Hi! I am a PhD student at National University Of Singapore. I am doing my thesis with Prateek Saxena. My current focus is to design differentially private machine learning algorithms, especially on graphs, that enable end applications such as node classification and recommendations. I like building usable private technologies in general. I opine that rigourous user privacy and monetizing users’ data can and should co-exist.
I have experience in program analysis, synthesis, debugging and security of blockchains.
I was fortunate to work with two exciting companies, Flipkart India and Aqilliz. Flipkart India (now owned by Walmart) gave me an opportunity to work on their anomaly detection engine. Aqilliz is an exciting startup from Singapore where I had a chance to demonstrate the impact of applying Differential Privacy protection on the utility of widely-used queries like recommendations.
My interests range widely from Computer Science to Psychology, Astronomy, Music, Cricket and Animals. I love singing and relish performing almost anything on a stage(of course after practicing….). I will probably stay in Singapore for at least another three years, so, If you are here then feel free to drop by and say hoi.
|Aug 28, 2022||[New!] Our paper on new graph neural network architetures, LPGNet, that provide privacy for edges got accepted to CCS’22.|
|Jul 21, 2021||Our paper on private hierarchical clustering in federated networks got accepted to CCS’21.|
|Jun 21, 2021||Our paper on fault localization using a single exploit got the best paper award at AsiaCCS’21!|
|May 22, 2021||Our paper on guaranteeing generalization for PBE-based program synthesis tools got accepted to FSE’21.|
|Oct 25, 2020||Our paper got accepted to AsiaCCS’21. Here is the link|