About Me
I am currently a Postdoctoral Fellow at Department of Computer Science of Johns Hopkins University, working with Prof. Suchi Saria. I graduated with my Ph.D. at University of Texas at Austin, where I was associated with IDEAL, WNCG and IFML. I was fortunate to be advised by Prof. Joydeep Ghosh. I got my Bachelor’s degree in electronics and eletrical engineering from The University of Edinburgh in 2017.
Research Interests
I am boardly interested in developing principles and practice of trustworthy machine learning. Specifically, I have been focused on the following research topics
- Uncertainty quantification: to better capture the epistemic uncertainty in common predictive modeling and classification problems.
- Robustness: to strengthen the model’s defense on adversarial attack, data poisoning and distribution drift, and construct certified robustness to provide safety guarantee via statistical modeling and optimization methods.
- Interpretability: to build human understandable explanations for model decisions, with particular focus on non i.i.d. data such as time series or sequential data.
Besides, I’m also interested in enhancing the predictive power of deep learning models in clinical contexts.
Recent News
- (9/22/23) One paper accepted to NeurIPS 2023.
- (9/1/23) Started my appointment as a Postdoctoral Fellow in Johns Hopkins.
- (7/17/23) Finished my PhD journey at UT!
- (5/23/23) I will start working with Prof. Suchi Saria as a Postdoctoral Fellow!
- (5/31/22) Started my internship at Google.
- (5/15/22) One paper accepted to ICML 2022.
- (2/1/22) Successfully passed my qualifying exam, and now become a Ph.D. candidate!
- (1/22/21) One paper accepted to AISTATS 2021.
- (9/25/20) One paper accepted to NeurIPS 2020 as a spotlight presentation.
Professional Experience
- Research Intern, Google. 5/22 - 9/22.
- Research Intern, Intuit AI. 6/21 - 9/21.
- R&D Intern, Salesforce. 6/20 - 8/20.
- Applied Scientist Intern, CognitiveScale. 5/18 - 8/18.
Service
- Conference reviewer: ICML 2021 - 2023; NeurIPS 2020 - 2023; ICLR 2020 - 2024; AISTATS 2021 - 2024; ICASSP 2024; ML4H 2023
- Journal reviewer: Pattern Recognition.