Boris Kryzhanovsky | Applied Mathematics | Best Researcher Award

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.

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LinTian Luh | Applied Mathematics | Numerical Analysis Research Award

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.

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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)