About Me

I’m an Applied Scientist at Amazon AWS. My research convers a wide range of topics in natural language processing and machine learning. Recently, my work has been focused on the application of large language models in the medical domain. My long-term objective is to pave the way for robust and deployable LLM applications.

I got my Ph.D. in Computer Science from MIT in 2023, and B.Eng. from Tsinghua University.

News

Jul. 2023: AWS Announces HealthScribe Service.
Feb. 2023: I joined Amazon AWS as an applied scientist.

Selected Projects

Robustness of Text Classifiers

With deployment of large language models, the security and robustness of these models have become a real issue. In this project, we thoroughly explore how well text classifiers can handle attacks from different angles. We developed R&R and SP-Attack for traditional transformer-based text classifiers. We also proposed AToP/BToP attacks for prompt-based language models. And we’re putting effort into defending against these attacks with In Situ Augmentation.

Synthetic Tabular Generation

In this project, we aim to generate synthetic tabular data, which can help remove the barriers in data sharing. We started with an LSTM-based TGAN model, then further improved it by proposing CTGAN.