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.

Professional Profile 

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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

 

 

Shiqing Zhang | Applied Mathematics | Excellence in Applied Mathematics

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Prof. Shiqing Zhang | Applied Mathematics | Excellence in Applied Mathematics

Math Department at Sichuan University, China

Dr. Shiqing Zhang is a distinguished professor of mathematics at Sichuan University, specializing in Nonlinear Functional Analysis, Celestial Mechanics, Differential Equations, and Mathematical Physics. With a Ph.D. from Nankai University (1991), he has made significant contributions to applied mathematics, particularly in optimization algorithms, N-body problems, and mathematical modeling. His extensive publication record in high-impact journals and multiple National Science Foundation of China (NSFC) research grants highlight his sustained research excellence. His work has applications in astrophysics, computational mathematics, and engineering. Recognized early as a Distinguished Young Teacher at Chongqing University (1996), Dr. Zhang has since continued to advance the field with groundbreaking research. While his academic contributions are remarkable, expanding industry collaborations and international recognition could further enhance his impact. Overall, his expertise and achievements make him a strong candidate for the Excellence in Applied Mathematics Award, with research that bridges theoretical mathematics and real-world applications.

Professional Profile 

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Education 

Dr. Shiqing Zhang has a strong academic background in mathematics, beginning with his B.S. degree from Chongqing University in 1985, followed by a Master’s degree from the same institution in 1987. He pursued advanced studies in mathematical sciences and earned his Ph.D. from Nankai University in 1991. Throughout his academic journey, Dr. Zhang has focused on deep theoretical aspects of mathematics, particularly in applied fields such as functional analysis, celestial mechanics, and differential equations. His education at renowned Chinese universities laid the foundation for his extensive contributions to mathematical research. His academic progression reflects a deep commitment to advancing mathematical knowledge and solving complex mathematical problems. With rigorous training in both pure and applied mathematics, Dr. Zhang’s educational background provided him with the analytical skills and problem-solving abilities necessary to excel in research, making him a leading figure in applied mathematics and a strong candidate for prestigious academic recognition.

Professional Experience 

Dr. Shiqing Zhang has built a distinguished academic career spanning over three decades. He began his professional journey at Chongqing University, where he served as an Assistant Professor (1988–1993) and later as an Associate Professor (1993–1997). His exceptional contributions to mathematics led to his promotion as a Professor at Chongqing University in 1997, a position he held until 2002. He then moved to Yangzhou University (2002–2005) as a Professor before joining Sichuan University in 2005, where he has been a Professor of Mathematics ever since. His professional trajectory demonstrates a continuous commitment to academia, teaching, and research. Over the years, he has played a crucial role in mentoring students, leading research initiatives, and contributing to the advancement of applied mathematics. His vast teaching experience, combined with his research contributions, establishes him as a well-respected authority in the field of mathematical sciences.

Research Interest

Dr. Shiqing Zhang’s research interests lie in Nonlinear Functional Analysis, Celestial Mechanics, Differential Equations, and Mathematical Physics. His work focuses on developing analytical methods to solve complex problems in applied mathematics. He has made significant contributions to the study of central configurations in celestial mechanics, periodic solutions in Hamiltonian systems, and optimization problems using variational methods. His research extends to iterative algorithms, monotone inclusion problems, and function space analysis, which have applications in physics, engineering, and computational sciences. Dr. Zhang has published extensively in high-impact mathematical journals, providing innovative solutions to long-standing problems. His work on mountain pass theorem applications, action-minimizing solutions, and functional inequalities showcases his depth in applied mathematics. By bridging theory with real-world applications, his research continues to shape developments in both pure and applied mathematical disciplines, reinforcing his position as a leading researcher in the field.

Awards and Honors 

Dr. Shiqing Zhang has been recognized for his contributions to mathematics through numerous research grants and honors. He has received multiple research grants from the National Natural Science Foundation of China (NSFC), spanning several years, including major funding from 1996 to 2024. These grants have supported his research in applied mathematics, particularly in nonlinear functional analysis and celestial mechanics. In recognition of his excellence in teaching and research, he was awarded the title of Distinguished Young Teacher at Chongqing University in 1996, highlighting his impact on mathematics education. His ability to secure continuous funding reflects the high quality and significance of his research contributions. Dr. Zhang’s strong academic credentials, numerous publications, and funded projects illustrate his expertise and commitment to mathematical advancements. These accolades confirm his role as a key figure in applied mathematics, making him a distinguished candidate for awards recognizing excellence in research.

Conclusion

Dr. Shiqing Zhang’s extensive contributions to applied mathematics, nonlinear functional analysis, and celestial mechanics establish him as a leading researcher in the field. With a solid educational foundation from top Chinese universities and a distinguished academic career spanning over three decades, he has significantly impacted both research and education. His numerous research grants from NSFC, coupled with high-quality publications in renowned mathematical journals, demonstrate the depth and influence of his work. His recognition as a Distinguished Young Teacher at Chongqing University further underscores his contributions to academia. Dr. Zhang’s research in differential equations, optimization, and mathematical physics bridges theoretical advancements with practical applications, enhancing the understanding of complex mathematical models. Given his academic excellence, research achievements, and long-standing contributions, he is a highly suitable candidate for the Excellence in Applied Mathematics Award, reflecting his dedication to advancing mathematical sciences globally.

Publications Top Noted

 

LinTian Luh | Applied Mathematics | Numerical Analysis Research Award

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Dr. LinTian Luh | Applied Mathematics | Numerical Analysis Research Award

Dr. Lin-Tian Luh is a distinguished mathematician specializing in radial basis functions, approximation theory, numerical mathematics, and topology. With a Ph.D. from the University of Göttingen, he has made significant contributions to the field, particularly in developing error bounds for high-dimensional interpolation and advancing the choice theory of shape parameters. Over his academic career at Providence University, where he served as a lecturer, associate professor, and full professor, he has been instrumental in enhancing research environments and collaborating internationally, notably with Professor R. Schaback. Dr. Luh has published extensively in high-impact journals, presented at major awards worldwide, and held editorial roles in reputable mathematical journals. His groundbreaking work on shape parameter selection has gained international recognition, solving longstanding challenges in the field. Honored multiple times for research excellence, he continues to push the boundaries of numerical analysis and computational mathematics, making profound impacts on scientific advancements.

Professional Profile 

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Education

Dr. Lin-Tian Luh obtained his Ph.D. in Mathematics from the University of Göttingen, Germany, where he studied under leading experts in numerical analysis and approximation theory. His doctoral research focused on radial basis functions and their applications in high-dimensional interpolation. Prior to his Ph.D., he completed his undergraduate and master’s studies in Taiwan, building a strong foundation in pure and applied mathematics. Throughout his academic journey, he demonstrated exceptional analytical skills and a deep passion for solving complex mathematical problems. His international education provided him with a broad perspective, allowing him to integrate diverse mathematical techniques into his research. Exposure to rigorous mathematical training at Göttingen further refined his expertise in error estimation and shape parameter selection. His academic achievements laid the groundwork for a successful career in both theoretical and applied mathematics, enabling him to contribute significantly to the advancement of numerical methods in scientific computation.

Professional Experience

Dr. Lin-Tian Luh has had a distinguished academic career, spanning decades of research, teaching, and mentorship. He began as a lecturer at Providence University in Taiwan, where he quickly established himself as an authority in numerical mathematics. Rising through the ranks to associate professor and later full professor, he played a pivotal role in shaping the university’s mathematics curriculum and fostering a strong research environment. He has collaborated extensively with international scholars, including Professor R. Schaback, contributing to groundbreaking advancements in radial basis function interpolation. Dr. Luh has also held visiting research positions at prestigious institutions, further strengthening his global academic impact. His dedication to teaching has inspired numerous students to pursue research in computational mathematics. Beyond academia, he has served on editorial boards of leading mathematical journals and as a reviewer for high-impact publications, solidifying his reputation as a key figure in numerical analysis and approximation theory.

Research Interest

Dr. Lin-Tian Luh’s research interests lie in numerical analysis, radial basis function (RBF) interpolation, approximation theory, and topology. He has made substantial contributions to high-dimensional interpolation techniques, particularly in error estimation and shape parameter selection for RBF methods. His work on developing optimal strategies for shape parameter choice has addressed longstanding challenges in computational mathematics, influencing applications in engineering, data science, and machine learning. He is also deeply engaged in the theoretical aspects of approximation theory, exploring new methods to improve the efficiency and accuracy of numerical algorithms. Dr. Luh’s research extends into applied topology, where he investigates connections between geometric structures and computational models. His interdisciplinary approach has led to collaborations across various fields, reinforcing the importance of mathematical theory in real-world problem-solving. With numerous publications in top-tier journals, his work continues to shape the evolving landscape of numerical mathematics and scientific computation.

Awards and Honors

Dr. Lin-Tian Luh has received multiple accolades for his exceptional contributions to mathematics, particularly in numerical analysis and approximation theory. He has been recognized by prestigious mathematical societies and institutions for his pioneering work in radial basis function interpolation. His research on shape parameter selection has earned international acclaim, leading to invitations as a keynote speaker at major mathematical awards. Dr. Luh has also been honored with excellence in research awards from Providence University, where his work has significantly advanced the institution’s academic reputation. In addition, he has received grants and fellowships supporting his innovative research, further validating his impact in the field. His editorial contributions to leading mathematical journals have also been acknowledged, highlighting his influence in shaping contemporary numerical mathematics. These honors reflect his dedication, originality, and profound impact on both theoretical and applied mathematics, reinforcing his legacy as a leader in computational and approximation theory.

Conclusion

Dr. Lin-Tian Luh is a renowned mathematician whose work in numerical analysis, radial basis function interpolation, and approximation theory has significantly influenced the field. With a strong educational background from the University of Göttingen and an illustrious academic career at Providence University, he has played a crucial role in advancing research and mentoring future generations of mathematicians. His collaborations with international scholars and contributions to high-dimensional interpolation techniques have provided groundbreaking insights into shape parameter selection and error estimation. Recognized globally for his research excellence, he has received multiple awards and honors, further establishing his prominence in mathematical sciences. Dr. Luh’s work continues to inspire and drive progress in numerical computation, bridging theoretical advancements with practical applications. His dedication to expanding mathematical knowledge and fostering innovation ensures that his contributions will have a lasting impact on the field, shaping the future of approximation theory and scientific computing.

Publications Top Noted

  • The Shape Parameter in the Shifted Surface Spline—A Sharp and Friendly Approach

    • Author: Lin-Tian Luh
    • Year: 2024
    • Source: Mathematics (MDPI)

  • Solving Poisson Equations by the MN-Curve Approach

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Mathematics (MDPI)

  • A Direct Prediction of the Shape Parameter in the Collocation Method of Solving Poisson Equation

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Mathematics (MDPI)

  • The Shape Parameter in the Shifted Surface Spline—An Easily Accessible Approach

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Mathematics (MDPI)

  • A Direct Prediction of the Shape Parameter—A Purely Scattered Data Approach

    • Author: Lin-Tian Luh
    • Year: 2020
    • Source: Engineering Analysis with Boundary Elements (EABE)

  • The Choice of the Shape Parameter–A Friendly Approach

    • Author: Lin-Tian Luh
    • Year: 2019
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • The Mystery of the Shape Parameter III

    • Author: Lin-Tian Luh
    • Year: 2016
    • Source: Applied and Computational Harmonic Analysis (Elsevier)

  • The Mystery of the Shape Parameter IV

    • Author: Lin-Tian Luh
    • Year: 2014
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • The Shape Parameter in the Gaussian Function II

    • Author: Lin-Tian Luh
    • Year: 2013
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • The Shape Parameter in the Gaussian Function

    • Author: Lin-Tian Luh
    • Year: 2012
    • Source: Computers and Mathematics with Applications (Elsevier)

  • The Shape Parameter in the Shifted Surface Spline III

    • Author: Lin-Tian Luh
    • Year: 2012
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • Evenly Spaced Data Points and Radial Basis Functions

    • Author: Lin-Tian Luh
    • Year: 2011
    • Source: WIT Transactions on Modelling and Simulation

  • The Crucial Constants in the Exponential-Type Error Estimates for Gaussian Interpolation

    • Author: Lin-Tian Luh
    • Year: 2008
    • Source: Analysis in Theory and Applications

  • A Direct Prediction of the Shape Parameter in the Collocation Method of Solving Poisson Equation (Preprint)

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Multidisciplinary Digital Publishing Institute (MDPI Preprints)

 

Aviv Gibali | Applied Mathematics | Best Researcher Award

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Prof. Aviv Gibali | Applied Mathematics | Best Researcher Award

Researcher at Holon Institute of Technology, Israel

Dr. Aviv Gibali is a distinguished mathematician and researcher specializing in applied mathematics, optimization, and variational inequalities. He holds a Ph.D. from the Technion – Israel Institute of Technology and has completed postdoctoral studies at the Fraunhofer Institute for Industrial Mathematics in Germany. Currently serving as the Head of the Department of Applied Mathematics at HIT – Holon Institute of Technology, he has previously held leadership roles at ORT Braude College of Engineering. Dr. Gibali has made significant contributions through numerous scholarly publications, award presentations, and editorial positions in prestigious journals. His expertise spans optimization algorithms, superiorization techniques, and mathematical modeling with applications in science and engineering. Actively engaged in international collaborations and academic committees, he has also received multiple awards for his impactful research. His dedication to advancing mathematical methodologies and their real-world applications establishes him as a leading figure in the field.

Professional Profile 

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Education

Dr. Aviv Gibali holds a strong academic background in mathematics, with degrees from prestigious institutions. He earned his Ph.D. in Mathematics from the Technion – Israel Institute of Technology in 2012, where his doctoral research focused on algorithms for solving variational inequalities and their applications under the supervision of Prof. Simeon Reich and Prof. Yair Censor. Prior to that, he completed his M.Sc. in Mathematics at the University of Haifa in 2008, working on iterative algorithms for solving variational inequality problems under the guidance of Prof. Yair Censor. His academic journey began with a B.Sc. in Mathematics from the University of Haifa in 2005. Following his Ph.D., Dr. Gibali pursued postdoctoral research in optimization at the Fraunhofer Institute for Industrial Mathematics (ITWM) in Kaiserslautern, Germany, from 2012 to 2014. His educational foundation has equipped him with deep expertise in mathematical modeling, optimization, and computational algorithms.

Professional Experience

Dr. Aviv Gibali is an accomplished mathematician and researcher specializing in optimization, variational inequalities, and applied mathematics. He currently serves as the Head of the Department of Applied Mathematics at HIT – Holon Institute of Technology and holds the rank of Associate Professor. Previously, he was an Associate Professor and Head of the Mathematics Department at ORT Braude College of Engineering. Dr. Gibali completed his Ph.D. at The Technion – Israel Institute of Technology and pursued postdoctoral research at the Fraunhofer Institute for Industrial Mathematics in Germany. His extensive academic contributions include serving as an associate editor for multiple prestigious journals, organizing international awards, and collaborating with leading institutions worldwide. With numerous invited talks, scientific visits, and interdisciplinary research projects, he has significantly advanced the field of mathematical optimization. His expertise spans theoretical advancements and industrial applications, earning him multiple awards and recognition in applied and computational mathematics.

Research Interest

Dr. Aviv Gibali’s research interests lie at the intersection of applied mathematics, optimization, and computational methods, with a strong focus on projection algorithms, variational inequalities, and convex feasibility problems. His work spans both theoretical advancements and real-world applications, particularly in industrial mathematics, medical imaging, radiation therapy planning, and data science. He has made significant contributions to superiorization techniques, an innovative approach to improving iterative algorithms for constrained optimization problems. Dr. Gibali is also actively engaged in developing and analyzing numerical algorithms for large-scale optimization, leveraging mathematical modeling to solve complex problems in engineering, machine learning, and healthcare. His interdisciplinary collaborations with international research institutions and industry partners enhance the practical impact of his studies. With a keen interest in mathematical education, he also contributes to innovative pedagogical methods, fostering a new generation of researchers in applied and computational mathematics.

Award and Honor

Dr. Aviv Gibali, a distinguished mathematician and researcher, has been widely recognized for his outstanding contributions to applied mathematics and optimization. He has received numerous accolades, including the prestigious Fourth Most Cited Article Award from Optimization Methods and Software in 2021, highlighting the impact of his research. In 2020, he secured First Prize in the Hackathon on Free Writing Home Exams, organized by Tel-Aviv University and Shenkar, demonstrating his innovative approach to education. His scholarly excellence has also been acknowledged through esteemed fellowships such as the Mathematics for Industry Network’s Short-Term Scientific Mission (2018) in Germany and the Austria-Israel Academic Network Innsbruck (AIANI) Fellowship (2017). With an extensive academic career, editorial roles in leading journals, and significant contributions to industrial mathematics, Dr. Gibali’s work continues to shape the field, earning him widespread recognition and respect within the global mathematical community.

Conclusion

Dr. Aviv Gibali is a distinguished researcher in applied mathematics, with a prolific academic career spanning optimization, variational inequalities, and superiorization techniques. His extensive contributions include over a decade of impactful research, international collaborations, editorial roles in leading mathematical journals, and leadership positions in academia. As an associate professor and head of the Department of Applied Mathematics at HIT – Holon Institute of Technology, Dr. Gibali has played a pivotal role in advancing mathematical research and fostering industry-academic partnerships. His numerous scientific visits, award organizations, and editorial engagements reflect his dedication to global knowledge dissemination. Recognized with prestigious awards and citations, he has demonstrated excellence in both theoretical advancements and real-world applications. While his achievements are remarkable, continued exploration of interdisciplinary applications and mentorship initiatives could further enhance his academic influence. Dr. Gibali’s scholarly impact and leadership make him a highly deserving candidate for the Best Researcher Award.

Publications Top Noted

  • Multidimensional Evolution Effects on Non-Cooperative Strategic Games
    Authors: Shipra Singh, Aviv Gibali, Simeon Reich
    Year: 2024
    Source: Mathematics
  • Resolvent-Free Method for Solving Monotone Inclusions
    Authors: Yan Tang, Aviv Gibali
    Year: 2023
    Source: Axioms
  • Special Issue “Symmetry in Optimization and Control with Real-World Applications”
    Authors: Kok Lay Teo, Aviv Gibali, Yong Wu
    Year: 2022
    Source: Symmetry
  • New Self-Adaptive Inertial-Like Proximal Point Methods for the Split Common Null Point Problem
    Authors: Yan Tang, Yeyu Zhang, Aviv Gibali
    Year: 2021
    Source: Symmetry
  • Multi-Time Generalized Nash Equilibria with Dynamic Flow Applications
    Authors: Shipra Singh, Aviv Gibali, Simeon Reich
    Year: 2021
    Source: Mathematics
  • An Analytic and Numerical Investigation of a Differential Game
    Authors: Aviv Gibali, Oleg Kelis
    Year: 2021
    Source: Axioms
  • Projected-Reflected Subgradient-Extragradient Method and Its Real-World Applications
    Authors: Aviv Gibali, O.S. Iyiola, Lanre Akinyemi, Yekini
    Year: 2021
    Source: Symmetry
  • A Symmetric FBF Method for Solving Monotone Inclusions
    Authors: Aviv Gibali, Yekini
    Year: 2020
    Source: Symmetry
  • Inertial Krasnoselskii–Mann Method in Banach Spaces
    Authors: Yekini Shehu, Aviv Gibali
    Year: 2020
    Source: Mathematics