Machine Learning

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

Statistics, Machine Learning

Lim Ek Hong

Student

Machine Learning, Statistical Analysis

Machine Learning, Information Theory and Statistics

Yang Junwen

Student

Information Theory, Machine Learning

Finance, Decision making under Uncertainty, Machine Learning

Rayner Rebello

Student

Finance
Machine Learning, Optimisation Under Uncertainty

Optimization, Revenue Management, Online Machine Learning

Tang Yuxuan

Student

Machine Learning, Optimization, Revenue Management

Data-Driven Decision Making, Stochastic and Robust Optimization, Pricing and Revenue Management, Discrete Choice Models, Online Machine Learning, Sharing Economy in Transportation

Li Xiaobo

Assistant Professor

Industrial Systems Engineering and Management

Sharing Economy, Transportation
Data-driven Optimization, Discrete Choice Models, Machine Learning, Revenue Management, Robust Optimization

Privacy and Fairness in Data Mining and Machine Learning; Machine Learning; Evolutionary Multi-Objective Optimization; Constraint Programming

Cheng Peng

Senior Research Fellow

Constraint Programming, Machine Learning

Optimization, Statistics, Machine Learning

Bretislav Hajek

Student

Machine Learning, Optimization

Predictive modelling using machine learning methods, Large scale linear optimization, Robust optimization

Zhu Shaowen

Student

Machine Learning, Robust Optimization

Energy Finance, Time Series Analysis, Quantitative Finance, Explainable Machine Learning

Li Wei

Research Fellow

Finance
Machine Learning

Adversarial machine learning, Distributionally robust optimization

Yue Zhao

Research Fellow

Distributionally Robust Optimization, Machine Learning

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

Information Theory, Machine Learning

Shuche Wang

Student

Information Theory, Machine Learning

Intelligent Transportation Systems, Connected and Automated Vehicles, Machine learning applications in transportation

Xie Yuntong

Student

Transportation
Machine Learning

Financial technology, Operations research and machine learning in financial engineering

Jiang Gaozhe

Student

Finance
Machine Learning, Operations Research

Supply Chain Management, Machine Learning, Decision Making Under Uncertainty

Wu Meixi

Student

Supply Chain
Machine Learning, Optimisation Under Uncertainty

Federated Learning , Machine Learning

Li Wenqian

Student

Learning, Machine Learning

Machine Learning, Operations Research, Statistical Physics

Xu Yunbei

Affiliated Faculty Member

Industrial Systems Engineering and Management

Machine Learning, Operations Research, Statistical Physics

Machine learning

Zhang Jingqi

Student

Machine Learning

Dynamic Programming, Data Science, Machine Learning

Billy Tim Anthony

Student

Dynamic Programming, Machine Learning

Machine Learning

Research Focus

Industry Focus

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

Statistics, Machine Learning

Lim Ek Hong

Machine Learning, Information Theory and Statistics

Yang Junwen

Finance, Decision making under Uncertainty, Machine Learning

Rayner Rebello

Optimization, Revenue Management, Online Machine Learning

Tang Yuxuan

Data-Driven Decision Making, Stochastic and Robust Optimization, Pricing and Revenue Management, Discrete Choice Models, Online Machine Learning, Sharing Economy in Transportation

Li Xiaobo

Privacy and Fairness in Data Mining and Machine Learning; Machine Learning; Evolutionary Multi-Objective Optimization; Constraint Programming

Cheng Peng

Optimization, Statistics, Machine Learning

Bretislav Hajek

Predictive modelling using machine learning methods, Large scale linear optimization, Robust optimization

Zhu Shaowen

Energy Finance, Time Series Analysis, Quantitative Finance, Explainable Machine Learning

Li Wei

Adversarial machine learning, Distributionally robust optimization

Yue Zhao

Tong Xin

Information Theory, Machine Learning

Shuche Wang

Intelligent Transportation Systems, Connected and Automated Vehicles, Machine learning applications in transportation

Xie Yuntong

Financial technology, Operations research and machine learning in financial engineering

Jiang Gaozhe

Supply Chain Management, Machine Learning, Decision Making Under Uncertainty

Wu Meixi

Federated Learning , Machine Learning

Li Wenqian

Machine Learning, Operations Research, Statistical Physics

Xu Yunbei

Machine learning

Zhang Jingqi

Dynamic Programming, Data Science, Machine Learning

Billy Tim Anthony

IORA

Resources