Bio

I am a research assistant at Monash University Malaysia. The center of my work is mathematical modelling, especially where it meets learning, decision-making, finance, and environmental systems.

I work on multi-agent reinforcement learning, market microstructure, and quantitative finance, but I do not think of those as isolated topics. I treat them as different settings in which modelling assumptions, information constraints, and regime structure determine what a system can actually learn or control.

The questions that keep showing up in my work are simple to state. What information does an agent actually need in order to act well? When does a change in regime matter more than a change in method? When does prediction improve control, and when does it only create the appearance of sophistication?

I am also building stronger foundations in stochastic modelling and environmental modelling. That is still an active direction of study rather than a finished claim to expertise, and I want to state that directly. It matters because I want my research record to connect reinforcement learning and finance to more classical modelling questions, including environmental systems and current wastewater treatment plant research.

I hold a BSc. (Hons) in Applied Mathematics with Computing from UTAR. Alongside formal research, I keep a running notebook of derivations, clarifications, and working explanations in statistics, regression, optimization, and reinforcement learning.

This site collects notes, essays, publications, and smaller technical artifacts around that line of work.