I’m currently a Senior Research Scientist at the Institute for Infocomm Research, working on transfer learning and robustness in deep learning. I have also worked on online prediction and anomaly detection. I’m broadly interested in developing generalizable and trustworthy AI models.
I graduated with a PhD in Statistics at Cornell University in 2020, with advisor David Matteson. My PhD focus is on anomaly and change detection methods for time series.
My undergraduate study is at UC Berkeley in Applied Mathematics and Statistics. After which, I worked for a year at the Institute for Infocomm Research in Singapore. My undergraduate and PhD studies are supported by the A*STAR National Science Scholarship (BS-PhD). During my PhD, I also had research and industry internship stints.