Ha Manh Bui

Hi! I am a Ph.D. Student in Computer Science at Johns Hopkins University, advised by Angie Liu. Prior to that, I was at VinAI and obtained a B.S.E. in Information Technology from PTIT-Hanoi, under the supervision of Toan Tran and Dinh Phung.

Research Interests: I want to develop Trustworthy Artificial Intelligence (AI) systems that can support people in high-stakes applications (e.g., forecasting, healthcare, finance, etc.). Pursuing this goal, my research focuses on enhancing the efficiency, uncertainty, and robustness of Machine Learning (ML) models for sequential decision problems.

Publications

Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits [PDF, article, Colab demo, code, BibTex] Ha Manh Bui, Enrique Mallada, Anqi Liu International Conference on Artificial Intelligence and Statistics, 2025

Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts [PDF, article, talk, Colab demo, code, BibTex] Ha Manh Bui, Anqi Liu International Conference on Machine Learning, 2024

Density-Regression: Efficient and Distance-Aware Deep Regressor for Uncertainty Estimation under Distribution Shifts [PDF, article, talk, Colab demo, code, BibTex] Ha Manh Bui, Anqi Liu International Conference on Artificial Intelligence and Statistics, 2024

Exploiting Domain-Specific Features to Enhance Domain Generalization [PDF, article, talk, code, BibTex] Manh-Ha Bui, Toan Tran, Anh Tran, Dinh Phung Advances in Neural Information Processing Systems, 2021