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

Contact Information

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


  • Ph.D. Princeton University, 2009

Awards, Honors, and Distinctions

  • 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 541: Applied Stochastic Processes
  • MATH 555: Ordinary Differential Equations
  • MATH 631: Measure and Integration
  • MATH 660: Numerical Partial Differential Equations
  • MATH 690-60: Topics in Numerical Methods
  • STA 621: Applied Stochastic Processes

In the News

Representative Publications

  • Zhou, M; Lu, J, A Policy Gradient Framework for Stochastic Optimal Control Problems with
    Global Convergence Guarantee
    (2023) [abs].
  • Bierman, J; Li, Y; Lu, J, Improving the Accuracy of Variational Quantum Eigensolvers with Fewer Qubits Using Orbital Optimization., Journal of Chemical Theory and Computation, vol 19 no. 3 (2023), pp. 790-798 [10.1021/acs.jctc.2c00895] [abs].
  • Chen, Z; Lu, J; Lu, Y; Zhang, X, On the convergence of Sobolev gradient flow for the Gross-Pitaevskii
    eigenvalue problem
    (2023) [abs].
  • Wang, M; Lu, J, Neural Network-Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions, Communications in Mathematics and Statistics (2023) [10.1007/s40304-023-00339-5] [abs].
  • Holst, M; Hu, H; Lu, J; Marzuola, JL; Song, D; Weare, J, Symmetry Breaking and the Generation of Spin Ordered Magnetic States in Density Functional Theory Due to Dirac Exchange for a Hydrogen Molecule, Journal of Nonlinear Science, vol 32 no. 6 (2022) [10.1007/s00332-022-09845-2] [abs].