Experience
Product Manager: coordinates an eight-person team, maintains the product backlog, and runs delivery for multi-chain crypto payment and wallet infrastructure.
Independent Consultant & Product Manager: business transformation, Web3 product management, proprietary AI research, and data/ML training
Contractor: Business Transformation Consultant
Contractor: Data Science & Machine Learning Trainer
Research Assistant
Finance Analyst - Data Engineer Intern
Education
BSc (Hons), First Class Honours · Applied Mathematics with Computing
Foundation · Science
Awards
Top 12
Future Founder Award, Top 15 Finalist
Mentor
Best Visualisation Award
Consolation Prize
Top 13 Finalist
Best Presenter
Participant
4th runner-up
Best Presenter Award, Best Team Award
Semi-finalist
Finalist
Certifications
Grants
Undergraduate scholarship awarded by the Kuok Foundation.
Study grant awarded by the HuaZong Education Fund.
Scholarship awarded by the KIT Foundation.
Merit-based tuition scholarship for academic performance at UTAR.
Merit-based tuition scholarship for the UTAR Foundation programme.
Open Source
Details
Added type annotations to sympy.utilities.exceptions, covering SymPyDeprecationWarning, sympy_deprecation_warning and ignore_warnings. The patch uses a TYPE_CHECKING guard to keep collections.abc out of the runtime import path. It was reviewed and merged into SymPy master.
Volunteering
Mentored participating teams and judged project submissions.
Mentored student teams throughout the hackathon.
Memberships
Member of the Kuok Foundation scholars community.
Publications
Abstract
Satellite rainfall products are often evaluated with gauges that sample different periods and spatial supports. We assessed daily IMERG Final V07 rainfall over Malaysia from October 2015 to September 2025, separating regional rainfall patterns from gauge-footprint and gauge-to-footprint effects. IMERG can screen regional rainfall patterns, but local high-intensity verification remains gauge-dependent.
Abstract
A full-factorial experiment in the Public Goods Game shows that information regime and incentive strength explain 85.8% of cooperation-rate variance; algorithm choice accounts for just 3.8%. Agents with the least information cooperate most (83% versus 42% under full observation), attributable to state-space compression. TreeSHAP and Shapley-variance decomposition confirm information structure, not algorithm selection, as the primary design lever for cooperation.
Abstract
Studies optimal trade execution strategies that incorporate predictive alpha signals, bridging market microstructure theory with practical quantitative trading.