Research Programmes

About Research Due to the uniqueness of service systems, it is often necessary to harness domain specific knowledge to improve the efficiency of algorithms and elicit insights that can be translated into effective operational policies. We will focus on healthcare service systems. An efficient, affordable, and high-quality healthcare system…
About Research Due to the uniqueness of service systems, it is often necessary to harness domain specific knowledge to improve the efficiency of algorithms and elicit insights that can be translated into effective operational policies. We will focus on healthcare service systems. An efficient, affordable, and high-quality healthcare system…
About the Project The research domains are based on sound science and solid mathematical foundations and they include Mathematical optimization Stochastic and Robust Optimization Decision Making under Risk and Uncertainty Applied Probability and Stochastic Analysis Principal Investigator Team Recent Projects…
About the Project The research domains are based on sound science and solid mathematical foundations and they include Mathematical optimization Stochastic and Robust Optimization Decision Making under Risk and Uncertainty Applied Probability and Stochastic Analysis Principal Investigator Team Recent Projects…
About the Project Consider a large number of detectors each generating a data stream. The task is to detect online, distribution changes in a small fraction of the data streams. We propose optimal algorithms that minimize the detection delay subject to a given average run length constraint. We also…
About the Project Consider a large number of detectors each generating a data stream. The task is to detect online, distribution changes in a small fraction of the data streams. We propose optimal algorithms that minimize the detection delay subject to a given average run length constraint. We also…
About the Project Variational inference methods are very useful in the analysis of large datasets. The key idea of such methods for Bayesian inference is to reformulate the problem of approximating a posterior distribution as an optimization problem. Recent progress in the area has been concerned with the application…
About the Project Variational inference methods are very useful in the analysis of large datasets. The key idea of such methods for Bayesian inference is to reformulate the problem of approximating a posterior distribution as an optimization problem. Recent progress in the area has been concerned with the application…
About the Project Approximate Bayesian computation (ABC) is a paradigm which allows one to perform Bayesian statistical inference, when the associate probability is totally intractable in a certain manner. In order to conduct this afore-mentioned inference, one must resort to Monte Carlo estimation. A/P Jasra and Dr Jo are…
About the Project Approximate Bayesian computation (ABC) is a paradigm which allows one to perform Bayesian statistical inference, when the associate probability is totally intractable in a certain manner. In order to conduct this afore-mentioned inference, one must resort to Monte Carlo estimation. A/P Jasra and Dr Jo are…
About the Project Algorithm efficiency for computationally expensive objective functions (e.g. computer codes) is greatly improved with the use of statistically based surrogate response surfaces iteratively built during the search process and with intelligent algorithms that effectively utilize parallel and distributed computing. The optimization and uncertainty quantification effort is…
About the Project Algorithm efficiency for computationally expensive objective functions (e.g. computer codes) is greatly improved with the use of statistically based surrogate response surfaces iteratively built during the search process and with intelligent algorithms that effectively utilize parallel and distributed computing. The optimization and uncertainty quantification effort is…
About Research Below are examples of how Operations Research can be used in Singapore and in Asia this Environmental and Water Resource area: Urban Hydrology Optimization and statistical analysis of water inflow and its pathway through an urban watershed can be used to design more efficient ways to harvest…
About Research Below are examples of how Operations Research can be used in Singapore and in Asia this Environmental and Water Resource area: Urban Hydrology Optimization and statistical analysis of water inflow and its pathway through an urban watershed can be used to design more efficient ways to harvest…
About Research Currently the leading team in the world in designing algorithms for solving large scale convex Optimisation problems, Developing other tools in Financial engineering, Sequential MC, Robust Optimization and learning algorithms. The Analytics group has strong interest in solving large scale optimization problems, with applications to data analytics.  Principal Investigators…
About Research Currently the leading team in the world in designing algorithms for solving large scale convex Optimisation problems, Developing other tools in Financial engineering, Sequential MC, Robust Optimization and learning algorithms. The Analytics group has strong interest in solving large scale optimization problems, with applications to data analytics.  Principal Investigators…
About Research We began a partnership with the Infocomm Media Development Authority of Singapore (IMDA) in Dec 2018, to use analytics and help them evaluate the Locker Alliance pilot they launched in Bukit Panjang and Punggol. The Locker Alliance is an interoperable network of parcel lockers located in residential…
About Research We began a partnership with the Infocomm Media Development Authority of Singapore (IMDA) in Dec 2018, to use analytics and help them evaluate the Locker Alliance pilot they launched in Bukit Panjang and Punggol. The Locker Alliance is an interoperable network of parcel lockers located in residential…