Broadly speaking, my research belongs to the area of optimisation, through mathematical programming, under uncertainty. My main interests span the areas of robust optimisation and stochastic programming, both of which are mathematical modelling techniques that can be applied to a wide range of cross disciplinary decision-making problems. I have used mathematical methods to derive novel reformulations and algorithmic solution approaches for classes of multi-stage robust optimisation and stochastic programming models such as network optimisation, combinatorial optimisation, and mixed integer optimisation. I have applied my results to integrated power grid expansion planning, disaster response planning, real options analysis in engineering systems design, and resilience improvement for critical infrastructure systems. More recently, I have been working on the concept of contextual optimization as a tool to merge, solidify, and extend the links between the fields of predictive and prescriptive analytics.

Methodological

- Robust optimisation

- Stochastic programming

- Cutting plane algorithms (Benders decomposition, row generation, approximations)

- Decision rules  

Application areas so far:
- Humanitarian logistics

- Flexibility and real options in engineering systems design

- Resilience of critical infrastructure systems

- Power grid expansion planning

- Route restoration

Experience

Senior Lecturer, The University of Edinburgh, 2023-present

Lecturer, The University of Edinburgh, 2018-2023

Senior Research Fellow, National University of Singapore and ETH Zurich, Singapore-ETH Center, 2018-2018

Research Fellow, National University of Singapore and ETH Zurich, Singapore-ETH Center, 2014-2018

Research Associate, Nanyang Technological University, 2013-2014

Academic Qualifications

Ph.D. Systems and Engineering Management, Nanyang Technological University, 2014

M.Sc. Industrial and Systems Engineering (specialization: Logistics and Operations Research), National University of Singapore, 2009 - Standard Chartered Bank Book Prize for being the best graduate in the graduating cohort in MSc (Industrial and Systems Engineering), with GPA 4.95 / 5.00

B.Eng. Industrial and Systems Engineering (specialization: Logistics and System Optimization), National University of Singapore, 2008

A Data-Driven Optimization Approach to Improve the Resilience of the Singapore
Mass Rapid Transit Network
Role: Lead Principal Investigator
Amount: S$249,974.58 - Funded by National Research Foundation of Singapore
Participating institutions: MIT, University of California, Berkeley, Technical University of Munich
Year awarded: 2017
NRF2017-ITS002-023

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