The group conducts research in modern biology problems by tapping on strengths in combinatorics, probability and statistics. Our current interests include detection of functional signals in biological sequences and protein networks, algorithms and models for inference of gene duplication history and reconstruction of phylogenetic networks, and discovery of the topological and dynamic principles of transcriptional regulatory networks.

Louis CHEN (PhD Stanford)
CHOI Kwok Pui (PhD Illinois)

ZHANG Louxin (PhD Waterloo)

Imaging & Vision Science

This multidisciplinary research group emphasizes the synergy of mathematics, engineering and computer science in the areas of imaging science, computer vision, information theory and learning. Topics of interest include wavelet frame methods in imaging science, compressive sensing, data assimilation, low rank matrix completion and their applications, time-frequency and scale-space methods in signal processing, human and computer vision, and the interplay between information theory and statistical learning.

GOH Say Song (PhD Michigan)
JI Hui (PhD Maryland)
Jonathan SCARLETT (PhD Cambridge)
LI Qianxiao (PhD Princeton)
SHEN Zuowei (PhD Alberta)

TAN Yan Fu, Vincent (PhD MIT)
TAN Hwee Huat (PhD Adelaide)
TONG Xin (PhD Princeton)
YANG Haizhao (PhD Stanford)

Mathematical Finance & Mathematical Economics

The group works in the interface of mathematics with finance and economics. Topics of interest include pricing of financial derivatives, portfolio selection, risk measure, fixed income products, credit risk, trading strategy, fintech, games with imperfect information or with many players or with location problems, random matching of economic agents, incentive compatibility problems in a large market with asymmetric information.

CHEN Ying (PhD Humboldt-Berlin)
DAI Min (PhD Fudan)
SUN Yeneng (PhD Illinois)

Marko WEBER (PhD SNS di Pisa)
ZHOU Chao (PhD Ecole Poly)

Numerical Analysis & Scientific Computing

The group focuses on the design and analysis of efficient, accurate and robust numerical methods and their applications to applied sciences and engineering. Topics include numerical linear algebra, computational fluid dynamics, computational materials science, multi-phase/complex fluids, computational quantum and plasma physics, control theory, analysis of finite element and spectral methods, analysis and modeling of complex energy landscapes and barrier-crossing events, multi-scale/multi-physics methods, and emerging applications.

BAO Weizhu (PhD Tsinghua)
CAI Zhenning (PhD Peking)
CHU Delin (PhD Tsinghua)
Simon ETTER (PhD Warwick)
LI Qianxiao (PhD Princeton)

REN Weiqing (PhD NYU)
TAN Roger (PhD La Trobe)
TOH Kim Chuan (PhD Cornell)
YANG Haizhao (PhD Stanford)

Optimization, Machine Learning and Data Science

The group works mainly on the analysis, design and implementation of algorithms for continuous optimization, possibly with stochastic variables. Topics of interest include conic programming and its applications, interior point methods, nonsmooth Newton methods, augmented Lagrangian methods, iterative methods for large linear systems of equations, feasibility problems, first order methods, stochastic gradient descent and data analysis.

CAI Zhenning (PhD Peking)
LEE Ching-pei (PhD Wisconsin)
LI Qianxiao (PhD Princeton)
Jeffrey PANG (PhD Cornell)
TOH Kim Chuan (PhD Cornell)

TONG Xin, (PhD Princeton)
YANG Haizhao (PhD Stanford)
ZHAO Gong Yun (PhD Wuerzburg)