03/RESEARCH
Research
Four research appointments across scientific machine learning, additive manufacturing, and the MIT Research Laboratory of Electronics.
Interests
- Scientific machine learning
- Numerical solvers and learned models in the same system, where the analysis tradition sets the standard for what counts as correct.
- Applied ML for materials and manufacturing
- Learned models over instrument data, where the measurement physics constrains what the model is allowed to claim.
- Probabilistic risk modelling
- Risk stated as a calibrated distribution rather than a single number, so the uncertainty survives into the decision.
Appointments
Oct 2026 – Present
Singapore-MIT Alliance for Research and Technology
Visiting Student
Selected for a research appointment under Prof. Rajeev J. Ram of MIT EECS and the Research Laboratory of Electronics.
Jul – Sep 2026
Nanyang Technological University
Undergraduate Research Assistant
Awarded a competitive undergraduate bursary to return to SC3DP for two research projects.
Jul 2025 – Mar 2026
MIT Julia Lab
Research Intern
Research intern at the MIT Julia Lab under PI Dr. Chris Rackauckas.
Jan – Jul 2025
Nanyang Technological University
Research Intern
Research intern at SC3DP with Prof. Paulo Bartolo, prior to starting my undergraduate studies.
Research-adjacent projects
- Empirical Study of RoA Penalty Functions in NeuralLyapunov.jl
A controlled study of how region-of-attraction penalties shape stability certificates learned by physics-informed networks.
- Federated Whisper Aggregation Pipeline
Fine-tuning a production speech model across decentralised datasets without moving any data.
- MoE Compression of LLM Weights
Post-training compression of Mixture-of-Experts checkpoints, benchmarked for semantic drift rather than size alone.