Jianfeng Lu, Associate Professor of Mathematics and 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 (Spring 2020):

• MATH 690-70.01, TOPICS IN APPLIED MATH Synopsis

  Physics 119, WF 10:05 AM-11:20 AM

  (also cross-listed as PHYSICS 590.03)

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. Chen, H; Li, Q; Lu, J, A numerical method for coupling the BGK model and Euler equations through the linearized Knudsen layer, Journal of Computational Physics, vol. 398 (December, 2019) [doi]  [abs]
2. Lu, J; Sogge, CD; Steinerberger, S, Approximating pointwise products of Laplacian eigenfunctions, Journal of Functional Analysis, vol. 277 no. 9 (November, 2019), pp. 3271-3282 [doi]  [abs]
3. Cao, Y; Lu, J; Lu, Y, Exponential Decay of Rényi Divergence Under Fokker–Planck Equations, Journal of Statistical Physics, vol. 176 no. 5 (September, 2019), pp. 1172-1184 [doi]  [abs]
4. Wang, Z; Li, Y; Lu, J, Coordinate Descent Full Configuration Interaction., Journal of Chemical Theory and Computation, vol. 15 no. 6 (June, 2019), pp. 3558-3569 [doi]  [abs]
5. Liu, JG; Lu, J; Margetis, D; Marzuola, JL, Asymmetry in crystal facet dynamics of homoepitaxy by a continuum model, Physica D: Nonlinear Phenomena, vol. 393 (June, 2019), pp. 54-67 [doi]  [abs]

Recent Grant Support

• FET: Small: Efficient Inference Tools for Quantum Systems: Algorithms, Applications, and Analysis, National Science Foundation, 2019/10-2022/09.      
• 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, 2018/09-2021/09.      
• 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.      
• CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, 1454939, 2015/09-2020/08.      
• CAREER: Research and training in advanced computational methods for quantum and statistical mechanics, National Science Foundation, DMS-1454939, 2015/09-2020/08.      
• Collaborative Research: SI2-SSI: ELSI-Infrastructure for Scalable Electronic Structure Theory, National Science Foundation, 1450280, 2015/06-2020/05.