Jianfeng Lu, Professor of Mathematics and Physics and Associate Professor of Chemistry
Jianfeng Lu is an applied mathematician interested in mathematical analysis and algorithm development for problems from computational physics, theoretical chemistry, materials science and other related fields.
More specifically, his current research focuses include: Electronic structure and many body problems; quantum molecular dynamics; multiscale modeling and analysis; rare events and sampling techniques.  Contact Info:
Teaching (Fall 2021):
 MATH 69060.01, TOPICS IN NUMERICAL METHODS
Synopsis
 Gross Hall 318, TuTh 08:30 AM09:45 AM
 Office Hours:
 By email appointments
 Education:
Ph.D.  Princeton University  2009 
BS  Peking University  2005 
 Specialties:

Applied Math
 Research Interests:
Mathematical analysis and algorithm development for problems from
computational physics, theoretical chemistry, materials science and others.
More specifically:
Electronic structure and many body problems;
Multiscale modeling and analysis; and
Rare events and sampling techniques.
 Areas of Interest:
Applied Mathematics Partial Differential Equations Probability Numerical Analysis Scientific Computing
 Curriculum Vitae
 Current Ph.D. Students
 Postdocs Mentored
 Haizhao Yang (July, 2015  present)
 Zhennan Zhou (August, 2014  present)
 Undergraduate Research Supervised
 Jeremy Tay (September, 2015  December, 2015)
 Fuchsia Chen (January, 2015  September, 2015)
 Leslie Lei (May, 2013  May, 2014)
 Recent Publications
(More Publications)
 Cheng, C; Daubechies, I; Dym, N; Lu, J, Stable phase retrieval from locally stable and conditionally connected measurements,
Applied and Computational Harmonic Analysis, vol. 55
(November, 2021),
pp. 440465 [doi] [abs]
 Li, L; Goodrich, C; Yang, H; Phillips, KR; Jia, Z; Chen, H; Wang, L; Zhong, J; Liu, A; Lu, J; Shuai, J; Brenner, MP; Spaepen, F; Aizenberg, J, Microscopic origins of the crystallographically preferred growth in evaporationinduced colloidal crystals.,
Proceedings of the National Academy of Sciences of the United States of America, vol. 118 no. 32
(August, 2021) [doi] [abs]
 An, D; Cheng, SY; HeadGordon, T; Lin, L; Lu, J, Convergence of stochasticextended Lagrangian molecular dynamics method for polarizable force field simulation,
Journal of Computational Physics, vol. 438
(August, 2021) [doi] [abs]
 Khoo, Y; Lu, J; Ying, L, Solving parametric PDE problems with artificial neural networks,
European Journal of Applied Mathematics, vol. 32 no. 3
(June, 2021),
pp. 421435 [doi] [abs]
 Yang, S; Cai, Z; Lu, J, Inclusionexclusion principle for open quantum systems with bosonic bath,
New Journal of Physics, vol. 23 no. 6
(June, 2021) [doi] [abs]
 Recent Grant Support
 RTG: Training Tomorrow's Workforce in Analysis and Applications, National Science Foundation, 2021/072026/06.
 NRTHDR: Harnessing AI for Autonomous Material Design, National Science Foundation, 2020/092025/08.
 Innovation of Numerical Methods for HighDimensional Problems, National Science Foundation, 2020/072023/06.
 FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis, National Science Foundation, 2019/102022/09.
 HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/102022/09.
 Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/092022/09.
 EAGERQACQSA: Resource Reduction in Quantum Computational Chemistry Mapping by Optimizing Orbital Basis Sets, National Science Foundation, 2020/092022/08.
 Collaborative Research: SI2SSI: ELSIInfrastructure for Scalable Electronic Structure Theory, National Science Foundation, 1450280, 2015/062022/05.
 Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/092021/09.
 CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS1454939, 2015/092020/08.
