This year, I am working with the team Taara at Google X as a PhD resident to come up with agile solutions for diverse problems using ML techniques. The main focus is to build predictive models and causal inference models using time-series data.

This Fall, I will be at Simons Institute as a visiting scholar to participate in the Data-driven Decision Processes workshop.

This Summer, I had an opportunity to work with a research team at Amazon AWS to develop differentially private algorithms for SageMaker. This work has been published in NeurIPS 2022 Workshop on Trustworthy and Socially Responsible Machine Learning (TSRML). https://www.amazon.science/publications/differentially-private-gradient-boosting-on-linear-learners-for-tabular-data-analysis

I was invited to a class, Design for Impact, at the Industrial Design Department at Rhode Island School of Design. The presentation was about how designers’ creativity could contribute to the era of artificial intelligence.

Our work on predicting the NBA game scores and the player’s performance (annual and game-level) using the synthetic control method was presented at the 2019 MIT Sports Summit.  

City Robotics Group in the MIT Media Lab held a design•a•hack•a•thon in collaboration with US San Diego Design Lab. The theme was designing a socially intelligent system for the future city mobility. My team designed a bicycle helmet that can work as a platform for V2V interaction in the future. With an optimistic mindset towards the…

In the novel A Christmas Carol, Scrooge is visited by ghosts showing his future that he will meet with a tragic end if he continues to be cold and miserly. After then, the imagination of future self transforms him into a changed man. We are to adopt this usefulness of imagining the future to help…