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Math @ Duke





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Jianfeng Lu, Professor of Mathematics and Associate Professor of Chemistry and Physics

Jianfeng Lu

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:
Office Location:  242 Physics Bldg, 120 Science Drive, Durham, NC 27708
Office Phone:  (919) 660-2875
Email Address: send me a message
Web Page:  http://www.math.duke.edu/~jianfeng/

Teaching (Fall 2020):

  • MATH 631.01, MEASURE AND INTEGRATION Synopsis
    Online ON, TuTh 10:15 AM-11:30 AM
Office Hours:

By email appointments
Education:

Ph.D.Princeton University2009
BSPeking University2005
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  

  • Kyle Thicke  
  • Chao Xu  
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)

  1. Han, J; Lu, J; Zhou, M, Solving high-dimensional eigenvalue problems using deep neural networks: A diffusion Monte Carlo like approach, Journal of Computational Physics, vol. 423 (December, 2020) [doi]  [abs]
  2. Lu, J; Lu, Y; Zhou, Z, Continuum limit and preconditioned Langevin sampling of the path integral molecular dynamics, Journal of Computational Physics, vol. 423 (December, 2020) [doi]  [abs]
  3. Cai, Z; Lu, J; Yang, S, Inchworm Monte Carlo Method for Open Quantum Systems, Communications on Pure and Applied Mathematics, vol. 73 no. 11 (November, 2020), pp. 2430-2472 [doi]  [abs]
  4. Yu, VWZ; Campos, C; Dawson, W; García, A; Havu, V; Hourahine, B; Huhn, WP; Jacquelin, M; Jia, W; Keçeli, M; Laasner, R; Li, Y; Lin, L; Lu, J; Moussa, J; Roman, JE; Vázquez-Mayagoitia, Á; Yang, C; Blum, V, ELSI — An open infrastructure for electronic structure solvers, Computer Physics Communications, vol. 256 (November, 2020), pp. 107459-107459, Elsevier BV [doi]  [abs]
  5. Lu, J; Steinerberger, S, Synchronization of Kuramoto oscillators in dense networks, Nonlinearity, vol. 33 no. 11 (November, 2020), pp. 5905-5918 [doi]  [abs]
Recent Grant Support

  • NRT-HDR: Harnessing AI for Autonomous Material Design, National Science Foundation, 2020/09-2025/08.      
  • Innovation of Numerical Methods for High-Dimensional Problems, National Science Foundation, 2020/07-2023/06.      
  • FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis, National Science Foundation, 2019/10-2022/09.      
  • HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/10-2022/09.      
  • EAGER-QAC-QSA: Resource Reduction in Quantum Computational Chemistry Mapping by Optimizing Orbital Basis Sets, National Science Foundation, 2020/09-2022/08.      
  • Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/09-2021/09.      
  • Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/09-2021/09.      
  • Collaborative Research: SI2-SSI: ELSI-Infrastructure for Scalable Electronic Structure Theory, National Science Foundation, 1450280, 2015/06-2021/05.      
  • CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS-1454939, 2015/09-2020/08.      

 

dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320