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

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:
Web Page:	http://www.math.duke.edu/~jianfeng/

Teaching (Fall 2021):

• MATH 690-60.01, TOPICS IN NUMERICAL METHODS Synopsis

  Gross Hall 318, TuTh 08:30 AM-09:45 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  

• 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. Cheng, C; Daubechies, I; Dym, N; Lu, J, Stable phase retrieval from locally stable and conditionally connected measurements, Applied and Computational Harmonic Analysis, vol. 55 (November, 2021), pp. 440-465 [doi]  [abs]
2. Li, L; Goodrich, C; Yang, H; Phillips, KR; Jia, Z; Chen, H; Wang, L; Zhong, J; Liu, A; Lu, J; Shuai, J; Brenner, MP; Spaepen, F; Aizenberg, J, Microscopic origins of the crystallographically preferred growth in evaporation-induced colloidal crystals., Proceedings of the National Academy of Sciences of the United States of America, vol. 118 no. 32 (August, 2021) [doi]  [abs]
3. An, D; Cheng, SY; Head-Gordon, T; Lin, L; Lu, J, Convergence of stochastic-extended Lagrangian molecular dynamics method for polarizable force field simulation, Journal of Computational Physics, vol. 438 (August, 2021) [doi]  [abs]
4. Khoo, Y; Lu, J; Ying, L, Solving parametric PDE problems with artificial neural networks, European Journal of Applied Mathematics, vol. 32 no. 3 (June, 2021), pp. 421-435 [doi]  [abs]
5. Yang, S; Cai, Z; Lu, J, Inclusion-exclusion principle for open quantum systems with bosonic bath, New Journal of Physics, vol. 23 no. 6 (June, 2021) [doi]  [abs]

Recent Grant Support

• 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.      
• 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.      
• Quantum Computing in Chemical and Material Sciences, Department of Energy, 2018/09-2022/09.      
• EAGER-QAC-QSA: Resource Reduction in Quantum Computational Chemistry Mapping by Optimizing Orbital Basis Sets, National Science Foundation, 2020/09-2022/08.      
• 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.      
• CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS-1454939, 2015/09-2020/08.