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.
JI Hui (PhD Maryland)
Jonathan SCARLETT (PhD Cambridge)
LI Qianxiao (PhD Princeton)
REN Weiqing (PhD NYU)
SHEN Zuowei (PhD Alberta)
SOH Yong Sheng (PhD Caltech)
TAN Yan Fu, Vincent (PhD MIT)
TONG Xin (PhD Princeton)
TOH Kim Chuan (PhD Cornell)
YANG Liu (PhD Brown)
ZHANG Louxin (PhD Waterloo)
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)
Julian SESTER(PhD Freiburg)
SUN Yeneng (PhD Illinois)
Marko WEBER (PhD SNS di Pisa)
ZHOU Chao (PhD Ecole Poly)
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)
LI Qianxiao (PhD Princeton)
REN Weiqing (PhD NYU)
TAN Roger (PhD La Trobe)
YANG Liu (PhD Brown)
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.
LI Qianxiao (PhD Princeton)
HAN Shaoning (PhD USC)
SOH Yong Sheng (PhD Caltech)
TOH Kim Chuan (PhD Cornell)
TONG Xin, (PhD Princeton)