My first win came froma pill box.
In my first year at NUS I led Team LightBox at Create4Good: a pill box that knows when it has been opened, and an app that lets a family see it. We built it for elderly users and the people who worry about them, then stood in front of judges and investors to make the case. We beat teams from France and Madagascar — the first time I watched something I built land with a room.
And then,another first place.
The Asian Business Plan Competition put us in a room with teams from NUS, HKUST and NTHU, pitching to regional judges and VCs. Our idea was FidusRide: a way for car-sharing operators to keep fleets clean and disputes fair. What I loved most was the team — software engineers working alongside aerospace engineers and finance people, each of us learning the others' language. We pitched to leading companies, took first place, and my teammates voted me MVP.
Winning showed mewho wasn't in the room.
The competitions were exciting, but I kept noticing how few women were on the stage with me. As Project Lead at NUS Women in Tech, I partnered with PayPal, UBS and Morgan Stanley to bring more than 200 female undergraduates into their offices — hackathons, code camps and spotlight days where the engineers presenting looked like the students listening. That work taught me that access is something you build, deliberately, the same way you build software. It's why I later founded NUS' first AWS-affiliated Cloud Club: a community for the students drawn to infrastructure, who had nowhere on campus to find each other.
My first productionsystem had 50+ sensors.
My first internship was at AquaShield, where 50+ IoT sensors send water-quality readings around the clock. I built the pipeline that carries them — Kafka to Redis to WebSockets — and the dashboards that turn them into something an operator can act on. I also built the internal tooling that cut our debugging time by 30%, which is where I learned that reliability is a feature. In between, PayPal's Pathways Program showed me how a fintech ships at scale.
A scam-reporting app,and my first LLM eval.
DSTA BrainHack was where I stopped treating AI as magic. We built an app and Telegram bot for reporting scams, and I wrote the pipelines that used Gemini to summarise and de-duplicate reports. The part that stayed with me was evaluation: learning to measure whether the model was actually right, and pushing it to 81% contextual precision. We made the finals.
Then I moved to New Yorkfor a year.
Through NUS Overseas College I joined Simulacra as a Full Stack Software & AI Engineer intern — an AI B2B SaaS startup building synthetic data for enterprises. We were a small team serving very large clients — Pernod Ricard, Ajinomoto, Walmart — across the US, France and Japan, and I worked with those clients directly. On a team that size there is no "frontend person": I built the admin panel and customer-facing product in React, the backend that enforced access and quotas, and the applied AI and data-science pipelines that benchmarked our synthetic data and cut manual validation work by 70%. It taught me that the fastest way to build the right thing is to sit in the room with the people who need it.
Now I work on the databehind blockchain security.
Today I'm a Software Engineer Intern on Binance's Infra, AI & Big Data team in Singapore. I write Spark SQL pipelines over Hive, Hudi and StarRocks, find the gaps and stale state in production ETL, and I'm building an LLM agent that turns messy incident reports into structured, source-backed risk signals. It's the largest data I've ever worked with, and the stakes are real.
Then I was askedto tell the story.
I was honoured to be invited by Professor Edward Tay to speak in postgraduate courses at NUS and share my journey — the wins, the internships, and what building things has taught me. I called the talk "My Three Whys": people-centredness, technology and its possibilities, and impact.