Jianfeng Lu, Associate Professor of Mathematics and 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 (Spring 2020):
 MATH 69070.01, TOPICS IN APPLIED MATH
Synopsis
 Physics 119, WF 10:05 AM11:20 AM
 (also crosslisted as PHYSICS 590.03)
 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)
 Chen, H; Li, Q; Lu, J, A numerical method for coupling the BGK model and Euler equations through the linearized Knudsen layer,
Journal of Computational Physics, vol. 398
(December, 2019) [doi] [abs]
 Lu, J; Sogge, CD; Steinerberger, S, Approximating pointwise products of Laplacian eigenfunctions,
Journal of Functional Analysis, vol. 277 no. 9
(November, 2019),
pp. 32713282 [doi] [abs]
 Cao, Y; Lu, J; Lu, Y, Exponential Decay of Rényi Divergence Under Fokker–Planck Equations,
Journal of Statistical Physics, vol. 176 no. 5
(September, 2019),
pp. 11721184 [doi] [abs]
 Wang, Z; Li, Y; Lu, J, Coordinate Descent Full Configuration Interaction.,
Journal of Chemical Theory and Computation, vol. 15 no. 6
(June, 2019),
pp. 35583569 [doi] [abs]
 Liu, JG; Lu, J; Margetis, D; Marzuola, JL, Asymmetry in crystal facet dynamics of homoepitaxy by a continuum model,
Physica D: Nonlinear Phenomena, vol. 393
(June, 2019),
pp. 5467 [doi] [abs]
 Recent Grant Support
 FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis, National Science Foundation, 2019/102022/09.
 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, 2018/092021/09.
 Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/092021/09.
 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, 1454939, 2015/092020/08.
 CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS1454939, 2015/092020/08.
 Collaborative Research: SI2SSI: ELSIInfrastructure for Scalable Electronic Structure Theory, National Science Foundation, 1450280, 2015/062020/05.
