Overview
Jianfeng Lu is an applied mathematician interested in mathematical analysis and algorithm development for problems from computational physics, theoretical chemistry, materials science, machine learning, and other related fields.
More specifically, his current research focuses include:
High dimensional PDEs; generative models and sampling methods; control and reinforcement learning; electronic structure and many body problems; quantum molecular dynamics; multiscale modeling and analysis.
More specifically, his current research focuses include:
High dimensional PDEs; generative models and sampling methods; control and reinforcement learning; electronic structure and many body problems; quantum molecular dynamics; multiscale modeling and analysis.
Current Appointments & Affiliations
James B. Duke Distinguished Professor of Mathematics
·
2024 - Present
Mathematics,
Trinity College of Arts & Sciences
Professor of Mathematics
·
2020 - Present
Mathematics,
Trinity College of Arts & Sciences
Associate Professor of Chemistry
·
2016 - Present
Chemistry,
Trinity College of Arts & Sciences
Professor of Physics
·
2023 - Present
Physics,
Trinity College of Arts & Sciences
Recent Publications
Mixing Time of Open Quantum Systems via Hypocoercivity.
Journal Article Physical review letters · April 2025 Understanding the mixing of open quantum systems is a fundamental problem in physics and quantum information science. Existing approaches for estimating the mixing time often rely on the spectral gap estimation of the Lindbladian generator, which can be ch ... Full text CiteSolution Theory of Hamilton-Jacobi-Bellman Equations in Spectral Barron Spaces
Preprint · March 24, 2025 Link to item CiteBi-Lipschitz Ansatz for Anti-Symmetric Functions
Preprint · March 6, 2025 Link to item CiteRecent Grants
Collaborative Research: RI: Medium: Machine learning for PDEs, and with PDEs
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2024 - 2028NRT-HDR: Harnessing AI for Autonomous Material Design
Inst. Training Prgm or CMEParticipants · Awarded by National Science Foundation · 2020 - 2026Innovation of Numerical Methods for High-Dimensional Partial Differential Equations
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2023 - 2026View All Grants
Education, Training & Certifications
Princeton University ·
2009
Ph.D.