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)

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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

Prof. Serena Doria | Probability and nonlinear integrals | Best Researcher Award

Prof. Serena Doria | Probability and nonlinear integrals | Best Researcher Award

University g. d'Annunzio Chieti-Pescara | Italy

Author Profile 

ORCID 

Summary 


Serena doria, an associate professor at the university g. d’annunzio chieti-pescara, italy, has established herself as a specialist in imprecise probability theory, approximate reasoning, and uncertainty modeling. her academic background and editorial contributions reflect a deep commitment to advancing knowledge in theoretical and applied domains. with over 90 research publications and participation in key international symposia, her work has found meaningful applications in power electronics, where decision-making under uncertainty is crucial. her editorial roles and research leadership highlight her growing influence in the field of computational intelligence and probabilistic reasoning.

Early academic pursuits 

Serena doria began her academic journey with a deep interest in mathematical reasoning and uncertainty theory, which later evolved into her significant contributions to power electronics and applied probabilistic methods. her foundational education set the stage for a career dedicated to blending rigorous theory with practical innovation, especially in fields involving data imprecision and approximation logic.

Professional endeavors 


Currently serving as an associate professor at the university g. d’annunzio chieti-pescara in italy, serena doria has established herself as a notable academic in both teaching and research. her professional journey includes editorial roles in esteemed international journals such as the international journal of approximate reasoning and the proceedings. she has also served as an editor Probability and nonlinear integrals alongside renowned scholars like thomas augustin, massimo marinacci, and enrique miranda, showcasing her collaborative expertise.

Contributions and research focus 


Serena’s research primarily revolves around imprecise probabilities, approximate reasoning, and uncertainty quantification—areas that greatly complement modern advancements in Probability and nonlinear integrals especially where decision-making under ambiguity is crucial. her work has led to the completion of three major research projects and the publication of a significant . she has published 37 scopus-indexed and 57 researchgate-listed journal articles, reinforcing her impact in both theoretical and applied domains.

Impact and influence 


With a growing academic presence, her scopus citation index stands at 224 with an h-index of 9, and on researchgate, she holds an impressive 298 citations with an h-index of 10. these metrics reflect her influence in bridging theoretical frameworks with practical applications in power electronics and decision sciences. her role in shaping the discourse around imprecise probability theory continues to be recognized globally.

Academic cites and recognition 


Her editorial contributions to high-impact publications, especially in collaboration with international symposiums such as isipta’15, underline her stature in the research community. she has played a critical role in nurturing academic discourse and elevating the visibility of approximation-based reasoning in global forums. her expertise is often sought for editorial and peer-review positions, further highlighting her scholarly authority.

Legacy and future contributions 


Serena doria’s legacy lies in her unwavering commitment to intellectual precision in uncertain domains, particularly where computation and decision-making intersect. as future technologies increasingly rely on data under uncertainty, her research will serve as a guiding framework—especially in fields like power electronics where predictive modeling and control systems demand robust reasoning models. with continued involvement in high-level academic platforms and research projects, she is poised to contribute meaningfully to the next generation of intelligent, uncertainty-aware systems.

Publications 

Title: Coherent Upper Conditional Previsions Defined through Conditional Aggregation Operators
Author(s): Serena Doria
Journal: Mathematics

Title: Sub-Additive Aggregation Functions and Their Applications in Construction of Coherent Upper Previsions
Author(s): Serena Doria, Radko Mesiar, Adam Šeliga
Journal: Mathematics

Title: Integral Representation of Coherent Lower Previsions by Super-Additive Integrals
Author(s): Serena Doria, Radko Mesiar, Adam Šeliga
Journal: Axioms

Conclusion 


Serena doria’s academic and research journey reflects a powerful blend of innovation, collaboration, and scholarly depth. her contributions have not only advanced the theoretical understanding of uncertainty but have also impacted emerging technologies such as power electronics, where intelligent systems require robust, adaptable frameworks. with a solid citation record and continued involvement in high-impact research, her legacy is poised to grow further. as computational methods evolve, her expertise in handling imprecise information will remain pivotal, especially in optimizing real-world systems like power electronics for the future.