Rongjie Lai - Biography

Education

Ph.D in Applied Mathematics, University of California, Los Angeles.

M. S. in Mathematics, Academy of Mathematics and System Science, Chinese Academy of Science.

B. S. in Mathematics, University of Science and Technology of China.

Employment

2023 – present: Professor, Department of Mathematics, Purdue University.
2014 – 2023: Assistant/Associate Professor, Department of Mathematical Sciences, Rensselaer Polytechnic Institute.

2013 – 2014: Visiting Assistant Professor, Department of Mathematics, University of California, Irvine.

2010 – 2013: NTT Assistant Professor, Department of Mathematics, University of Southern California.

Awards/Grants:

(Co-PI) NIH 1R21GM143506, "Method development for simultaneous automatic assignment and structure determination in protein NMR", 09/2022-08/2025. (collaborate with Chunyu Wang@RPI)
(PI) NSF SCALE MoDL (DMS-2401297, previous DMS-2134168), “Representation Learning via Variational Mean Field Theory”, 01/2022-03/2026. (collaborate with Tianyi Chen@RPI, Jie Chen@IBM (unpaid))
(PI) IBM AI Research Collaboration, 2019-2021.

(PI) NSF CAREER Award (DMS-1752934), “Geometry and Learning for Manifold-Structured Data in 3D and Beyond”, 2018-2023.

(PI) NSF DMS-1522645, “Geometric PDEs Based Methods for Analyzing Point Clouds in 3D and Higher”, 2015-2019.

(PI) American Mathematical Society Simons travel grant, 2013-2015.

(PI) Zumberge Individual Award, USC's James H. Zumberge Faculty Research and Innovation Fund, 2011-2012.

Shapiro International Fellowship, UCLA, 2006–2007.

Community Services:

Award selection committee, International Congress of Basic Science, 2024.
Co-founder and secretary (2023), SIAM Section NY/NJ/PA.
SIAM Student Chapter advisor, RPI. 2018 – 2023.
Referee for more than 30 Journals/Conferences.
Co-organized activities (see below):

Sampling, Inference and Data-Driven Physical Modeling in Scientific Machine Learning, IPAM, July, 2025.
Minisympoisium on "Data Driven and Reduced Order Methods in Dynamical System", SIAM conference on Applications of Dynamic Systems (DS25) Denver, U.S. 2025.
Minisymposiums on "Incorporating Scientific Computing/Geometry/Optimal Transport in Machine Learning: Theory and Applications", SIAM Conferene on Mathematics of Data Science, Oct. 2024.
Theory and Applications for Optimal Control and Generative Models, Purdue University, Aug 2024.
Inaugural SIAM-NNP Annual Meeting, Oct. 2023.
Minisymposium on "Optimal Transport: Computation, Applications, and Extensions", SIAM-NNP Annual meeting, Oct. 2023.
Minisymposium on "Geometric Methods for Understanding and Applying Machine Learning", SIAM Conference on Imaging Science, March 2022.
Workshop on "Geometry and Learning from Data", BIRS-CMO, Oct., 2021
Minisymposium on ‘‘Statistics and Machine Learning for the Euclidean Distance Geometry Problem", SIAM Conference on Data Science, Cincinnati, Ohio, May, 2020.
Geometry and Learning from Data in 3D and Beyond, IPAM three-month long program, UCLA, USA, March 11-June 14, 2019.
Minisympoiusm on Geometry and Learning in 3D Shape Analysis in SIAM Conference on Imaging Science (IS18). University of Bologna, Bologna, Italy. June 5-8, 2018.
Workshop on ‘‘Shape analysis and learning by geometry and machine’’, Institute of Pure and Applied Math (IPAM), UCLA, Feb. 2016.
Minisymposium on ‘‘Geometric Understanding of Data in 3D and Higher (I, II, III)", International Congress on Industrial and Applied Mathematics. Beijing, 2015
Minisymposium on ‘‘ Mathematics of Medical Imaging and Shape Analysis (I, II, III)", SIAM conference on image science, Philadelphia, 2012.