Leonid Litinskii | Applied Mathematics | Best Researcher Award

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 

Scopus Profile
ORCID Profile

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

 

 

Sabah Kausar | Applied Mathematics | Young Scientist Award

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

 

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.

Professional Profile 

Scopus Profile
ORCID Profile

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)