Shijie Zhao | Applied Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Shijie Zhao | Applied Mathematics | Best Researcher Award

Associate Professor at Liaoning Technical University, China

Assoc. Prof. Dr. Shijie Zhao is a distinguished researcher and academic at the Institute of Intelligence Science and Optimization, Liaoning Technical University, China. With a Ph.D. in Optimization and Management Decisions, his expertise lies in metaheuristic optimization, multi-objective optimization, and underwater navigation and positioning. He has made significant contributions through innovative algorithm designs and novel mathematical models, particularly in high-dimensional feature selection and robust navigation techniques. Dr. Zhao has published 9 SCI-indexed journal articles and participated in over 10 nationally and provincially funded research projects. He serves as a reviewer for leading journals including those by Elsevier, Springer, and IEEE, and holds memberships in 13 professional bodies. With strong programming skills, rigorous analytical thinking, and a commitment to scientific innovation, Dr. Zhao has also earned four research awards. His work bridges theoretical mathematics and practical applications, making him a valuable contributor to the global research community in intelligent systems and optimization.

Professional Profile 

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Education

Assoc. Prof. Dr. Shijie Zhao has a robust academic foundation anchored at Liaoning Technical University, China. He earned his B.S. degree in Science of Information & Computation in 2012, followed by a successive postgraduate and doctoral program in Mathematics and Applied Mathematics from 2012 to 2014. He went on to complete his Ph.D. in Optimization and Management Decisions in 2018. His educational trajectory highlights a deep commitment to the field of mathematical optimization and intelligent systems. Dr. Zhao’s academic excellence is also reflected in his ability to integrate theoretical knowledge with practical problem-solving, laying a strong foundation for his future research. His interdisciplinary approach blends pure mathematics with applied optimization techniques, making him uniquely positioned to contribute to emerging challenges in computational intelligence, machine learning, and navigation systems. His comprehensive training has equipped him with skills in advanced mathematical modeling, algorithm design, and statistical analysis—all crucial for his research trajectory.

Professional Experience

Dr. Shijie Zhao began his professional journey as a faculty member at Liaoning Technical University, where he is now serving as an Associate Professor and Director of the Institute of Intelligence Science and Optimization. Since 2012, he has progressed through a series of academic roles, including a postdoctoral tenure beginning in 2020. He has successfully led and participated in a range of scientific research projects sponsored by institutions such as the China Postdoctoral Science Foundation and the Department of Science & Technology of Liaoning Province. In addition to his teaching responsibilities, he has been actively involved in administrative, academic, and research leadership roles. Dr. Zhao has served as a reviewer for numerous high-impact international journals and conferences and has editorial roles in reputed scientific publications. His contributions to collaborative and interdisciplinary projects underscore his ability to bridge research and real-world applications, enhancing his standing as a key contributor in intelligent systems research.

Research Interest

Assoc. Prof. Dr. Shijie Zhao’s research interests lie at the intersection of intelligent optimization, computational mathematics, and advanced data analytics. He specializes in the development and enhancement of metaheuristic and multi-objective optimization algorithms, addressing both theoretical and application-driven challenges. His work has pioneered novel strategies for high-dimensional feature selection and optimization in machine learning contexts. Another key area of his focus is underwater navigation and positioning, where he has introduced innovative models for enhancing gravity navigation accuracy. With a strong foundation in mathematics, Dr. Zhao combines theoretical rigor with practical applicability, ensuring that his research contributes both to academic knowledge and technological development. His recent work explores how optimization strategies can be integrated into real-time systems, with implications in robotics, autonomous navigation, and engineering design. By addressing complex computational problems, Dr. Zhao’s research plays a vital role in driving forward the capabilities of intelligent systems and adaptive algorithms.

Award and Honor

Dr. Shijie Zhao has earned multiple accolades in recognition of his impactful contributions to scientific research and innovation. He has received four prestigious research awards for his work in intelligent systems, mathematical optimization, and applied computational modeling. His leadership in various national and provincial research initiatives has further cemented his reputation as a top-tier researcher in his domain. In addition to these honors, he has held editorial and reviewer positions for over ten internationally recognized journals, including publications by IEEE, Springer, and Elsevier—an acknowledgment of his expertise and academic integrity. Dr. Zhao is also an active member of 13 professional bodies, reflecting his global engagement and scholarly influence. His participation in high-impact collaborative projects and his growing citation index underscore the recognition and respect he commands in the research community. These honors validate his innovative spirit and unwavering dedication to advancing knowledge in mathematics and intelligent computing.

Conclusion

In conclusion, Assoc. Prof. Dr. Shijie Zhao exemplifies excellence in mathematical research, optimization theory, and intelligent system applications. His educational background, combined with over a decade of professional experience, positions him as a thought leader in his field. Through pioneering contributions to metaheuristic algorithms, multi-objective optimization, and underwater navigation, he bridges the gap between theoretical frameworks and practical technologies. His commitment to research integrity, academic service, and innovation has earned him widespread recognition and professional accolades. As an educator, leader, and scientist, Dr. Zhao’s multifaceted contributions reflect a deep dedication to advancing scientific knowledge and solving complex global challenges. His future endeavors are poised to have even greater impacts on the fields of artificial intelligence, data-driven decision-making, and intelligent navigation. With a strong publication record, a solid foundation in mathematics, and an expanding research network, Dr. Zhao continues to be a prominent and influential figure in the global academic landscape.

Publications Top Notes

  • Title: ID2TM: A Novel Iterative Double-Cross Domain-Center Transfer-Matching Method for Underwater Gravity-Aided Navigation
    Authors: Shijie Zhao, Zhiyuan Dou, Huizhong Zhu, Wei Zheng, Yifan Shen
    Year: 2025
    Source: IEEE Internet of Things Journal

  • Title: OS-BiTP: Objective sorting-informed bidomain-information transfer prediction for dynamic multiobjective optimization
    Authors: Shijie Zhao, Tianran Zhang, Lei Zhang, Jinling Song
    Year: 2025
    Source: Swarm and Evolutionary Computation

  • Title: Mirage search optimization: Application to path planning and engineering design problems
    Authors: Jiahao He, Shijie Zhao, Jiayi Ding, Yiming Wang
    Year: 2025
    Source: Advances in Engineering Software

  • Title: Twin-population Multiple Knowledge-guided Transfer Prediction Framework for Evolutionary Dynamic Multi-Objective Optimization
    Authors: Shijie Zhao, Tianran Zhang, Miao Chen, Lei Zhang
    Year: 2025
    Source: Applied Soft Computing

  • Title: VC-TpMO: V-dominance and staged dynamic collaboration mechanism based on two-population for multi- and many-objective optimization algorithm
    Authors: Shijie Zhao, Shilin Ma, Tianran Zhang, Miao Chen
    Year: 2025
    Source: Expert Systems with Applications

  • Title: A Novel Cross-Line Adaptive Domain Matching Algorithm for Underwater Gravity Aided Navigation
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2024
    Source: IEEE Geoscience and Remote Sensing Letters

  • Title: Triangulation topology aggregation optimizer: A novel mathematics-based meta-heuristic algorithm for continuous optimization and engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Liang Cai, Ronghua Yang
    Year: 2024
    Source: Expert Systems with Applications

  • Title: Improving Matching Efficiency and Out-of-Domain Positioning Reliability of Underwater Gravity Matching Navigation Based on a Novel Domain-Center Adaptive-Transfer Matching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Transactions on Instrumentation and Measurement

  • Title: A dynamic support ratio of selected feature-based information for feature selection
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2023
    Source: Engineering Applications of Artificial Intelligence

  • Title: Sea-horse optimizer: a novel nature-inspired meta-heuristic for global optimization problems
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Mengchen Wang
    Year: 2023
    Source: Applied Intelligence

  • Title: Improving the Out-of-Domain Matching Reliability and Positioning Accuracy of Underwater Gravity Matching Navigation Based on a Novel Cyclic Boundary Semisquare-Domain Researching Method
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2023
    Source: IEEE Sensors Journal

  • Title: A feature selection method via relevant-redundant weight
    Authors: Shijie Zhao, Mengchen Wang, Shilin Ma, Qianqian Cui
    Year: 2022
    Source: Expert Systems with Applications

  • Title: Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
    Authors: Shijie Zhao, Tianran Zhang, Shilin Ma, Miao Chen
    Year: 2022
    Source: Engineering Applications of Artificial Intelligence

  • Title: Improving Matching Efficiency and Out-of-domain Reliability of Underwater Gravity Matching Navigation Based on a Novel Soft-margin Local Semicircular-domain Re-searching Model
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Huizhong Zhu, Aigong Xu
    Year: 2022
    Source: Remote Sensing

  • Title: Improving Matching Accuracy of Underwater Gravity Matching Navigation Based on Iterative Optimal Annulus Point Method with a Novel Grid Topology
    Authors: Shijie Zhao, Wei Zheng, Zhaowei Li, Aigong Xu, Huizhong Zhu
    Year: 2021
    Source: Remote Sensing

  • Title: A Novel Quantum Entanglement‐Inspired Meta‐heuristic Framework for Solving Multimodal Optimization Problems
    Authors: Shijie Zhao
    Year: 2021
    Source: Chinese Journal of Electronics

  • Title: A Novel Modified Tree‐Seed Algorithm for High‐Dimensional Optimization Problems
    Authors: Shijie Zhao
    Year: 2020
    Source: Chinese Journal of Electronics

 

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.

Professional Profile 

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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

 

Felix Sadyrbaev | Applied Mathematics | Best Researcher Award

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Prof. Felix Sadyrbaev | Applied Mathematics | Best Researcher Award

Researcher at Institute of Mathematics and Computer Science, University of Latvia (LU MII abbreviated), Latvia

Professor Felix Sadyrbaev is a distinguished mathematician specializing in dynamical systems, boundary value problems, and mathematical modeling, particularly in network theory and gene regulatory networks. He earned his Ph.D. from Belorussian State University (1982) and completed his habilitation at Latvian State University (1995). Currently, he serves as the Head of Laboratory at the Institute of Mathematics and Computer Science, University of Latvia, and as a Professor and Director of the Doctorate Program in Mathematics at Daugavpils University. With over 190 scholarly publications and active participation in multiple International Congresses of Mathematicians, he has significantly contributed to mathematical research and education. A member of the Latvian and American Mathematical Societies, he also serves on editorial boards of international mathematical journals. Recognized for his contributions, he was elected a Full Member of the Academy of Sciences of Latvia in 2021, further solidifying his impact on the global mathematical community.

Professional Profile 

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Education

Professor Felix Sadyrbaev completed his undergraduate studies at Latvian State University (Riga, former USSR) and later pursued his Ph.D. in Mathematics at Belorussian State University (Minsk) in 1982. His doctoral research focused on dynamical systems, particularly boundary value problems and qualitative theory. In 1995, he earned his habilitation from Latvian State University, further advancing his expertise in mathematical modeling and optimization theory. His academic journey reflects a strong foundation in both theoretical and applied mathematics, enabling him to contribute significantly to various research domains. His education in leading institutions of the former USSR provided him with rigorous training in mathematical analysis, which has been instrumental in shaping his research career. Over the years, his academic background has allowed him to bridge different areas of mathematics, making significant contributions to network theory, gene regulatory networks, and mathematical optimization. His expertise continues to drive innovative research in applied and theoretical mathematics.

Professional Experience

Professor Sadyrbaev has had a distinguished career in academia and research spanning over four decades. Since 1978, he has been affiliated with the Institute of Mathematics and Computer Science at the University of Latvia, where he currently serves as the Head of Laboratory. In 1999, he joined Daugavpils University as a Professor and Director of the Doctorate Program in Mathematics, contributing significantly to the academic development of future researchers. His leadership roles have involved mentoring Ph.D. students, directing mathematical research initiatives, and fostering collaborations with international institutions. As an expert in dynamical systems and mathematical modeling, he has played a key role in advancing the field both locally and globally. His participation in international awards and research projects underscores his commitment to academic excellence. His long-standing association with multiple institutions highlights his dedication to fostering innovation, research collaboration, and the advancement of mathematical sciences.

Research Interest

Professor Sadyrbaev’s research interests lie in the areas of dynamical systems, boundary value problems, and mathematical modeling, with a strong focus on network theory and gene regulatory networks. His work in qualitative theory and optimization has been instrumental in advancing mathematical methods for solving complex real-world problems. He has contributed significantly to differential equations, stability analysis, and nonlinear dynamics, providing insights into critical mathematical frameworks. His interdisciplinary approach bridges applied mathematics, computational techniques, and theoretical modeling, making his research highly relevant across various scientific domains. His contributions to mathematical modeling in biology and engineering have led to significant applications, particularly in understanding complex network systems. With over 190 publications and numerous plenary talks, his research has influenced both academia and industry. His ongoing work continues to explore innovative mathematical methods for solving contemporary challenges, reinforcing his impact on the global mathematical community.

Awards and Honors

Professor Sadyrbaev has received prestigious recognition for his outstanding contributions to mathematics. In 2021, he was elected a Full Member of the Academy of Sciences of Latvia, a testament to his significant impact on mathematical research and education. His participation in major International Congresses of Mathematicians (ICM) across different countries, including Berlin, Beijing, Bangalore, Seoul, and São Paulo, highlights his global academic influence. He has also served as a delegate to the International Mathematical Union (IMU) General Assembly, representing the Latvian Mathematical Society in key international discussions. Additionally, he is a member of the Latvian Mathematical Society and the American Mathematical Society, further cementing his standing in the international mathematical community. His editorial board memberships in several international mathematical journals reflect his role in shaping contemporary mathematical research. His numerous honors underscore his dedication to advancing mathematical sciences through research, mentorship, and academic leadership.

Conclusion

Professor Felix Sadyrbaev is a highly accomplished mathematician with extensive contributions to dynamical systems, mathematical modeling, and network theory. His distinguished career spans over four decades, with significant roles in research, academic leadership, and international collaborations. His election as a Full Member of the Academy of Sciences of Latvia, numerous publications, and participation in prestigious international congresses solidify his reputation as a leading expert in his field. His influence extends beyond research, as he plays a key role in mentoring future mathematicians and fostering interdisciplinary collaborations. As a respected figure in the mathematical community, his work continues to shape contemporary mathematical theory and applications. Through his editorial roles, award participation, and research impact, he remains a driving force in the advancement of mathematical sciences. His remarkable career serves as an inspiration for young researchers and highlights the importance of mathematics in solving real-world challenges.

Publications Top Noted

  • On differential equations with exponential nonlinearities

    • Authors: Armands Gritsans, Felix Sadyrbaev
    • Year: 2025
    • Source: Applied Numerical Mathematics

  • Remarks on Modeling of Neural Networks

    • Authors: Felix Sadyrbaev
    • Year: [No year mentioned]
    • Source: [No source information available]

  • In Search of Chaos in Genetic Systems

    • Authors: Olga Kozlovska, Felix Sadyrbaev
    • Year: 2024
    • Source: Chaos Theory and Applications

  • Comparative Analysis of Models of Genetic and Neuronal Networks

    • Authors: Diana Ogorelova, Felix Sadyrbaev
    • Year: 2024
    • Source: Mathematical Modelling and Analysis

  • Editorial: Mathematical modeling of gene networks

    • Authors: Jacques François Demongeot, Felix Sadyrbaev, Inna Samuilik
    • Year: 2024
    • Source: Frontiers in Applied Mathematics and Statistics

  • On Period Annuli and Induced Chaos

    • Authors: Svetlana Atslega, Olga Kozlovska, Felix Sadyrbaev
    • Year: 2024
    • Source: WSEAS Transactions on Systems

  • A New 3D Chaotic Attractor in Gene Regulatory Network

    • Authors: Olga Kozlovska, Felix Sadyrbaev, Inna Samuilik
    • Year: 2024
    • Source: Mathematics

  • On Solutions of the Third-Order Ordinary Differential Equations of Emden-Fowler Type

    • Authors: Felix Sadyrbaev
    • Year: 2023
    • Source: Dynamics

  • On Coexistence of Inhibition and Activation in Genetic Regulatory Networks

    • Authors: Felix Sadyrbaev, Valentin Sengileyev, Albert Silvans
    • Year: [No year mentioned]

 

Halima Bensmail | Applied Mathematics | Best Researcher Award

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Prof. Dr. Halima Bensmail | Applied Mathematics | Best Researcher Award

Principal scientist at Qatar Computing Research Institute, Qatar

Dr. Halima Bensmail is a distinguished Principal Scientist at the Qatar Computing Research Institute, specializing in machine learning, bioinformatics, biostatistics, and statistical modeling. With a Ph.D. in Statistics (Summa Cum Laude) from the University Pierre & Marie Curie, she has made significant contributions to Bayesian inference, multivariate analysis, and precision medicine. She has an impressive research record with an H-index of 31, i10-index of 54, and around 140 publications in prestigious journals such as Nature Communications, JASA, and IEEE TNNLS. As the founder of the Statistical Machine Learning and Bioinformatics group at QCRI, she has led groundbreaking projects, including the development of open-source data-driven tools like the PRISQ pre-diabetes screening model and MCLUST clustering algorithm. With extensive academic experience in the USA, France, and the Netherlands, she has mentored numerous postdocs and students, shaping the next generation of researchers. Her expertise and leadership make her a key figure in data science and precision health.

Professional Profile 

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Education

Dr. Halima Bensmail holds a Ph.D. in Statistical Machine Learning (Summa Cum Laude) from the University Pierre & Marie Curie (Paris 6), where she specialized in Bayesian inference, spectral decomposition, and mixture models. Her thesis focused on deterministic and Bayesian model-based clustering and classification for data science applications. Prior to that, she earned an M.S. in Machine Learning from the same university, with a focus on probability, financial modeling, and stochastic processes. She also holds a Bachelor’s degree in Applied Mathematics and Statistics from the University Mohammed V in Morocco, where she gained expertise in numerical analysis, stochastic processes, topology, and mathematical programming. Throughout her academic journey, she was mentored by esteemed professors and developed a strong foundation in theoretical and applied statistics. Her educational background has laid the groundwork for her pioneering research in machine learning, bioinformatics, and data-driven modeling for real-world applications.

Professional Experience

Dr. Bensmail is currently a Principal Scientist at the Qatar Computing Research Institute (QCRI), where she leads research in bioinformatics, statistical machine learning, and artificial intelligence. She also serves as a Full Professor in the College of Science and Engineering at Hamad Bin Khalifa University and a Visiting Full Professor at Texas A&M University at Qatar. Previously, she held tenured faculty positions at Virginia Medical School and the University of Tennessee, where she contributed significantly to public health and business administration research. She has also worked as a Research Scientist at the University of Leiden, a scientist at the Fred Hutchinson Cancer Research Center, and a postdoctoral researcher at the University of Washington. With decades of experience across academia and research institutions in the U.S., Europe, and the Middle East, she has built expertise in developing statistical and AI-driven solutions for biomedical and computational challenges.

Research Interests

Dr. Bensmail’s research spans statistical machine learning, bioinformatics, and precision medicine. She has developed novel clustering algorithms, such as an advanced Bayesian clustering model implemented in the MCLUST package, and statistical methods for analyzing Next-Generation Sequencing (NGS) data. She is also interested in computational biology, specifically protein-protein interactions, protein solubility, and structural biology. Her work includes dimensionality reduction techniques like nonnegative matrix factorization and discriminative sparse coding for domain adaptation. In the field of precision medicine, she has designed PRISQ, a statistical model for pre-diabetes screening. Her broader interests include Bayesian statistics, functional data analysis, information theory, and high-dimensional data modeling. With a strong focus on developing real-world data-driven tools, she actively contributes to statistical methodologies that enhance decision-making in medicine, genomics, and artificial intelligence applications.

Awards and Honors

Dr. Bensmail has received numerous accolades for her contributions to machine learning, bioinformatics, and statistical modeling. Her work has been widely recognized, with over 140 peer-reviewed publications and an H-index of 31, demonstrating the impact of her research. She has secured research grants and led major projects in AI-driven healthcare solutions. Her contributions to the field have been acknowledged through invitations to serve as a keynote speaker at international awards and as an editorial board member for high-impact journals. She has also been instrumental in mentoring young researchers, postdoctoral fellows, and doctoral students, fostering the next generation of scientists in AI, statistics, and bioinformatics. Additionally, her work on statistical methods for precision medicine and biomedical informatics has gained international recognition, positioning her as a leading expert in the field of data science for healthcare and computational biology.

Conclusion

Dr. Halima Bensmail is a pioneering researcher in machine learning, statistical modeling, and bioinformatics, with a career spanning leading institutions in the U.S., Europe, and the Middle East. Her contributions to clustering algorithms, high-dimensional data analysis, and precision medicine have made a lasting impact on the fields of AI and computational biology. As a mentor and leader, she has shaped numerous young scientists and postdocs, driving innovation in data science applications. With a robust publication record, influential research projects, and a dedication to developing real-world AI-driven solutions, she stands as a leading figure in statistical machine learning. Her expertise and contributions continue to push the boundaries of knowledge in bioinformatics, artificial intelligence, and healthcare analytics, making her a strong candidate for prestigious research awards and recognition in scientific communities worldwide.

Publications Top Noted

 

Muhammad Mudassar Hassan | Graph Theory | Best Researcher Award

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Dr. Muhammad Mudassar Hassan | Graph Theory | Best Researcher Award

Researcher at Anhui University, Hefei, China.

Muhammad Mudassar Hassan is a dedicated researcher at Anhui University, Hefei, China, specializing in applied mathematics, chemoinformatics, and structural engineering. His research primarily focuses on the comparative and computational study of Zagreb Connection Indices in chemical graphs, leading to the development of modified indices that enhance structural analysis in graph theory. As the first author of all his research articles, he has contributed to SCI-indexed journals, reflecting the quality of his work. He actively collaborates on various research projects and is a member of the American Mathematical Society. Additionally, he has a patent under process, showcasing his innovative contributions. However, his citation index remains relatively low, and he lacks editorial roles, published books, and industry collaborations. Strengthening these areas could further establish his research impact. With continued publications and broader academic engagement, he has the potential to make significant advancements in his field and become a strong candidate for the Best Researcher Award.

Professional Profile 

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Education

Muhammad Mudassar Hassan has a strong academic background in applied mathematics, which forms the foundation of his research expertise. He has pursued higher education with a focus on mathematical modeling, graph theory, and chemoinformatics, equipping him with the necessary skills to analyze complex chemical structures. His academic journey has been marked by rigorous training in computational methods, topological indices, and structural graph theory, allowing him to develop innovative approaches in these areas. Throughout his studies, he has actively engaged in research, contributing to scientific advancements in his field. His commitment to continuous learning and exploration of mathematical applications in chemistry and structural engineering has helped him establish a solid theoretical and practical foundation. By integrating computational techniques with applied mathematics, he has positioned himself as a researcher capable of addressing real-world scientific challenges. His educational background serves as a strong base for his ongoing research and future contributions.

Professional Experience

Muhammad Mudassar Hassan is a researcher at Anhui University, Hefei, China, where he focuses on applied mathematics and graph theory. His professional work revolves around the computational study of Zagreb Connection Indices and other degree-based topological indices, contributing to advancements in chemoinformatics and structural engineering. He has led multiple research projects as the first author of all his published articles, demonstrating his expertise in independent research. Although he does not currently hold editorial positions, he has collaborated with researchers on various projects, broadening his professional experience. Additionally, he is a member of the American Mathematical Society, which reflects his active engagement in the mathematical research community. While his professional experience is centered on academia, expanding into industry-based research or consultancy projects could further enhance his impact. His current work highlights his strong analytical skills and dedication to advancing mathematical applications in chemical graph theory and computational modeling.

Research Interest

Muhammad Mudassar Hassan’s research interests lie at the intersection of applied mathematics, chemoinformatics, and structural engineering. His primary focus is on the development and computational analysis of Zagreb Connection Indices in chemical graphs, which have proven to be essential in understanding structural properties. His work extends to degree-based topological indices, which help in characterizing molecular structures mathematically. His research contributes to both theoretical and practical advancements, as these indices are widely used in cheminformatics, drug discovery, and materials science. He is particularly interested in improving and modifying existing mathematical models to enhance their applicability in real-world chemical and structural problems. His studies involve extensive computational analysis, making his research relevant to data-driven scientific advancements. As a researcher, he continuously seeks to explore new mathematical methodologies that can further improve the understanding and application of graph theory in scientific domains. His work reflects his passion for interdisciplinary mathematical research.

Awards and Honors

Muhammad Mudassar Hassan’s academic and research contributions have been recognized through his membership in the American Mathematical Society, a prestigious organization in the field of mathematics. While he has made valuable contributions to applied mathematics and cheminformatics, he has yet to receive major individual awards or honors in recognition of his research. His publications in SCI-indexed journals demonstrate his credibility as a researcher, and his patent under process indicates his innovative potential. Though he has not yet held editorial positions or received industry-based accolades, his research contributions suggest promising potential for future recognition. Strengthening his academic presence through increased citations, award presentations, and involvement in professional committees could enhance his prospects for receiving distinguished awards. With continued dedication to publishing high-impact research and broadening his academic influence, he is well-positioned to earn honors that acknowledge his expertise in mathematical modeling and computational graph theory.

Conclusion

Muhammad Mudassar Hassan is a dedicated researcher with expertise in applied mathematics, particularly in the computational study of Zagreb Connection Indices and topological indices in chemical graphs. His research contributions, published in SCI-indexed journals, demonstrate his commitment to advancing graph theory applications in cheminformatics and structural engineering. While he has established himself as a promising academic researcher, expanding his influence through higher citation impact, editorial roles, industry collaborations, and additional publications could further strengthen his research profile. His patent under process highlights his potential for innovation, and his membership in the American Mathematical Society reflects his professional engagement. With continued research output and broader academic contributions, he has the potential to achieve greater recognition in his field. By focusing on increasing research impact and networking within the scientific community, he could further establish himself as a leading researcher and a strong candidate for prestigious academic awards in the future.

Publications Top Noted

  • Title: Connection-based modified Zagreb indices of Boron triangular sheet BTS (m, n)

    • Authors: MM Hassan, S Jabeen, H Ali, P Ali
    • Year: 2023
    • Citations: 5
    • Source: Molecular Physics

  • Title: Topological descriptors of molecular networks via reverse degree

    • Authors: MM Hassan
    • Year: 2024
    • Citations: 4
    • Source: Polycyclic Aromatic Compounds

  • Title: Molecular networks via reduced reverse degree approach

    • Authors: MM Hassan, XF Pan, DM Yu, MS Sardar
    • Year: 2025
    • Citations: –
    • Source: Journal of Molecular Graphics and Modelling

  • Title: Computation of connection-based Zagreb indices in chain graphs and triangular sheets

    • Authors: MM Hassan, A Waqar, H Ali, P Ali
    • Year: 2024
    • Citations: 3
    • Source: Journal of Coordination Chemistry

  • Title: Connection Number-based Multiplicative Zagreb Indices of Chemical Structures

    • Authors: MM Hassan
    • Year: 2023
    • Citations: 2
    • Source: Current Organic Chemistry

  • Title: Molecular structure of DNA via Zagreb connection descriptors

    • Authors: MM Hassan, XF Pan
    • Year: 2024
    • Citations: 1
    • Source: The European Physical Journal E

 

 

 

Livija Cveticanin | Applied Mathematics | Best Researcher Award

Posted on by sciencefather

Prof. Dr. Livija Cveticanin | Applied Mathematics | Best Researcher Award

Professor at Faculty of Technical Sciences, University of Novi Sad, Serbia

Prof. Livija Cveticanin is a distinguished academic and researcher, currently holding positions at the University of Novi Sad, Obuda University, and the Polytechnic University in Temisoara. She has made significant contributions to the fields of rotor dynamics and nonlinear vibrations, publishing over 200 journal papers, six monographs with renowned publishers, and co-authoring six textbooks. Prof. Cveticanin is known for developing the “Cveticanin Method,” a groundbreaking procedure for solving nonlinear differential equations in vibration analysis. Her research has garnered international recognition, placing her among the top 2% of most cited scientists globally according to Stanford University’s rankings. She has been an invited speaker at numerous international awards and is involved in high-profile projects such as COST CA15125 and the European SenVibe project. In addition to her research, Prof. Cveticanin is an active leader in scientific communities, serving as president of the Academy of Sciences of Vojvodina and editor-in-chief of the Analecta Technica Szegedinensia.

Professional Profile 

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Education

Prof. Livija Cveticanin’s educational journey reflects a distinguished academic path in mechanical engineering and nonlinear dynamics. She graduated with a degree in Mechanical Engineering from the University of Novi Sad, Serbia. Building on this solid foundation, she pursued advanced studies at the same institution, earning her PhD at the University of Novi Sad. Her academic ambitions further led her to the Hungarian Academy of Sciences in Budapest, where she obtained the prestigious Doctor of Science degree. Prof. Cveticanin’s academic expertise spans the fields of rotor dynamics, nonlinear vibrations, and complex mechanical systems, with significant contributions to solving strong nonlinear differential equations. She continues to shape the future of engineering education as a member of the Doctoral School of Safety and Security Sciences at Obuda University in Budapest and as a faculty member at various esteemed institutions in Europe. Her academic achievements are a testament to her commitment to excellence in both research and education.

Professional Experience

Prof. Livija Cveticanin has an illustrious academic career, holding prestigious positions at multiple renowned institutions. She is a Professor Emeritus at the University of Novi Sad in Serbia, a Professor at Obuda University in Hungary, and an Honorary Professor at the Polytechnic University in Timisoara, Romania. She earned her PhD at the University of Novi Sad and her Doctor of Science degree at the Hungarian Academy of Sciences in Budapest. Prof. Cveticanin has made significant contributions to the fields of rotor dynamics, nonlinear vibrations, and mechanical engineering, publishing over 200 journal papers, six monographs, and several chapters in international books. She developed the innovative “Cveticanin Method” for solving nonlinear differential equations of vibration. As a respected leader in her field, she has been a plenary speaker at numerous international awards, led international research projects, and served as Editor-in-Chief of Analecta Technica Szegedinensia. Her work has earned her recognition as one of the top 2% scientists globally.

Research Interest

Prof. Livija Cveticanin’s research interests primarily focus on the dynamics of rotors and machines with variable mass, as well as nonlinear vibrations in mechanical systems. Her pioneering work addresses the challenges of solving strong nonlinear differential equations of vibration, for which she developed the widely recognized Cveticanin Method. This method has become an important tool in the study of nonlinear vibrations. Prof. Cveticanin’s contributions extend to areas such as the application of analytical techniques to dynamic systems, including machinery and mechanical components subjected to complex, time-varying forces. Her expertise also covers the behavior of nonlinear dynamic systems under different operational conditions, which is crucial for designing more efficient and reliable mechanical systems. Prof. Cveticanin is involved in both theoretical research and practical applications, with significant contributions to engineering design, machine dynamics, and the development of methodologies for tackling difficult vibration problems.

Award and Honor

Prof. Livija Cveticanin has received numerous prestigious awards and honors throughout her distinguished career, recognizing her groundbreaking contributions to the field of nonlinear dynamics and mechanical engineering. Notably, she has been included in the Stanford University Ranking of the top 2% most influential scientists in the world, based on her lifetime publication and citation records. In 2001, Thomson Reuters awarded her for publishing the most cited one-author paper in Serbia, which was also ranked among the top 1% of the most cited papers in physics. Additionally, she has been honored with leadership roles, including being the president of the Academy of Sciences of Vojvodina and holding positions in several esteemed scientific organizations such as GAMM and IFToMM. Her remarkable achievements and contributions to academia have earned her international recognition, with invitations to lecture at renowned institutions, such as CISM in Udine, Italy, and the International PhD School of Nonlinear Sciences in São Paulo, Brazil.

Conclusion

Prof. Livija Cveticanin stands as an outstanding figure in the field of mechanical engineering and nonlinear dynamics, making profound contributions to rotor dynamics, vibrations, and differential equations. With over 200 journal papers and six monographs published by renowned publishers such as Springer, her work has earned global recognition. Notably, her innovative “Cveticanin Method” has become a fundamental tool in solving nonlinear vibration equations. Prof. Cveticanin’s leadership and involvement in international projects, such as COST CA15125 (DENORMS) and SenVibe, further solidify her status as a driving force in advancing the field. As the president of the Academy of Sciences of Vojvodina and Editor-in-Chief of Analecta Technica Szegedinensia, her influence extends beyond research into academia and international collaborations. Her recognition in the Stanford University ranking of the top 2% of most cited scientists globally exemplifies her lasting impact and underscores her eligibility for the Best Researcher Award.

Publications Top Noted

  • Title: Homotopy–perturbation method for pure nonlinear differential equation
    Authors: L. Cveticanin
    Year: 2006
    Citations: 330
  • Title: Dynamic modeling of a pneumatic muscle actuator with two-direction motion
    Authors: J. Sárosi, I. Biro, J. Nemeth, L. Cveticanin
    Year: 2015
    Citations: 131
  • Title: Oscillator with fraction order restoring force
    Authors: L. Cveticanin
    Year: 2009
    Citations: 110
  • Title: Strong nonlinear oscillators
    Authors: L. Cveticanin
    Year: 2018
    Citations: 108
  • Title: Dynamics of machines with variable mass
    Authors: L. Cveticanin
    Year: 2022
    Citations: 98
  • Title: Dynamic characterization and simulation of two-link soft robot arm with pneumatic muscles
    Authors: A. Hošovský, J. Piteľ, K. Židek, M. Tóthová, J. Sárosi, L. Cveticanin
    Year: 2016
    Citations: 89
  • Title: Oscillator with strong quadratic damping force
    Authors: L. Cveticanin
    Year: 2009
    Citations: 78
  • Title: Jacobi elliptic functions: a review of nonlinear oscillatory application problems
    Authors: I. Kovacic, L. Cveticanin, M. Zukovic, Z. Rakaric
    Year: 2016
    Citations: 75
  • Title: The homotopy-perturbation method applied for solving complex-valued differential equations with strong cubic nonlinearity
    Authors: L. Cveticanin
    Year: 2005
    Citations: 70
  • Title: Oscillator with a Sum of Noninteger‐Order Nonlinearities
    Authors: L. Cveticanin, T. Pogany
    Year: 2012
    Citations: 67
  • Title: Resonant vibrations of nonlinear rotors
    Authors: L. Cveticanin
    Year: 1995
    Citations: 66
  • Title: Dynamics of mechanical systems with non-ideal excitation
    Authors: L. Cveticanin, M. Zukovic, J. M. Balthazar
    Year: 2018
    Citations: 64
  • Title: Dynamics of the non-ideal mechanical systems: A review
    Authors: L. Cveticanin
    Year: 2010
    Citations: 62
  • Title: Vibrations of a coupled two-degree-of-freedom system
    Authors: L. Cveticanin
    Year: 2001
    Citations: 61
  • Title: Chaos in non-ideal mechanical system with clearance
    Authors: M. Zukovic, L. Cveticanin
    Year: 2009
    Citations: 59
  • Title: The motion of a two-mass system with non-linear connection
    Authors: L. Cveticanin
    Year: 2002
    Citations: 59
  • Title: Free vibration of a Jeffcott rotor with pure cubic non-linear elastic property of the shaft
    Authors: L. Cveticanin
    Year: 2005
    Citations: 55
  • Title: Conservation laws in systems with variable mass
    Authors: L. Cveticanin
    Year: 1993
    Citations: 55
  • Title: Sorption behavior of polycyclic aromatic hydrocarbons on biodegradable polylactic acid and various nondegradable microplastics: Model fitting and mechanism analysis
    Authors: M. Lončarski, V. Gvoić, M. Prica, L. Cveticanin, J. Agbaba, A. Tubić
    Year: 2021
    Citations: 53
  • Title: Approximate analytical solutions to a class of non-linear equations with complex functions
    Authors: L. Cveticanin
    Year: 1992
    Citations: 52