Research
Research Interest
- Large Language Models (LLMs) for enterprise data management applications, particularly Text-to-SQL systems
- Stochastic optimization methods for machine learning, deep learning, and reinforcement learning
- Multi-agent reinforcement learning and robustness evaluation
- Federated learning and distributed optimization
Publications
The Consistency Hypothesis in Uncertainty Quantification for Large Language Models
Forty-First Conference on Uncertainty in Artificial Intelligence (UAI 2025)
Q. Xiao, D. Bhattacharjya, B. Ganesan, R. Marinescu, K. Mirylenka, N. H. Pham, M. Glass, and J. Lee
Evaluating Robustness of Cooperative MARL: A Model-based Approach
2023 IEEE International Conference on Data Mining (ICDM)
N. H. Pham, L. M. Nguyen, J. Chen, H. T. Lam, S. Das, T. W. Weng
FedDR–Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization
The 35th Conference on Neural Information Processing Systems (NeurIPS 2021)
Q. Tran-Dinh, N. H. Pham, D. T. Phan, and L. M. Nguyen
Regression Optimization for System-level Production Control
2021 American Control Conference (ACC)
D. T. Phan, L. M. Nguyen, P. Murali, N. H. Pham, H. Liu, J. Kalagnanam
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
The 37th International Conference on Machine Learning (ICML 2020)
Q. Tran-Dinh, N. H. Pham, and L. M. Nguyen
[Python Code]
A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning
The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)
N. H. Pham, L. M. Nguyen, D. T. Phan, P. H. Nguyen, M. van Dijk, and Q. Tran-Dinh
[Python Code]
Autonomous Robotic System using Non-Destructive Evaluation methods for Bridge Deck Inspection
IEEE International Conference on Robotics and Automation (ICRA)
T. D. Le, S. Gibb, N. H. Pham, H. M. La, L. Falk, and T. Berendsen
Design and Implementation of an Autonomous Robot for Steel Bridge Inspection
54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
N. H. Pham and H. M. La
Visual and 3D Mapping for Steel Bridge Inspection Using a Climbing Robot
33rd International Symposium on Automation and Robotics in Construction and Mining (ISARC)
N. H. Pham, H. M. La, Q. P. Ha, S. N. Dang, A. H. Vo, and Q. H. Dinh
A Hybrid Stochastic Optimization Framework for Composite Nonconvex Optimization
Mathematical Programming (Math. Program)
Q. Tran-Dinh, N. H. Pham, D. T. Phan, and L. M. Nguyen
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization
Journal of Machine Learning Research (JMLR)
N. H. Pham, L. M. Nguyen, D. T. Phan, and Q. Tran-Dinh
[Python Code]
Automated Robotic Monitoring and Inspection of Steel Structures and Bridges
Robotica
H. M. La, T. H. Dinh, N. H. Pham, Q. P. Ha, and A. Q. Pham
Black-Box Uncertainty Quantification for Large Language Models via Ensemble-of-Ensembles
AAAI 2026 Workshop on Assessing and Improving Reliability of Foundation Models in the Real World (AAAI 2026 Workshop)
W. Ma, D. Bhattacharjya, J. Lee, N. H. Pham, H. Kokel, Q. Ji
ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning
NeurIPS 2025 Workshop on Efficient Reasoning (NeurIPS 2025 Workshop)
W. Chen, N. H. Pham, M. Glass, L. Vu, G. Rossiello, D. Subramanian, S. Paternain
Rationalization Models for Text-to-SQL
ICLR 2025 Workshop on Reasoning and Planning for LLMs (ICLR 2025 Workshop)
G. Rossiello, N. H. Pham, M. Glass, J. Lee, D. Subramanian
Convergence Rates of Accelerated Markov Gradient Descent with Applications in Reinforcement Learning
arXiv:2002.02873
T. T. Doan, L. M. Nguyen, N. H. Pham, and J. Romberg
Finite-Time Analysis of Stochastic Gradient Descent under Markov Randomness
arXiv:2003.10973
T. T. Doan, L. M. Nguyen, N. H. Pham, and J. Romberg