Biography

Nengli received his Ph.D. in Mathematics at Imperial College London (under a joint programme with the National University of Singapore), where he focused on stochastic analysis and rough paths theory. Before that, he studied random dynamical systems at Princeton University (M.A. Applied Mathematics), and in the Courant Institute of Mathematical Sciences at NYU (M.S. Mathematics).

Prior to obtaining his doctorate, he has previously worked at the Bioinformatics Institute in A*STAR on image analysis, and at DSO National Laboratories on designing efficient algorithms to track targets obtained from sensor data.

Education

  • Ph.D. Mathematics, Imperial College London (2016)
  • M.A. Applied Mathematics, Princeton University (2010)
  • M.S. Mathematics, New York University (2008)
  • B.A. Applied Mathematics and Cognitive Neuroscience, Summa Cum Laude, University of California, Berkeley (2004)

Research Interests

Stochastic analysis, Rough paths theory, Gaussian processes, Neural networks and Deep learning.
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Teaching

Fall 2017: Real Analysis

Research Groups

SUTD Brain Lab 

Selected Publications

  • T. Cass and N. Lim (2017), A Stratonovich-Skorohod integral formula for Gaussian rough paths, under review in The Annals of Probability.
  • N. Lim and N. Privault (2015), Analytic bond pricing for short rate dynamics evolving on matrix Lie groups, Quantitative Finance.
  • T. Gong, N. Lim, L. Cheng, H. Lee, et al. (2013), Finding distinctive shape features for automatic hematoma classification in head CT images from traumatic brain injuries, International Conference on Tools with Artificial Intelligence (ICTAI).

Awards

  • Yael Naim Dowker Centenary Prize, awarded for best mathematics Ph.D. thesis, Imperial College London (2016)
  • Dorothea Klumpke Roberts Prize, awarded for exceptional scholarship in mathematics, UC Berkeley (2004)