Faculty of Science

Mathematical optimization, particularly mixed-integer nonlinear programming and nonsmooth optimization, along with their applications in operations research, data science, and other related fields.

Shaoning Han

Affiliated Faculty
Mathematics
  • data science, Mathematical optimization, mixed-integer nonlinear programming, nonsmooth optimization, Operations Research
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His research interests centre around stochastic processes and their broad applications and intersections with other fields such as data science, with a particular focus on Markov chains theory and stochastic algorithms driven by Markov chains

Michael Choi

Statistics and Data Science
  • Markov Chain, Stochastic Processes
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My research interests lie broadly inside probability theory and its applications in statistics, machine learning and nonlinear systems. My recent research involves investigating the behavior of algorithms, e.g. EnKF, MCMC and SGD, when the problem dimension is high. One of the common theme is that we can show stable performance of these algorithms, if certain intrinsic structures can be exploited

Tong Xin

Assistant Professor
Mathematics
  • Machine Learning
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I am broadly interested in mathematical optimization and its applications to the data sciences. I am specifically interested in developing optimization-based methodology for a range of data processing problems, as well as understanding the performance and limitations of widely used optimization-based methods in the data sciences

Soh Yong Sheng

Mathematics
  • Optimization
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Forecasting and Business Intelligence, Non-stationary Time Series Analysis, High Frequency Data and Limit Order Book, Functional Data Analysis and Network Analytics, Text Mining and Sentiment Analysis, Renewable Energy Data Analytics, Risk Management, Crypto Blockchain

Chen Ying

Mathematics
  • Blockchain, Forecasting, Risk Management
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Second order backward stochastic differential equations (2BSDEs), Stochastic control in finance and insurance, Valuation adjustments, Principal-Agent problems, Data analytics and information acquisition, Deep learning methods

Zhou Chao

Mathematics
  • Finance
  • Deep Learning, Stochastic Control
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Bayesian model selection, Bayesian nonparametrics, hierarchical models, Markov chain Monte Carlo, spatio-temporal modelling.

David Nott

Associate Professor
Statistics and Data Science
  • Bayesian models, Markov Chain
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Sequential analysis, Change-point detection, Monte Carlo methods

Chan Hock Peng

Statistics and Data Science
  • Change-Point Detection, Monte Carlo Methods
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Matrix Optimization Problems: algorithms, applications, and theory. In particular, large scale semidefinite programming. Fast algorithms for large scale statistical and machine learning problems. Iterative methods for large linear systems of equations, especially those arising in optimization.

Toh Kim Chuan

Research Director (Technical)
Mathematics
  • Algorithms, Machine Learning, Matrix Optimization, Semidefinite Programming
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