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Jianfeng Lu


Professor of Mathematics

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.

Appointments and Affiliations

  • Professor of Mathematics
  • Associate Professor of Chemistry
  • Professor of Physics

Contact Information

  • Office Location: 242 Physics Bldg, 120 Science Drive, Durham, NC 27708
  • Office Phone: (919) 660-2875
  • Email Address:
  • Websites:


  • Ph.D. Princeton University, 2009

Awards, Honors, and Distinctions

  • Feng Kang Prize of Scientific Computing. Chinese Academy of Sciences. 2023
  • IMA Prize in Mathematics and its Applications. Institute of Mathematics and its Applications. 2017
  • CAREER Award. National Science Foundation. 2015
  • Sloan Research Fellowship. Alfred P. Sloan Foundation. 2013
  • Porter Ogden Jacobus Fellowship. Princeton University. 2008

Courses Taught

  • MATH 391: Independent Study
  • MATH 393: Research Independent Study
  • MATH 394: Research Independent Study
  • MATH 493: Research Independent Study
  • MATH 555: Ordinary Differential Equations
  • MATH 631: Measure and Integration
  • MATH 660: Numerical Partial Differential Equations
  • MATH 690-60: Topics in Numerical Methods

In the News

Representative Publications

  • Jing, Y; Chen, J; Li, L; Lu, J, A Machine Learning Framework for Geodesics Under Spherical Wasserstein–Fisher–Rao Metric and Its Application for Weighted Sample Generation, Journal of Scientific Computing, vol 98 no. 1 (2024) [10.1007/s10915-023-02396-y] [abs].
  • Chen, Z; Lu, J, Exact and Efficient Representation of Totally Anti-Symmetric Functions (2023) [abs].
  • Wang, Z; Zhang, Z; Lu, J; Li, Y, Coordinate Descent Full Configuration Interaction for Excited States., Journal of Chemical Theory and Computation, vol 19 no. 21 (2023), pp. 7731-7739 [10.1021/acs.jctc.3c00452] [abs].
  • Cheng, X; Lu, J; Tan, Y; Xie, Y, Convergence of flow-based generative models via proximal gradient
    descent in Wasserstein space
    (2023) [abs].
  • Bierman, J; Li, Y; Lu, J, Qubit Count Reduction by Orbital Optimization for Variational Quantum
    Excited States Solvers
    (2023) [abs].

Affiliate Topics in Materials Research