and environmental science has positioned her as a promising researcher. As she continues to develop innovative nanomaterials for real-world applications, she remains committed to academic excellence and collaborative research projects. With her growing contributions to scientific knowledge and sustainability-focused solutions, she is a strong candidate for Young Scientist Awards and similar recognitions in the fields of nanotechnology, applied physics, and environmental research.

Conclusion

Dr. Sabah Kausar is a rising physicist and nanotechnology researcher committed to solving environmental and sustainability challenges through innovative material science. With a strong academic background, hands-on research experience, and a passion for applied physics, she has contributed to the development of photocatalytic and antimicrobial nanomaterials. Her work has significant implications for clean energy, water purification, and food preservation, demonstrating the power of interdisciplinary scientific advancements. As a young scientist, she continues to explore new frontiers in nanotechnology, with a focus on sustainable applications. Her ability to integrate material characterization, experimental physics, and environmental research makes her a promising scientific leader. With continued collaborations, high-impact research, and academic contributions, she is well-positioned to make lasting contributions in physics, nanotechnology, and sustainability science.

Publications Top Noted

 

Vincent Ademola Adeyemi | Dynamical Systems | Best Researcher Award

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Dr. Vincent Ademola Adeyemi | Dynamical Systems | Best Researcher Award

Researcher Associate at CITEDI-Instituto Politécnico Nacional, Mexico

Dr. Vincent Ademola Adeyemi is a distinguished researcher specializing in digital image processing, cryptography, data encryption, secure communication systems, and FPGA-based implementations. He holds a Doctorate in Science (DSc) in Digital Systems from Instituto Politécnico Nacional (IPN), Mexico, alongside advanced degrees in computer science. His research focuses on nonlinear dynamics, chaos control, and optimization, contributing significantly to the fields of mathematical modeling and secure data transmission. With numerous publications in high-impact, peer-reviewed journals such as Scientific Reports, Sensors, Electronics, and Mathematical Problems in Engineering, he has made notable advancements in secure image encryption and chaos-based cryptographic systems. Dr. Adeyemi collaborates internationally, demonstrating a strong interdisciplinary approach. His work has practical applications in cybersecurity and digital communication. A dedicated academic, he continues to push the boundaries of innovation in applied mathematics and computer science, making him a strong contender for prestigious research awards.

Professional Profile

Google Scholar
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ORCID Profile

Education

Dr. Vincent Ademola Adeyemi has an extensive academic background in computer science and digital systems. He earned his Doctorate in Science (DSc) in Digital Systems from Instituto Politécnico Nacional (IPN), Mexico (2018–2022), where he focused on FPGA-based implementations and secure communication systems. Prior to this, he obtained a Master of Science (MSc) in Computer Science from the University of Ibadan, Nigeria (2005–2007), and a Bachelor of Science (BSc) in Computer Science from the University of Ado-Ekiti (now Ekiti State University), Nigeria (1998–2002). He also holds a National Diploma in Computer Science from the Federal Polytechnic, Ado-Ekiti, Nigeria (1995–1997). His academic journey reflects a strong foundation in computational theory, digital systems, and cryptography, shaping his expertise in cybersecurity, mathematical modeling, and nonlinear dynamics. Through these qualifications, Dr. Adeyemi has developed a profound understanding of cutting-edge technologies, enabling him to contribute significantly to applied research and innovation.

Professional Experience

Dr. Vincent Ademola Adeyemi has accumulated vast experience in academia and research, focusing on applied mathematics, cryptography, and secure digital communication. He has held research and teaching positions at reputable institutions, engaging in high-level research on FPGA-based systems, data encryption, and chaotic system modeling. His work has involved international collaborations with leading experts in mathematical modeling and digital security, particularly in Mexico and Nigeria. He has played a pivotal role in developing innovative encryption techniques and optimizing chaotic systems for secure communications. As a researcher, he has contributed to peer-reviewed international journals and awards, ensuring the real-world applicability of his findings. His professional engagements also include mentoring students, supervising research projects, and participating in interdisciplinary teams working on cybersecurity solutions. With a strong academic-industrial interface, Dr. Adeyemi continues to advance the frontiers of digital systems, positioning himself as a thought leader in applied cryptography and chaos-based communications.

Research Interest

Dr. Vincent Ademola Adeyemi’s research interests lie in digital image processing, cryptography, data encryption, secure communication systems, nonlinear dynamics, and FPGA-based system design. He specializes in chaos theory applications, particularly in the modeling, control, and synchronization of chaotic systems, which have extensive applications in secure data transmission. His work integrates mathematical modeling with computational techniques to optimize cryptographic algorithms for enhanced security and performance. A significant aspect of his research involves implementing encryption methods on FPGA platforms, ensuring high-speed and energy-efficient solutions for real-time security applications. Additionally, he explores evolutionary algorithms for optimizing chaotic systems, contributing to advances in cyber-physical security. His interdisciplinary approach bridges applied mathematics, digital engineering, and computer science, offering innovative solutions to modern cybersecurity challenges. Through his groundbreaking research, Dr. Adeyemi aims to enhance secure communications, data privacy, and information security in emerging technological landscapes.

Awards and Honors

Dr. Vincent Ademola Adeyemi has received numerous recognitions for his contributions to applied cryptography, secure digital systems, and nonlinear dynamics. His research has been published in high-impact journals such as Scientific Reports, Sensors, Electronics, Fractal and Fractional, and Mathematical Problems in Engineering, reflecting his influence in the scientific community. He has been an active participant in international awards, where his work on FPGA-based encryption and chaos theory has been widely acknowledged. Additionally, his collaborative projects with leading researchers have resulted in technological advancements in secure image transmission and optimization of chaotic systems. His contributions to applied mathematics and computer science have positioned him as a promising candidate for prestigious research awards. Through his academic excellence, Dr. Adeyemi has built a strong reputation in the field, inspiring future researchers and pushing the boundaries of digital security innovations.

Conclusion

Dr. Vincent Ademola Adeyemi is a highly accomplished researcher in digital systems, cryptography, and secure communication. His extensive education, professional experience, and pioneering research in chaos-based encryption and FPGA systems make him a leading figure in applied mathematics and cybersecurity. With a strong publication record in peer-reviewed journals and active participation in international awards, he has contributed significantly to digital security advancements. His work in nonlinear dynamics, optimization, and secure data transmission has practical applications in cybersecurity, digital communication, and mathematical modeling. Recognized for his innovative research, he continues to push technological boundaries in secure digital systems. Through his dedication to academic excellence and interdisciplinary research, Dr. Adeyemi is a valuable contributor to the global scientific community, making him a strong candidate for prestigious research awards and honors. His work not only enhances cybersecurity but also paves the way for future advancements in secure information processing and transmission.

Publications Top Noted

  • Maximizing the chaotic behavior of fractional order Chen system by evolutionary algorithms
    Authors: JC Nuñez-Perez, VA Adeyemi, Y Sandoval-Ibarra, FJ Perez-Pinal, …
    Year: 2021
    Citations: 20
    Source: Mathematics 9 (11), 1194

  • FPGA realization of spherical chaotic system with application in image transmission
    Authors: JC Nuñez-Perez, VA Adeyemi, Y Sandoval-Ibarra, FJ Pérez-Pinal, …
    Year: 2021
    Citations: 13
    Source: Mathematical Problems in Engineering 2021 (1), 5532106

  • FPGA realization of the parameter-switching method in the Chen oscillator and application in image transmission
    Authors: VA Adeyemi, JC Nuñez-Perez, Y Sandoval Ibarra, FJ Perez-Pinal, …
    Year: 2021
    Citations: 10
    Source: Symmetry 13 (6), 923

  • Optimizing the maximum Lyapunov exponent of fractional order chaotic spherical system by evolutionary algorithms
    Authors: VA Adeyemi, E Tlelo-Cuautle, FJ Perez-Pinal, JC Nuñez-Perez
    Year: 2022
    Citations: 8
    Source: Fractal and Fractional 6 (8), 448

  • FPGA realization of an image encryption system using the DCSK-CDMA technique
    Authors: MA Estudillo-Valdez, VA Adeyemi, JC Nuñez-Perez
    Year: 2024
    Citations: 4
    Source: Integration 96, 102157

  • FPGA Implementation of Parameter-Switching Scheme to Stabilize Chaos in Fractional Spherical Systems and Usage in Secure Image Transmission
    Authors: VA Adeyemi, E Tlelo-Cuautle, Y Sandoval-Ibarra, JC Nuñez-Perez
    Year: 2023
    Citations: 4
    Source: Fractal and Fractional 7 (6), 31

  • FPGA realization of four chaotic interference cases in a terrestrial trajectory model and application in image transmission
    Authors: MA Estudillo-Valdez, VA Adeyemi, E Tlelo-Cuautle, Y Sandoval-Ibarra, …
    Year: 2023
    Citations: 3
    Source: Scientific Reports 13 (1), 12969

  • Secure communication system based on synchronized 3D spherical chaotic systems
    Authors: JCN Pérez, VA Adeyemi, SEG Osuna, YS Ibarra, ET Cuautle
    Year: 2020
    Citations: 3
    Source: 2020 IEEE International Conference on Engineering Veracruz (ICEV), 1-8

  • Mathematical and numerical analysis of the dynamical behavior of Chen oscillator
    Authors: JC Nuñez-Perez, VA Adeyemi, Y Sandoval-Ibarra, RY Serrato-Andrade, …
    Year: 2020
    Citations: 3
    Source: International Journal of Dynamics and Control 8, 386-395

  • FPGA Realization of an Image Encryption System Using a 16-CPSK Modulation Technique
    Authors: JC Nuñez-Perez, MA Estudillo-Valdez, Y Sandoval-Ibarra, VA Adeyemi
    Year: 2024
    Citations: 1
    Source: Electronics 13 (22), 4337

  • Chaos control and anti-control in fractional order Rössler system by parameter switching method
    Authors: VA Adeyemi
    Year: 2020
    Citations: 1
    Source: Revista Aristas, 166-171

 

Muhammad Marwan | Applied Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Muhammad Marwan | Applied Mathematics | Best Researcher Award

Associate professor at Linyi university, China

Dr. Marwan Muhammad is a distinguished researcher in applied mathematics, specializing in bifurcation theory, chaos, fractals, mobile chaotic robots, control theory, synchronization, and secure communication. With an H-index of 11, he has published extensively in high-impact journals such as Fractals, Nonlinear Dynamics, and IEEE-IoT. Currently an Associate Professor at Linyi University, China, he has over a decade of teaching and research experience, including a postdoctoral fellowship at Zhejiang Normal University (ZJNU). His work integrates mathematical theory with practical applications in cryptography, robotics, and UAV dynamics. Dr. Muhammad has successfully supervised multiple Master’s students and collaborated on funded research projects. His global academic exposure, particularly in China and Pakistan, enhances his research perspective. While his contributions are significant, further international collaborations, industry engagement, and competitive research grants would solidify his standing as a leading expert in computational and applied mathematics.

Professional Profile

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Education

Dr. Marwan Muhammad holds a Ph.D. in Applied Mathematics from the Institute of Space Technology, Pakistan, where he specialized in nonlinear dynamics and stability analysis. His doctoral research focused on applying nonlinear tools to chaotic systems. He earned an M.S. in Mathematics from COMSATS Institute of Information Technology, Pakistan, with a thesis on Fejér-Hadamard inequalities for convex functions. His academic journey began with a B.S. in Mathematics from Islamia College University, Peshawar, where he was awarded a Gold Medal for his outstanding performance. His early education includes an HSSC and SSC from the Peshawar Board, securing top grades. Throughout his academic career, Dr. Muhammad demonstrated a strong foundation in theoretical and applied mathematics, equipping him with the expertise needed to excel in research and teaching. His education has played a pivotal role in shaping his research trajectory, particularly in bifurcation theory, chaos, fractals, and control systems.

Professional Experience

Dr. Marwan Muhammad has over a decade of experience in academia and research. He is currently an Associate Professor at Linyi University, China, where he teaches and supervises research in applied mathematics. Previously, he completed a postdoctoral fellowship at Zhejiang Normal University (ZJNU), China, focusing on advanced topics in nonlinear dynamics. His professional journey includes serving as a Lecturer at Islamabad Model Postgraduate College, Riphah International University, and the Higher Education Department of Peshawar. His teaching portfolio covers a broad range of mathematical disciplines, including computational mathematics, dynamical systems, and mathematical modeling. Additionally, he has worked on a research project funded by the Higher Education Commission (HEC) of Pakistan, leading to several high-impact publications. His international exposure, particularly in China and Pakistan, has enriched his academic perspective, allowing him to integrate diverse mathematical techniques into his research and contribute significantly to the global scientific community.

Research Interest

Dr. Marwan Muhammad’s research focuses on nonlinear dynamics, bifurcation theory, chaos, fractals, control theory, synchronization, and secure communication. His work in mobile chaotic robots and multi-scroll attractors has applications in cryptography, robotics, and artificial intelligence. He is particularly interested in the mathematical modeling of complex systems, including UAV dynamics, plasma systems, and satellite chaotic systems. His contributions extend to fractional calculus, where he has analyzed tumor-immune interactions and porous medium equations. His research also explores numerical methods for solving chaotic systems, emphasizing computational efficiency and accuracy. Dr. Muhammad’s interdisciplinary approach integrates mathematics, physics, and engineering, leading to innovative solutions for real-world problems. His recent publications in journals like Fractals and Nonlinear Dynamics demonstrate his ability to bridge theoretical insights with practical applications, positioning him as a key contributor to the fields of computational and applied mathematics.

Awards and Honors

Dr. Marwan Muhammad has been recognized for his academic excellence and research contributions. He was awarded a Gold Medal for securing the highest distinction in his undergraduate studies at Islamia College University, Peshawar. His research has been published in prestigious journals, highlighting his impact in the field of applied mathematics. His contributions to nonlinear dynamics and chaotic systems have earned him invitations to collaborate on international research projects. Additionally, his supervision of Master’s students and successful research collaborations reflect his commitment to academic mentorship. His work has received recognition from funding agencies such as the Higher Education Commission (HEC) of Pakistan, under which he successfully led research projects. While his accolades are notable, continued participation in international awards, securing competitive research grants, and expanding collaborations with leading global institutions would further elevate his reputation as a distinguished researcher in computational and applied mathematics.

Conclusion

Dr. Marwan Muhammad is an accomplished mathematician whose research in nonlinear dynamics, chaos, and fractals has significantly contributed to applied mathematics. With a strong educational foundation, international research experience, and extensive teaching background, he has established himself as a key figure in computational mathematics. His work has practical applications in cryptography, robotics, and control systems, making it relevant to both academia and industry. While his publications and collaborations are impressive, expanding his research network, securing additional funding, and engaging in interdisciplinary projects could further enhance his impact. His dedication to mentoring students and advancing mathematical knowledge underscores his potential for continued success. With sustained efforts, Dr. Muhammad is poised to become a leading authority in his field, driving innovation and discovery in mathematical sciences.

Publications Top Noted

  • Coexisting attractor in a gyrostat chaotic system via basin of attraction and synchronization of two nonidentical mechanical systems
    Authors: M. Marwan, V. Dos Santos, M.Z. Abidin, A. Xiong
    Year: 2022
    Citations: 11
    Source: Mathematics, 10(11), 1914

  • Retardational effect and Hopf bifurcations in a new attitude system of quad-rotor unmanned aerial vehicle
    Authors: M. Fiaz, M. Aqeel, M. Marwan, M. Sabir
    Year: 2021
    Citations: 11
    Source: International Journal of Bifurcation and Chaos, 31(09), 2150127

  • Control and numerical analysis for cancer chaotic system
    Authors: J. Iqbal, S. Ahmad, M. Marwan, M. Shaukat
    Year: 2020
    Citations: 11
    Source: Archive of Applied Mechanics, 90, 2597-2608

  • Image cryptography communication using FPAA-based multi-scroll chaotic system
    Authors: K. Karawanich, J. Chimnoy, F. Khateb, M. Marwan, P. Prommee
    Year: 2024
    Citations: 8
    Source: Nonlinear Dynamics, 112(6), 4951-4976

  • Hopf bifurcation analysis for liquid-filled gyrostat chaotic system and design of a novel technique to control slosh in spacecrafts
    Authors: M. Sabir, S. Ahmad, M. Marwan
    Year: 2021
    Citations: 8
    Source: Open Physics, 19(1), 539-550

  • Investigation of fractional-ordered tumor-immune interaction model via fractional-order derivative
    Authors: G. Ali, M. Marwan, U.U. Rahman, M. Hleili
    Year: 2024
    Citations: 7
    Source: Fractals, 32(06), 1-10

  • Generalized Full Order Observer Subject to Incremental Quadratic Constraint (IQC) for a Class of Fractional Order Chaotic Systems
    Authors: M. Marwan, M.Z. Abidin, H. Kalsoom, M. Han
    Year: 2022
    Citations: 7
    Source: Fractal and Fractional, 6(4), 189

  • Generation of multi-scrolls in coronavirus disease 2019 (COVID-19) chaotic system and its impact on the zero-COVID policy
    Authors: M. Marwan, M. Han, R. Khan
    Year: 2023
    Citations: 6
    Source: Scientific Reports, 13, 13954

  • Novel approaches for solving fuzzy fractional partial differential equations
    Authors: M. Osman, Y. Xia, M. Marwan, O.A. Omer
    Year: 2022
    Citations: 6
    Source: Fractal and Fractional, 6(11), 656

  • Montgomery identity and Ostrowski-type inequalities for generalized quantum calculus through convexity and their applications
    Authors: H. Kalsoom, M. Vivas-Cortez, M.Z. Abidin, M. Marwan, Z.A. Khan
    Year: 2022
    Citations: 6
    Source: Symmetry, 14(7), 1449

  • Adaptive observer design for systems with incremental quadratic constraints and nonlinear outputs—application to chaos synchronization
    Authors: L. Moysis, M. Tripathi, M.K. Gupta, M. Marwan, C. Volos
    Year: 2022
    Citations: 6
    Source: Archives of Control Sciences, 32

  • Mixed obstacle avoidance in mobile chaotic robots with directional keypads and its non-identical generalized synchronization
    Authors: M. Marwan, F. Li, S. Ahmad, N. Wang
    Year: 2025
    Citations: 5
    Source: Nonlinear Dynamics, 113(3), 2377-2390

  • Chaotic behavior of Lorenz-based chemical system under the influence of fractals
    Authors: M. Marwan, A. Xiong, M. Han, R. Khan
    Year: 2024
    Citations: 4
    Source: Match Communications in Mathematical and Computer Chemistry, 91(2), 307-336

  • Control analysis of virotherapy chaotic system
    Authors: J. Iqbal, S. Ahmad, M. Marwan, A. Rafiq
    Year: 2022
    Citations: 4
    Source: Journal of Biological Dynamics, 16(1), 585-595

  • Hidden covers (wings) in the fractals of chaotic systems using advanced Julia function
    Authors: M. Marwan, M. Han, M. Osman
    Year: 2023
    Citations: 3
    Source: Fractals, 31(09), 2350125

  • Generalized external synchronization of networks based on clustered pandemic systems—The approach of COVID-19 towards influenza
    Authors: M. Marwan, M. Han, R. Khan
    Year: 2023
    Citations: 3
    Source: PLOS ONE, 18(10), e0288796

  • Existence of Solution and Self‐Exciting Attractor in the Fractional‐Order Gyrostat Dynamical System
    Authors: M. Marwan, G. Ali, R. Khan
    Year: 2022
    Citations: 3
    Source: Complexity, 2022(1), 3505634

  • On the analytical approach of codimension-three degenerate Bogdanov-Takens (BT) bifurcation in satellite dynamical system
    Authors: M. Marwan, M.Z. Abidin
    Year: 2023
    Citations: 2
    Source: Journal of Nonlinear Modeling and Analysis

  • On the global well-posedness of rotating magnetohydrodynamics equations with fractional dissipation
    Authors: M.Z. Abidin, M. Marwan, H. Kalsoom, O.A. Omer
    Year: 2022
    Citations: 2
    Source: Fractal and Fractional, 6(6), 340

  • Semi-analytical analysis of a fractional-order pandemic dynamical model using non-local operator
    Authors: M. Marwan, G. Ali, F. Li, S.A.O. Abdallah, T. Saidani
    Year: 2025
    Source: Fractals

 

Mehakpreet Singh | Computational Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Mehakpreet Singh | Computational Mathematics | Best Researcher Award

Associate Professor at University of Limerick, Ireland

Assoc. Prof. Dr. Mehakpreet Singh is a distinguished researcher in Applied Mathematics, currently serving as an Associate Professor at the University of Limerick, Ireland. With a Ph.D. from IIT Kharagpur, his expertise spans population balance modeling, computational fluid dynamics, and kinetic models. He has authored 70 research articles, including 37 as the first author and 35 as a corresponding author, with an H-index of 25 and 1366 citations, reflecting his academic impact. A recipient of the prestigious Marie Curie Individual Fellowship, he has collaborated with leading industry partners such as Johnson & Johnson and Pfizer. His research contributions extend to high-impact journals like Physics of Fluids and Kinetic and Related Models. Beyond research, he has played a vital role in mentoring students and teaching advanced mathematics courses. His global research experience, strong publication record, and industrial collaborations position him as a leader in applied mathematics and mathematical physics.

Professional Profile 

Google Scholar
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Education

Assoc. Prof. Dr. Mehakpreet Singh holds a Ph.D. in Applied Mathematics from the Indian Institute of Technology (IIT) Kharagpur, India (2009-2015), where he focused on forward and inverse problems in population balances. His doctoral research resulted in six publications, five as the first author. His master’s degree in Applied Mathematics (2006-2008) was earned from Guru Nanak Dev University, India, following a bachelor’s degree in Mathematics, Physics, and Chemistry (2003-2006) from Khalsa College, Amritsar, India. His academic journey has been defined by rigorous mathematical training, leading to expertise in computational modeling and applied mathematics. His Ph.D. thesis was later published as a book, reflecting its significance in the field. His diverse academic background has equipped him with advanced mathematical and computational skills, allowing him to bridge the gap between mathematical theories and real-world applications, making substantial contributions to interdisciplinary research areas.

Professional Experience

Dr. Mehakpreet Singh’s professional journey showcases an impressive blend of academic research and industry collaboration. He is currently an Associate Professor at the University of Limerick, Ireland (June 2024 – present), following a tenure as an Assistant Professor (June 2022 – June 2024). Prior to this, he was a Marie Curie Individual Fellow (2019-2021) at the Bernal Institute, UL, conducting groundbreaking research in mathematical modeling. His industrial collaborations include projects with Johnson & Johnson and Pfizer, during his postdoctoral fellowship at Ghent University, Belgium (2016-2017). Additionally, he has worked in various research roles at UL and the Bernal Institute, contributing significantly to mathematical modeling in chemical and pharmaceutical sciences. His teaching experience spans undergraduate and postgraduate courses in applied and computational mathematics, strengthening students’ analytical and problem-solving skills. His diverse experience across academic and industrial settings reflects his ability to translate mathematical concepts into practical applications.

Research Interest

Dr. Mehakpreet Singh’s research interests lie at the intersection of applied mathematics, computational modeling, and mathematical physics. His work focuses on population balance modeling, computational fluid dynamics, kinetic models, and nonlinear dynamics, with applications in chemical engineering, biophysics, and optical systems. He has a strong inclination toward mathematical solutions for industrial challenges, as seen in his collaborations with global pharmaceutical companies. His expertise in numerical methods and analytical techniques has led to significant contributions to high-impact journals such as Physics of Fluids and Kinetic and Related Models. His research also extends to inverse problems, fragmentation dynamics, and mathematical modeling of complex systems, making him a key contributor to cutting-edge advancements in applied mathematics. His ability to integrate theoretical and computational approaches allows him to develop innovative solutions with wide-ranging scientific and industrial applications.

Awards and Honors

Dr. Mehakpreet Singh’s achievements are recognized through several prestigious awards and honors. He was awarded the Marie Curie Individual Fellowship (2019-2021), a highly competitive European research grant, which supported his advanced research in computational and applied mathematics. His research contributions have earned him international recognition, with over 70 published articles, 37 as the first author, and 35 as the corresponding author, accumulating 1366 citations and an H-index of 25. His Ph.D. thesis was published as a book on Amazon, further cementing his scholarly impact. He has also been actively involved in mentoring Ph.D. students and leading interdisciplinary research teams. His research in mathematical modeling has led to breakthroughs in chemical and biological systems, with strong industrial applications, further highlighting his contributions to academia and industry. His growing reputation as a researcher continues to influence the fields of applied mathematics and computational modeling.

Conclusion

Assoc. Prof. Dr. Mehakpreet Singh is an accomplished researcher whose contributions to applied mathematics, computational modeling, and mathematical physics have earned him global recognition. His strong publication record, industrial collaborations, and academic leadership position him as a leading expert in his field. With a career spanning mathematical theory, industrial applications, and innovative research, he has successfully bridged the gap between academia and real-world problem-solving. His expertise in population balance models, fluid dynamics, and kinetic equations continues to shape the landscape of mathematical and engineering sciences. As an educator, he is committed to mentoring the next generation of mathematicians and engineers, ensuring that his research has a lasting impact. With an impressive blend of theoretical knowledge, computational skills, and industrial experience, Dr. Singh is a strong candidate for prestigious research awards, recognizing his outstanding contributions to the scientific community.

Publications Top Noted

  • Title: Coupled approach and its convergence analysis for aggregation and breakage models: Study of extended temporal behaviour
    Authors: S. Yadav, A. Das, S. Singh, S. Tomar, R. Singh, M. Singh
    Year: 2024
    Citations: 6
    Source: Powder Technology 439, 119714

  • Title: Advanced numerical scheme and its convergence analysis for a class of two-point singular boundary value problems
    Authors: N. Sriwastava, A.K. Barnwal, H. Ramos, R.P. Agarwal, M. Singh
    Year: 2023
    Citations: 6
    Source: Mathematics and Computers in Simulation 216, 30-48

  • Title: Two moments preserving sectional approach for an enzymatic coagulation equation
    Authors: Z. Ansari, M. Rae, M. Singh
    Year: 2024
    Citations: 5
    Source: Physics of Fluids 36 (6), 067112 (1-15)

  • Title: An efficient technique based on Green’s function for solving two-point boundary value problems and its convergence analysis
    Authors: S. Tomar, S. Dhama, H. Ramos, M. Singh
    Year: 2023
    Citations: 4
    Source: Mathematics and Computers in Simulation 210, 408-423

  • Title: A note on the volume conserving solution to simultaneous aggregation and collisional breakage equation
    Authors: F.W.V. Kharchandy, A. Das, V. Thota, J. Saha, M. Singh
    Year: 2023
    Citations: 4
    Source: Axioms 12 (2), 181 (1-10)

  • Title: Rate of convergence of two moments consistent finite volume scheme for non-classical divergence coagulation equation
    Authors: M. Singh
    Year: 2023
    Citations: 4
    Source: Applied Numerical Mathematics 187, 120-137

  • Title: Bernstein operational matrix of differentiation and collocation approach for a class of three-point singular BVPs: error estimate and convergence analysis
    Authors: N. Sriwastava, A.K. Barnwal, A.W. Wazwaz, M. Singh
    Year: 2023
    Citations: 3
    Source: Opuscula Mathematica 43 (4), 575-601

  • Title: Development of a new iterative method and its convergence analysis for nonlinear fourth‐order boundary value problems arising in beam analysis
    Authors: S. Tomar, M. Singh, H. Ramos, A.M. Wazwaz
    Year: 2022
    Citations: 3
    Source: Mathematical Methods in the Applied Sciences, 1-9

  • Title: Reply to Comment on ‘Analytical approach for solving population balances: a homotopy perturbation method’ (2019)
    Authors: G. Kaur, R. Singh, M. Singh, J. Kumar, T. Matsoukas
    Year: 2020
    Citations: 3
    Source: Journal of Physics A: Mathematical and Theoretical 53 (38), 388002

  • Title: Efficient Mass-Preserving Finite Volume Approach for the Rennet-Induced Coagulation Equation
    Authors: M. Singh, N. Sriwastav, O. Shardt
    Year: 2024
    Citations: 2
    Source: Chaos, Solitons and Fractals 181, 114692

  • Title: Models for converting CLD to PSD for bimodal distributions of particles
    Authors: V.G. Honavar, A. Pandit, M. Singh, V. Ranade
    Year: 2023
    Citations: 2
    Source: Chemical Engineering Research and Design 200, 576-591

  • Title: An opportunity for streamlined computational fluid dynamics integration via a semi-analytical method for weighted finite volume fragmentation equations
    Authors: S. Yadav, D. Wadhwa, M. Singh, J. Kumar
    Year: 2024
    Citations: 1
    Source: Physics of Fluids 36 (12), 123322

  • Title: Optimizing numerical performance of enzymatic coagulation models: Insights into proteolysis and gelation dynamics
    Authors: Z. Ansari, M. Rae, J. Kumar, M. Singh
    Year: 2024
    Citations: 1
    Source: Physics of Fluids 36, 117171

  • Title: Explicit and approximate solutions for a classical hyperbolic fragmentation equation using a hybrid projected differential transform method
    Authors: N. Yadav, Z. Ansari, R. Singh, A. Das, S. Singh, S. Heinrich, M. Singh
    Year: 2024
    Citations: 1
    Source: Physics of Fluids 36 (9), 093343

  • Title: A new and unified semi-analytical method with a convergence acceleration parameter for linear and nonlinear fragmentation equations
    Authors: S. Keshav, M. Singh, S. Singh, G. Walker, J. Kumar
    Year: 2025
    Source: Proceedings of the Royal Society A. Mathematical, Physical and Engineering

  • Title: Extending the applicability of improved Chebyshev-Secant-type methods
    Authors: N. Yadav, S. Singh, E. Martínez, M. Singh
    Year: 2025
    Source: Zeitschrift für angewandte Mathematik und Physik

  • Title: A meshfree approach for the rennet-induced coagulation equation: Spline based multistage Bernstein collocation method and its convergence analysis
    Authors: N. Sriwastav, A. Das, O. Shardt, J. Kumar, M. Singh
    Year: 2025
    Source: Applied Mathematical Modelling 143, 116035

  • Title: Machine Learning Configurations for State of Charge Predictions of Li-ion Batteries
    Authors: M. Rae, M. Ottaviani, D. Capkova, T. Kazda, M. Singh
    Year: 2025
    Source: Monatshefte für Chemie – Chemical Monthly

  • Title: Explicit and approximate solutions for the fragmentation equation in the presence of source and efflux terms: a coupled meshfree approach and its convergence analysis
    Authors: S. Keshav, S. Singh, Y. Huang, J. Kumar, M. Singh
    Year: 2025
    Source: Kinetic and Related Models 18 (4), 520-540

 

Victor Kuetche Kamgang | Mathematical Physics | Best Researcher Award

Published on by Math Scientist

Prof. Victor Kuetche Kamgang | Mathematical Physics | Best Researcher Award

Full Professor at University of Yaounde, Cameroon

Prof. Victor KUETCHE KAMGANG is a distinguished physicist specializing in classical and quantum information processing, with a strong research focus on complex adaptive systems, soliton theory, nonlinear optics, condensed matter, quantum holography, and renewable energies. He currently serves as a Full Professor at Yaoundé 1 State University, Cameroon, and has previously held leadership roles, including Head of the Department of Physics at Dschang State University. His academic journey includes a Ph.D. in Physics from Yaoundé 1 State University, with extensive research on high-dimensional excitations in physical systems. Prof. Kuetche Kamgang has contributed significantly to applied mathematics and theoretical physics, publishing widely in esteemed journals such as Physica D, Chaos, and the European Physical Journal Plus. His interdisciplinary research has global relevance, advancing knowledge in both fundamental and applied sciences. Through his leadership and innovative contributions, he continues to shape the future of physics and engineering research.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Prof. Victor KUETCHE KAMGANG holds a Ph.D. in Physics from Yaoundé 1 State University, Cameroon, awarded in 2010. His doctoral research focused on high-dimensional excitations in physical evolution systems, under the supervision of Prof. Crepin Timoleon Kofane. Prior to that, he obtained an M.Sc. in Physics with a specialization in Mechanics in 2004, where he explored nonlinear geometric algebra in the context of smooth loop theory in physics. His undergraduate studies culminated in a B.Sc. in Physics in 2002 and a dual degree in Physics-Chemistry in 1999. Throughout his academic journey, Prof. Kuetche Kamgang has demonstrated exceptional analytical skills and a deep understanding of complex physical phenomena, paving the way for his groundbreaking research in classical and quantum information processing. His rigorous academic training has equipped him with expertise in soliton theory, nonlinear optics, and condensed matter physics, enabling him to make significant contributions to contemporary scientific challenges.

Professional Experience

Prof. Kuetche Kamgang has an extensive academic career spanning over two decades. He currently serves as a Full Professor at Yaoundé 1 State University, a position he has held since November 2024. He is affiliated with multiple institutions, including the National Advanced School of Engineering of Yaoundé and the Faculty of Science at both Yaoundé 1 and Dschang State Universities. Previously, he was Head of the Department of Physics at Dschang State University from 2021 to 2024, where he played a vital role in curriculum development and academic leadership. He also served as an Associate Professor at Yaoundé 1 State University from 2018 to 2024 and a Lecturer from 2012 to 2018. His international experience includes a tenure as a Junior Associate Research Scientist at The Abdus Salam International Centre for Theoretical Physics (ICTP) in Italy from 2012 to 2017, further strengthening his global research collaborations and scientific influence.

Research Interest

Prof. Kuetche Kamgang’s research spans a wide array of advanced topics in physics and applied mathematics. His primary focus lies in classical and quantum information processing, with special attention to complex adaptive systems in control engineering and behavioral sciences. His expertise covers soliton theory, fractals, integrability, condensed matter physics, nonlinear optics, barotropic relaxation, ferromagnetism, and quantum holography. His recent studies explore Kruskal simplifications in carbon nanotube dynamics, the impact of spin torque in ferromagnetic media, and the nonlinear behavior of short light pulses in birefringent optical fibers. He also delves into genetic and neuronal network modeling, contributing significantly to interdisciplinary research. His work, published in high-impact journals such as Physica D, Chaos, and the European Physical Journal Plus, has advanced understanding in multiple scientific domains. His commitment to exploring the mathematical foundations of physical phenomena continues to shape cutting-edge developments in theoretical and applied physics.

Awards and Honors

Prof. Kuetche Kamgang has earned recognition for his outstanding contributions to physics and applied mathematics. His expertise in soliton theory, nonlinear dynamics, and quantum information processing has positioned him as a leading researcher in his field. His international collaborations, particularly with ICTP in Italy, have further enhanced his global scientific impact. He has been an invited speaker at various prestigious awards and has played a crucial role in advancing the understanding of complex systems. His membership in high-profile academic and research institutions signifies his standing in the global scientific community. His groundbreaking contributions to condensed matter physics, nonlinear optics, and renewable energy solutions continue to earn accolades, fostering academic excellence and innovation. His commitment to mentoring young researchers and leading interdisciplinary studies cements his legacy as an influential figure in modern physics.

Conclusion

Prof. Victor KUETCHE KAMGANG stands out as a distinguished physicist whose work has significantly advanced the fields of quantum and classical information processing, nonlinear dynamics, and applied mathematics. His extensive academic background, leadership roles, and research contributions underscore his expertise and influence in global scientific discourse. Through his numerous high-impact publications and international collaborations, he continues to push the boundaries of theoretical and applied physics. His research has practical implications for emerging technologies, including quantum computing, renewable energy, and advanced materials. As a respected professor and mentor, he plays a vital role in shaping future generations of physicists and engineers. His dedication to scientific discovery and interdisciplinary collaboration ensures that his impact on the academic and research communities will remain profound and long-lasting.

Publications Top Noted

  • Title: SU(2)-Hidden Symmetry of Two-Level Media: Propagation of Higher-Order Ultimately Short-Wave Excitations with Nonzero Angular Momenta

    • Authors: R.K.K. Lemoula, Romuald K.K., V.K. Kuetche, Victor Kamgang
    • Year: 2025
    • Source: Physica D: Nonlinear Phenomena

  • Title: Effects of Spin Torque Within Ferromagnetic Infinite Medium: The Short-Wave Approximation and Painlevé Analysis

    • Authors: F.T. Nguepjouo, Francis T., V.K. Kuetche, Victor Kamgang, E. Tchomgo-Felenou, E.
    • Year: 2024
    • Citations: 1
    • Source: Chaos

  • Title: Kruskal Simplification in Carbon Nanotube System Arrays Dynamics

    • Authors: R.S. Noule, Raïssa S., V.K. Kuetche, Victor Kamgang
    • Year: 2024
    • Citations: 1
    • Source: European Physical Journal Plus

  • Title: Coexisting Attractors in Neuronal Circuit Based on Josephson Junction Under the Effects of Light and Temperature: Analysis and Microcontroller Implementation

    • Authors: B. Ramakrishnan, Balamurali, N.F.F. Foka, Noel Freddy Fotie, A. Akgul, Akif, V.K. Kuetche, Victor Kamgang, R.R. Karthikeyan, Rajagopal R.
    • Year: 2024
    • Citations: 2
    • Source: Iranian Journal of Science

  • Title: Nonlinear Dynamics of Short Light Pulse in Birefringent Optical Fiber

    • Authors: H.T. Tchokouansi, Hermann T., R.T. Tchidjo, Robert Tamwo, V.K. Kuetche, Victor Kamgang
    • Year: 2023
    • Source: Optik

  • Title: Cylindrical Gravitational Pulse Waveguide Excitations

    • Authors: J.J. Defo, Jean J., V.K. Kuetche, Victor Kamgang
    • Year: 2022
    • Source: Journal of Experimental and Theoretical Physics

  • Title: Dynamics of Damped Single Valued Magnetic Wave in Inhomogeneous Circularly Polarized Ferrites

    • Authors: H.T. Tchokouansi, Hermann T., E. Tchomgo-Felenou, E., V.K. Kuetche, Victor Kamgang, R.T. Tchidjo, Robert Tamwo
    • Year: 2022
    • Citations: 6
    • Source: Chinese Journal of Physics