National University of Singapore
I'm an Assistant Professor in the School of Computing and the Institute of Data Science in National University of Singapore. My research aims to make machine learning systems more reliable and applicable to a wider variety of real-world contexts, particularly:
- Trustworthiness. How do we make models more reliable and factual, and more aware of what they don't know, mitigating issues like hallucination, distribution shift, and biases?
- Graphs and Structured Data. As foundation models are applied to increasingly diverse and multimodal tasks in our daily lives, they will increasingly encounter complex structured data such as graphs. How can foundation models enhance graph learning, such as for recommendation and e-commerce?
- Applications. I am also interested in some other real-world applications, particularly related to web safety (scams, fraud, and misinformation) and biomedical applications.
I received my Ph.D. in Machine Learning from Carnegie Mellon University, where I was advised by Christos Faloutsos. I received my M.S. in Computer Science and my B.S. in Mathematics from Stanford University.