I am a Ph.D. candidate at University of Toronto under the supervision of Professor Scott Sanner, and a member of the Data-Driven Decision Making Lab (D3M). I am also a Postgraduate Affiliate with the Vector Institute. Previously, I have completed my BASc. in Industrial Engineering from University of Toronto (2014) with emphasis on Operations Research, and earned my MASc. from University of Toronto (2016) as a member of the Toronto Intelligent Decision Engineering Laboratory (TIDEL) on the topic of Mixed-Integer Linear Programming Models for Least-Commitment Partial-Order Planning under the supervision of Professor J. Christopher Beck and Professor Andre Augusto Cire. My main research focus is on the theory and the application of Operations Research techniques and Deep Neural Networks to our Data-Driven Automated Planning framework.
- Mar 25, 2019: Joined the Vector Institute as a Postgraduate Affiliate.
- Feb 14, 2019: Gave two seminar lectures on Artificial Intelligence in University of Toronto.
- Feb 1, 2019: Paper on metric hybrid nonlinear planning with constraint generation got accepted to CPAIOR-2019.
- Nov 26, 2018: Paper on compact and efficient encodings for planning with binarized neural networks is submitted to AIJ.
- Jul 28, 2018: The original neural network based planner: HD-MILP-Plan is re-written in Python and now online.
- Jun 2, 2018: Two binarized neural network based planners: FD-BLP-Plan and FD-SAT-Plan are now online.
- May 25, 2018: Paper on symbolic bucket elimination for optimization problems received Student Paper Award at CPAIOR-2018.
- Apr 4, 2018: Paper on planning with binarized neural networks got accepted to IJCAI-ECAI-2018.