Bin Shi | Applied Mathematics | Research Excellence Award

Prof. Bin Shi | Applied Mathematics | Research Excellence Award

Fudan University | China 

Bin Shi is an associate professor with tenure whose research spans mathematics, machine learning, and the physical sciences, with a strong emphasis on theoretical foundations and interdisciplinary applications. His work focuses on optimization methods for machine learning, where he develops mathematically rigorous algorithms to improve efficiency, stability, and generalization in large-scale and complex learning systems. He has made significant contributions to numerical analysis and scientific computing, particularly in designing and analyzing computational methods for high-dimensional and nonlinear problems arising in science and engineering. A central theme of his research is data assimilation, integrating observational data with mathematical models to enhance prediction and uncertainty quantification in complex dynamical systems. He also explores quantum algorithms, investigating how quantum computing paradigms can accelerate optimization and learning tasks. His background in nonlinear and stochastic sciences underpins his studies of systems influenced by randomness, multiscale interactions, and long-term dynamics. In addition, his research extends to fluid dynamics, including turbulence, geophysical flows, and astrophysical phenomena, where advanced mathematical and computational techniques are used to understand highly nonlinear and chaotic behaviors. Overall, his work bridges rigorous theory with computational practice, contributing to the development of reliable algorithms and models for modern data-driven and physics-informed scientific challenges.

Citation Metrics (Google Scholar)

2000
1500
1000
500
0

Citations
825

Documents
10

h-index
11

Citations

Documents

h-index

View Google scholar Profile

Featured Publications

Understanding the Acceleration Phenomenon via High-Resolution Differential Equations

B. Shi, S.S. Du, W. Su, M.I. Jordan — Mathematical Programming, 195, 79–148 (2022) · 379 citations
Acceleration via Symplectic Discretization of High-Resolution Differential Equations

B. Shi, S.S. Du, W. Su, M.I. Jordan — Advances in Neural Information Processing Systems (NeurIPS), 32 (2019) · 166 citations
On Learning Rates and Schrödinger Operators

B. Shi, W.J. Su, M.I. Jordan — Journal of Machine Learning Research, 24(379), 1–53 (2023) · 85 citations
Mathematical Theories of Machine Learning: Theory and Applications

B. Shi, S.S. Iyengar — Springer International Publishing (2020) · 44 citations
Gradient Norm Minimization of Nesterov Acceleration: o(1/k³)

S. Chen, B. Shi, Y. Yuan — arXiv preprint, arXiv:2209.08862

Assoc. Prof. Dr. Mohamed Ali El Sayed Fahim  – applied mathematics – Best Researcher Award 

Assoc. Prof. Dr. Mohamed Ali El Sayed Fahim  - applied mathematics - Best Researcher Award 

Basic sciences department -faculty of engineering - Egypt

Author Profile 

SCOPUS 

ORCID 

🎓 Early academic pursuits

Mohamed Ali El Sayed Fahim  his academic journey began with a passion for engineering and mathematics, culminating in a bachelor's degree in electrical engineering with a specialization in measurements and controls from benha university in 2008. earning a "very good with honors" distinction, he demonstrated early on a strong foundation in technical sciences, particularly in power electronics and engineering mathematics. his growing interest in advanced mathematical modeling led him to pursue postgraduate studies in mathematical programming and operations research.

👨‍🏫 Professional endeavors

Fahim's professional academic career began in 2009 as a demonstrator of engineering mathematics at the faculty of engineering, benha university. over the next several years, he steadily rose through academic ranks, from assistant teacher in 2014 to lecturer in 2018, and ultimately to associate professor in 2023. he served at both benha university and bader university in cairo (buc), where he has been a cornerstone in the department of basic engineering sciences.

📚 Contributions and research focus

Associate professor fahim’s primary research interests lie in mathematical programming, operations research, and multi-objective optimization. his academic work bridges theory with applied mathematics engineering applications, offering solutions to complex, uncertain systems.

🌍 Impact and influence

Fahim’s research has significantly influenced both academic and industrial spheres. his work on multi-level programming and uncertain optimization models has been applied in engineering applied mathematics contexts, especially where systems like power electronics require precise and adaptive control methods.

📈 Academic citations and recognitions

Mohamed Fahim is a registered researcher on international platforms such as orcid and scopus. he is recognized for his scholarly productivity, particularly in the fields of operations research applied mathematics and mathematical modeling. his citation metrics on scopus reflect the growing relevance of his research in global academic circles.

🧭 Legacy and future contributions

Looking ahead, fahim envisions continuing his work at the intersection of mathematics and engineering. his goal is to advance optimization algorithms that can support next-generation technologies, particularly within power electronics systems and intelligent control networks.

Notable Publications 

  • Title: Two TOPSIS-Based Approaches for Multi-Choice Rough Bi-Level Multi-Objective Nonlinear Programming Problems
    Authors: Mohamed A. El Sayed, Farahat A. Farahat, Mohamed A. Elsisy, Maazen Alsabaan, Mohamed I. Ibrahem, Haitham Elwahsh
    Journal: Mathematics

  • Title: Performance Analysis of Fully Intuitionistic Fuzzy Multi-Objective Multi-Item Solid Fractional Transportation Model
    Authors: Sultan Almotairi, Elsayed Badr, M. A. Elsisy, F. A. Farahat, M. A. El Sayed
    Journal: Fractal and Fractional

  • Title: Multi-choice fractional stochastic multi-objective transportation problem
    Authors: M. A. El Sayed, Ibrahim A. Baky
    Journal: Soft Computing

  • Title: The Karush–Kuhn–Tucker (KKT) optimality conditions for fuzzy-valued fractional optimization problems
    Authors: Deepika Agarwal, Pitam Singh, M. A. El Sayed
    Journal: Mathematics and Computers in Simulation

  • Title: Stability of Parametric Intuitionistic Fuzzy Multi-Objective Fractional Transportation Problem
    Author: M. A. El Sayed
    Journal: Fractal and Fractional