Born in India and Grew up in Singapore • Studied Mathematics and Computer Science at Caltech • PhD in Computer Science from MIT • Lives in California, USA • Postdoctoral Researcher at NTT Research, USA
What first drew me to mathematics wasn’t numbers or formulas – it was the satisfaction of knowing why something was true. I loved puzzles and logic problems from an early age, and my parents noticed. I was extremely fortunate because they did their best to find the support I needed to keep exploring that interest and progress in the math Olympiad scene. I later represented Singapore several times in the China Girls’ Mathematical Olympiad. Those experiences drew me in. I loved the structure of Olympiad problems – the feeling that, with enough persistence, all the puzzle pieces would eventually fit. But what fascinated me most was the idea of a proof. Proofs were like perfectly tuned explanations: elegant, inevitable, and deeply satisfying. I remember learning how to write one and being amazed that something as human as convincing someone of something could be captured by precise logic.
For example, is solving a Sudoku puzzle as easy as checking that a completed Sudoku grid is valid?
During my undergraduate studies at California Institute of Technology, I learned that the idea of “proofs” also lies at the heart of theoretical computer science. I encountered the seminal P vs NP problem, which asked whether “finding a proof” (NP) is as easy as “verifying a proof” (P). For example, is solving a Sudoku puzzle as easy as checking that a completed Sudoku grid is valid? On the face of it, the former seems much more difficult – but for all we know, both tasks could be equally “easy” (i.e. NP = P). This is one of the biggest unsolved mysteries in theoretical computer science, and it drew me in with the deep mathematical ideas that had been developed to understand it. I soon decided to pursue a joint major in mathematics and computer science to explore that theory more deeply.
I could not stop thinking about this, how much can we push the limits of what a proof can look like?
Later, I took a cryptography class that introduced a concept called zero-knowledge proofs, which changed the way I viewed proofs. Proofs didn’t have to be static write-ups – they could be interactive, even conversational in some sense. With this relaxation, zero-knowledge formalized the idea of convincing someone that something is true without revealing why. For example, you could prove that you know a solution to a Sudoku without giving away the solution itself. It seemed absurd, but it was possible. I could not stop thinking about this, how much can we push the limits of what a proof can look like?
I also had the first taste of pursuing mathematics research during my time at Caltech. It was the first time mathematics felt creative rather than competitive. I had to decide for myself what questions to ask and what counted as progress. It was the first time I’d worked on something where there wasn’t a clear notion of “done.” I enjoyed the freedom that I had to choose where I wanted the project to go. I was motivated to keep doing this, and I decided to pursue a PhD in theoretical computer science.
During my PhD at MIT, I explored more problems in theoretical computer science, and landed on a problem that I am still obsessed with: constructing succinct proofs. Like zero knowledge, succinct proofs redefine what a “proof” can look like, but in a different way – they capture the idea that you can convince someone of a complex statement using a proof that is much shorter than the statement itself. For example, could we prove that a 100 x 100 Sudoku has a solution by providing a proof containing only 128 bits, instead of 10,000? At first, this seemed completely ridiculous. How could a proof possibly be shorter than the thing it proves? It shouldn’t even be possible. But instead of assuming an all-powerful prover, if we assume the prover has limited resources, say finite time – then it actually might be.
While I was at MIT, I had the privilege of being mentored by several incredible female professors whose sharpness and confidence quietly shifted how I saw myself.
That tension between truth and feasibility made me appreciate the “engineering” side of theoretical cryptography: sometimes the goal isn’t to prove that something exists unconditionally, but to show that it can exist within realistic limits. And one doesn’t need to stop there – one could also ask for a proof to be both succinct and zero-knowledge simultaneously! Indeed, succinct zero-knowledge proofs (sometimes called zk-proofs or zk-SNARKs) are now the backbone of blockchains, allowing large computations to be verified efficiently while maintaining privacy.
Representation shapes what seems possible, even when no one says it out loud. I feel so incredibly lucky to have crossed paths with these incredible women.
While I was at MIT, I had the privilege of being mentored by several incredible female professors whose sharpness and confidence quietly shifted how I saw myself. Watching them made it feel more plausible that I could be a researcher or academic too. Earlier in my life, during the Math Olympiad or even at Caltech, I was often one of the few girls in the room. At the time, I didn’t think much of it, but looking back, I realize how much visibility matters. Representation shapes what seems possible, even when no one says it out loud. I feel so incredibly lucky to have crossed paths with these incredible women.
Perhaps my favourite thing about doing research is that unlike Olympiad math, it doesn’t exist in a vacuum – research is deeply conversational. I’ve learned that sharing half-formed thoughts – defending, revising, and rebuilding them – is often how the most enjoyable mathematics happens. Each discussion shifts how you see the problem, and sometimes that’s enough to move it forward. I’ve also come to enjoy the part that happens after the proof is done. I enjoy giving talks, explaining the ideas to others, and seeing how they react. Good talks feel like an extension of research itself: a chance to start a conversation about mathematical ideas.
I am now a postdoctoral researcher at NTT Research, a research lab based in California. I still work on constructing zero-knowledge succinct proofs and other related cryptography problems. Even though I work on theoretical computer science, by an ironic turn of events, much of my recent work uses traditional mathematical proofs to construct succinct proofs in the cryptographic sense. I am excited to see where else my research leads me. I hope to go into academia, where I can study these problems further. I hope that being here and doing this work helps make the field feel a little more possible for others who might not have seen themselves in it before.
Published on December 10, 2025.
Photo credit: Asaf Etgar
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