Rongjie Lai
Dr. Rongjie Lai received his B.S. degree in mathematics from the University of Science and Technology of China, in 2003, his M.S. degree in mathematics from the Academy of Mathematics and System Sciences, Chinese Academy of Sciences in 2006 and his Ph.D. degree in applied mathematics from the University of California, Los Angeles, in 2010. Before he joined RPI in 2014, Dr. Lai held visiting assistant professor positions at the University of Southern California and the University of California, Irvine, respectively.
Dr. Lai’s research interests are mainly in developing mathematical and computational tools for analyzing and processing signals, images as well as unorganized data using methods of variational partial differential equations, computational differential geometry and learning. His research further extends to the design of efficient numerical methods to solve variational PDEs and optimization problems. Dr. Lai’s research has wide applications in medical imaging, brain mapping, computer graphics, as well as their extensions to data science. In 2018, Dr. Lai was granted an NSF CAREER award for his research in geometry and learning for manifoldstructured data in 3D and higher dimension.
Education

B.S. in Mathematics, University of Science and Technology of China, 2003
M.S. in Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, 2006
Ph.D in Applied Mathematics, University of California, Los Angeles, 2010
Selected Publications
 R. Lai, J. Li, “Manifold Based Lowrank Regularization for Image Restoration and Semisupervised Learning”, Journal of Scientific Computing, 74(3), pp 1241–1263, 2018.
 R. Lai, J. Lu, “Point Cloud Discretization of FokkerPlanck Operators for Committor Functions”, Multiscale Modeling & Simulation, 16(2), 710726, 2018
 R. Lai and H. Zhao, "Multiscale NonRigid Point Cloud Registration Using Rotationinvariant SlicedWasserstein Distance via LaplaceBeltrami Eigenmap". SIAM Journal on Imaging Sciences, 10(2), pp. 449—483, 2017.
 R. Lai and J. Li, "Solve Partial Differential Equations on Manifolds from Incomplete Distance Information", SIAM Journal on Scientific Computing, 39(5), pp. 22312256, 2017.
 C. Kao, R. Lai and B. Osting,"Maximal LaplaceBeltrami Eigenvalues on Closed Riemannian Surfaces". ESAIM: Control, Optimization and Calculus of Variations, 23(2), pp. 685720, 2017
 R. Lai and J. Lu, “Localized Density Matrix Minimization and Linear Scaling Algorithms”, 315, pp. 194–210, Journal of Computational Physcis, 2016
 V. Ozolins, R. Lai, R. Caflisch, S. Osher， “Compressed Modes for Variational Problems in Mathematics and Physics”, Proceedings of the National Academy of Sciences (PNAS), 110 (46), pp. 18368–18373, 2013.
 R. Lai and S. Osher, “A splitting method for orthogonality constrained problems”, Journal of Scientific Computing, 58(2), pp. 431–449. 2014.
 Y. Shi, R. Lai, J.J. Wang, D. Pelletier, D. Mohr, N. Sicotte and A. W. Toga: “Metric Optimization for Surface Analysis in the LaplaceBeltrami Embedding Space”, IEEE Trans. Medical Imaging， 33(7), pp. 1447–1463, 2014.
 R. Lai, Z. Wen, W. Yin, X. Gu, and L. Lui, “FoldingFree Global Conformal Mapping for Genus0 Surfaces by Harmonic Energy Minimization”, Journal of Scientific Computing, 58(3), pp. 705–725, 2014.