I work at the intersection of Singapore housing-market research, geospatial analysis, policy interpretation, and analytical systems. My focus is on using data and methods to study how real estate markets function in practice.
My work is centered on Singapore's housing market: how prices move, how policy shapes behaviour, how location affects demand, and how analytical systems can make market behaviour easier to study.
I am most interested in questions that sit between empirical real estate research and technical execution. That includes housing-market analysis, geospatial methods, forecasting, policy interpretation, and the research infrastructure that turns raw transactions, financing conditions, and urban context into usable evidence.
This site brings those threads together as a record of research-oriented work, technical systems, and public-facing analysis built around real estate, market intelligence, and long-term academic questions.
I look at housing through incentives, data quality, financing conditions, transport access, and the practical frictions that shape buyer and seller behaviour.
That usually means combining transaction data, macro context, maps, policy interpretation, and system design instead of relying on a single chart or a single market story.
I use SQL, Python, dashboards, APIs, and automation to build repeatable research and operating systems rather than one-off analysis.
The output can take different forms: a case study, a dashboard, a media explainer, a geospatial tool, an internal workflow, or a recurring reporting pipeline. The common thread is that the work should clarify a decision, not just display data.
I am an incoming PhD student in Management (Real Estate) at the Department of Real Estate, NUS Business School, beginning in August 2026. That next phase is a natural extension of the direction this site has been moving toward: deeper work on housing markets, stronger analytical rigor, and a longer-term research agenda around property systems, urban dynamics, and market behaviour.
That direction sits naturally beside the systems side of my work. Both are ultimately about the same thing: taking fragmented, noisy systems and turning them into something clearer, more reliable, and more useful for decision making.
My recent professional work was shaped heavily by my time at Ohmyhome, where I worked across market research, geospatial analysis, automation, executive dashboards, compliance systems, digital marketing analytics, and decision-support for leadership. That period pushed me from broad analytics work into a much more specific focus on how housing markets and operational systems function in practice.
Earlier roles at Standard Chartered, Singtel Cyber Security, Jones Lang LaSalle, and the Singapore Police Force gave me a broader foundation across reporting, process improvement, governance, and business problem-solving. The through-line was always the same: reduce ambiguity, build better systems, and make decisions more defensible.
My background combines business, analytics, and management. I graduated from the University of Birmingham with First Class Honours in International Business and later completed a Master's degree in Analytics and Visualizations at the Singapore University of Social Sciences, where my research focused on using geospatial methods to improve real-estate price prediction in Singapore, working with approximately 1.5 million transaction rows.
That combination still shapes how I work now. I care about technical depth, but I care just as much about whether the output is actually usable by operators, managers, journalists, policymakers, or the public.
This site is becoming a record of the work I want to keep compounding over the long term: housing-market research, analytical systems, media commentary, technical infrastructure, and doctoral research. It is meant to show both the ideas and the machinery behind them.