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Jianfeng Lu, Professor

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 (Spring 2024):

  • PHYSICS 590.01, TOPICS IN THEORETICAL PHYSICS Synopsis
    Gross Hall 324, TuTh 10:05 AM-11:20 AM
    (also cross-listed as MATH 690-70.02)
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. Li, X; Pura, J; Allen, A; Owzar, K; Lu, J; Harms, M; Xie, J, DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree., Genetic Epidemiology, vol. 48 no. 1 (February, 2024), pp. 42-55 [doi]  [abs]
  2. 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 (January, 2024) [doi]  [abs]
  3. 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 (November, 2023), pp. 7731-7739 [doi]  [abs]
  4. Cao, Y; Lu, J; Wang, L, On Explicit L2 -Convergence Rate Estimate for Underdamped Langevin Dynamics, Archive for Rational Mechanics and Analysis, vol. 247 no. 5 (October, 2023) [doi]  [abs]
  5. Lu, J; Wu, Y; Xiang, Y, Score-based Transport Modeling for Mean-Field Fokker-Planck Equations, vol. 503 (April, 2023) [doi]  [abs]
Recent Grant Support

  • Innovation of Numerical Methods for High-Dimensional Partial Differential Equations, National Science Foundation, 2023/08-2026/07.      
  • New computational methods to dynamically pinpointing the subregions carrying disease-associated rare variants, National Institutes of Health, 2022/09-2026/07.      
  • RTG: Training Tomorrow's Workforce in Analysis and Applications, National Science Foundation, 2021/07-2026/06.      
  • NRT-HDR: Harnessing AI for Autonomous Material Design, National Science Foundation, 2020/09-2025/08.      
  • FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis, National Science Foundation, 2019/10-2023/09.      
  • HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms, National Science Foundation, 2019/10-2023/09.      
  • EAGER-QAC-QSA: Resource Reduction in Quantum Computational Chemistry Mapping by Optimizing Orbital Basis Sets, National Science Foundation, 2020/09-2023/08.      
  • Innovation of Numerical Methods for High-Dimensional Problems, National Science Foundation, 2020/07-2023/06.      
  • Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/09-2022/09.      
  • Collaborative Research: SI2-SSI: ELSI-Infrastructure for Scalable Electronic Structure Theory, National Science Foundation, 1450280, 2015/06-2022/05.      
  • Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/09-2021/09.      

 

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

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