About

I am a Senior Research Scientist at the Institute for Infocomm Research (I²R), specializing in multimodal large language models (LLMs). My research focuses on developing audio-text LLMs, as part of the National Multimodal LLM Programme.

My work also spans vision-language models, computer vision (particularly robustness and transfer learning), and time series prediction and anomaly detection. My broader research interest lies in advancing generalizable and trustworthy AI models for real-world applications.

I received my PhD in Statistics from Cornell University in 2020, advised by David Matteson, where I focused on anomaly and change detection. Prior to that, I earned my B.A. in Applied Mathematics and Statistics from UC Berkeley. My undergraduate and PhD studies were supported by the A*STAR National Science Scholarship (BS-PhD). I have also gained experience through research and industry internships at Amazon, MERL and IBM during my PhD.

For a full list of my publications, please refer to my Google Scholar profile.