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 Research, under the supervision of Toan Tran and Dinh Phung.

Research Interests [Research Statement]: Uncertainty and Robustness in Machine Learning.

Publications

Reinforcement Learning for Sequential Resource Allocation in Healthcare [short slides, INFORMS slides] Ha Manh Bui, Felix Parker, Kimia Ghobadi, Angie Liu on-going, 2025

Calibrated Uncertainty Sampling for Active Learning [PDF] Ha Manh Bui, Iliana Maifeld-Carucci, Anqi Liu under-review, 2025

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, slides, poster, 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, slides, poster, Colab demo, code, BibTex] Ha Manh Bui, Anqi Liu International Conference on Artificial Intelligence and Statistics, 2024

Benchmark for Uncertainty & Robustness in Self-Supervised Learning [PDF, article, code, BibTex] Ha Manh Bui, Iliana Maifeld-Carucci arXiv pre-print, 2022

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