World's Best Scientists 2026 revealed!
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Engineering and Technology
USA
2026
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Mathematics
USA
2026

D-Index & Metrics

Mathematics

D-Index
91
Citations
32201
World Ranking
70
National Ranking
43

Engineering and Technology

D-Index
98
Citations
36568
World Ranking
161
National Ranking
58

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in United States Leader Award
  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Engineering and Technology in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 2020 - ACM Gordon Bell Prize For "Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning"
  • 2013 - Fellow of the American Mathematical Society
  • 2009 - SIAM Fellow For analysis of multiscale and stochastic problems.

Overview

Weinan E is affiliated with Princeton University in the United States. Their primary research contributions fall within Computer Science, particularly focusing on subfields such as Materials Chemistry, Artificial Intelligence, Statistical and Nonlinear Physics, Molecular Biology, and Computational Mechanics.

The scientist's work addresses key topics including Machine Learning in Materials Science, Model Reduction and Neural Networks, Neural Networks and Applications, Protein Structure and Dynamics, X-ray Diffraction in Crystallography, Stochastic Gradient Optimization Techniques, and Computational Drug Discovery Methods.

Frequent collaborators of Weinan E include Linfeng Zhang, Han Wang, Guolin Ke, Roberto Car, and Jiequn Han.

They have published extensively, with a significant number of papers in venues such as arXiv, Computer Physics Communications, SSRN Electronic Journal, Zenodo, and Physical Review B.

Notable recent papers include:

  • DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models, 2020, Computer Physics Communications
  • DeePMD-kit v2: A software package for deep potential models, 2023, The Journal of Chemical Physics
  • Phase Diagram of a Deep Potential Water Model, 2021, Physical Review Letters
  • 86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy, 2020, Computer Physics Communications
  • A deep potential model with long-range electrostatic interactions, 2022, The Journal of Chemical Physics

Weinan E has contributed to academic literature in book form as well, with a publication titled Introduction to Data Science released in 2022 by WSPC/HEP eBooks.

Their work has been recognized through several awards, including the ACM Gordon Bell Prize in 2020 for pushing the limits of molecular dynamics simulations with ab initio accuracy. They were also named a Fellow of the American Mathematical Society in 2013 and a SIAM Fellow in 2009 for contributions to the analysis of multiscale and stochastic problems.

Best Publications

  • Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

    Linfeng Zhang;Jiequn Han;Han Wang;Roberto Car

  • DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics

    Han Wang;Linfeng Zhang;Jiequn Han;Weinan E

  • Solving high-dimensional partial differential equations using deep learning

    Jiequn Han;Arnulf Jentzen;Weinan E

  • The Deep Ritz Method: A Deep Learning-Based Numerical Algorithm for Solving Variational Problems

    Weinan E;Weinan E;Bing Yu

  • String method for the study of rare events

    Weinan E;Weiqing Ren;Eric Vanden-Eijnden

  • Deep Learning-Based Numerical Methods for High-Dimensional Parabolic Partial Differential Equations and Backward Stochastic Differential Equations

    Weinan E;Weinan E;Jiequn Han;Arnulf Jentzen

  • The Heterognous Multiscale Methods

    Weinan E;Bjorn Engquist

  • DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

    Yuzhi Zhang;Haidi Wang;Weijie Chen;Jinzhe Zeng

  • Heterogeneous multiscale methods: A review

    Weinan E;Bjorn Engquist;Xiantao Li;Weiqing Ren

  • Simplified and improved string method for computing the minimum energy paths in barrier-crossing events.

    Weinan E;Weiqing Ren;Eric Vanden-Eijnden

  • Onsager's conjecture on the energy conservation for solutions of Euler's equation

    Peter Constantin;Weinan E;Edriss S. Titi

  • A Proposal on Machine Learning via Dynamical Systems

    Weinan E;Weinan E

  • Generalized variational principles, global weak solutions and behavior with random initial data for systems of conservation laws arising in adhesion particle dynamics

    Weinan E;Yu G. Rykov;Yakov G. Sinai

  • Transition-Path Theory and Path-Finding Algorithms for the Study of Rare Events

    Weinan E;Eric Vanden-Eijnden

  • The heterogeneous multiscale method

    Assyr Abdulle;Weinan E;Weinan E;Björn Engquist;Eric Vanden-Eijnden

  • Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation.

    Linfeng Zhang;De-Ye Lin;Han Wang;Roberto Car

  • Active learning of uniformly accurate interatomic potentials for materials simulation

    Linfeng Zhang;De Ye Lin;Han Wang;Roberto Car

  • Towards a Theory of Transition Paths

    E Weinan;Eric Vanden-Eijnden

  • Finite temperature string method for the study of rare events.

    Weinan E;Weiqing Ren;Eric Vanden-Eijnden

  • The Heterogeneous Multiscale Method: A Review

    Weinan E;Bjorn Engquist;Xiantao Li;Weiqing Ren

  • Invariant measures for Burgers equation with stochastic forcing

    Weinan E;Konstantin Khanin;Alexander Mazel;Yakov Sinai

Frequent Co-Authors

Eric Vanden-Eijnden
Eric Vanden-Eijnden Courant Institute of Mathematical Sciences
Jianfeng Lu
Jianfeng Lu Duke University
Björn Engquist
Björn Engquist The University of Texas at Austin
Roberto Car
Roberto Car Princeton University
Arnulf Jentzen
Arnulf Jentzen Chinese University of Hong Kong, Shenzhen
Lin Lin
Lin Lin University of California, Berkeley
Chi-Wang Shu
Chi-Wang Shu Brown University
Lexing Ying
Lexing Ying Stanford University
Mark E. Tuckerman
Mark E. Tuckerman New York University
Yakov G. Sinai
Yakov G. Sinai Princeton University

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