Jianfeng Lu, Associate Professor of Mathematics and Chemistry and Physics
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 2018):
 MATH 69070.01, TOPICS IN APPLIED MATH
Synopsis
 Physics 235, TuTh 10:05 AM11:20 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)
 Huang, Y; Lu, J; Ming, P, A Concurrent Globalâ€“Local Numerical Method for Multiscale PDEs,
Journal of Scientific Computing
(February, 2018),
pp. 128 [doi] [abs]
 Lu, J; Zhou, Z, Accelerated sampling by infinite swapping of path integral molecular dynamics with surface hopping.,
Journal of Chemical Physics, vol. 148 no. 6
(February, 2018),
pp. 064110 [doi] [abs]
 Dai, S; Li, B; Lu, J, Convergence of PhaseField Free Energy and Boundary Force for Molecular Solvation,
Archive for Rational Mechanics and Analysis, vol. 227 no. 1
(January, 2018),
pp. 105147 [doi]
 Lu, J; Thicke, K, Cubic scaling algorithms for RPA correlation using interpolative separable density fitting,
Journal of Computational Physics, vol. 351
(December, 2017),
pp. 187202 [doi]
 Cao, Y; Lu, J, Lindblad equation and its semiclassical limit of the AndersonHolstein model,
Journal of Mathematical Physics, vol. 58 no. 12
(December, 2017) [doi] [abs]
 Recent Grant Support
 CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS1454939, 2015/092020/08.
 CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS1454939, 2015/092020/08.
