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

IBM Outstanding Technical Achievement Award (2026): For NL2Insights Impacting Products and Clients
#1 on BIRD Leaderboard (2024): IBM Granite Text-to-SQL models achieved first place in both tracks, outperforming GPT-4 and GPT-4o
NL2Insights Production Impact: 200,000+ SQL queries generated across 1,000+ databases, powering watsonx.data, BI Assistant, and Process Mining
Multilingual Text2SQL (2026): Enabled production deployment across all IBM Cloud and AWS regions
6 IBM Awards (2024-2026): Two Outstanding Technical Achievement Awards, Growth Award, and multiple Research Accomplishments

W. Ma, D. Bhattacharjya, J. Lee, N. H. Pham, H. Kokel, Q. Ji. 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, 2026.

W. Chen, N. H. Pham, M. Glass, L. Vu, G. Rossiello, D. Subramanian, S. Paternain. ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning. NeurIPS 2025 Workshop on Efficient Reasoning, 2025.
G. Rossiello, N. H. Pham, M. Glass, J. Lee, D. Subramanian. Rationalization Models for Text-to-SQL. ICLR 2025 Workshop on Reasoning and Planning for LLMs, 2025. [Preprint]
Q. Xiao, D. Bhattacharjya, B. Ganesan, R. Marinescu, K. Mirylenka, N. H. Pham, M. Glass, and J. Lee. The Consistency Hypothesis in Uncertainty Quantification for Large Language Models. Proceedings of the Forty-First Conference on Uncertainty in Artificial Intelligence (UAI), 2025.

N. H. Pham, L. M. Nguyen, J. Chen, H. T. Lam, S. Das, T. W. Weng. Evaluating Robustness of Cooperative MARL: A Model-based Approach. 2023 IEEE International Conference on Data Mining (ICDM), pp. 1271-1276, Shanghai, China, 2023. [Paper]

Q. Tran-Dinh, N. H. Pham, D. T. Phan, and L. M. Nguyen. FedDR–Randomized Douglas-Rachford Splitting Algorithms for Nonconvex Federated Composite Optimization. The 35th Conference on Neural Information Processing Systems (NeurIPS), 2021. [Preprint]
D. T. Phan, L. M. Nguyen, P. Murali, N. H. Pham, H. Liu, J. Kalagnanam. Regression Optimization for System-level Production Control. American Control Conference (ACC), 2021.
Q. Tran-Dinh, N. H. Pham, D. T. Phan, and L. M. Nguyen. A Hybrid Stochastic Optimization Framework for Composite Nonconvex Optimization. Mathematical Programming, 2021. [Paper]

Q. Tran-Dinh, N. H. Pham, and L. M. Nguyen. Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization. The 37th International Conference on Machine Learning (ICML), 2020. [Preprint] [Python Code]
N. H. Pham, L. M. Nguyen, D. T. Phan, and Q. Tran-Dinh. ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization. Journal of Machine Learning Research, 21:110, 1-48, 2020. [Preprint] [Python Code]
N. H. Pham, L. M. Nguyen, D. T. Phan, P. H. Nguyen, M. van Dijk, and Q. Tran-Dinh. A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement Learning. The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. [Preprint] [Python Code]

H. M. La, T. H. Dinh, N. H. Pham, Q. P. Ha, and A. Q. Pham. Automated Robotic Monitoring and Inspection of Steel Structures and Bridges. Robotica, Cambridge University Press, 1-21, 2018.
T. D. Le, S. Gibb, N. H. Pham, H. M. La, L. Falk, and T. Berendsen. Autonomous Robotic System using Non-Destructive Evaluation methods for Bridge Deck Inspection. IEEE International Conference on Robotics and Automation (ICRA), May 2017, Singapore. [Preprint]
N. H. Pham and H. M. La. Design and Implementation of an Autonomous Robot for Steel Bridge Inspection. 54th Annual Allerton Conference on Communication, Control, and Computing, Sept. 2016, Urbana-Champaign, IL. [Preprint]
N. H. Pham, H. M. La, Q. P. Ha, S. N. Dang, A. H. Vo, and Q. H. Dinh. Visual and 3D Mapping for Steel Bridge Inspection Using a Climbing Robot. 33rd International Symposium on Automation and Robotics in Construction and Mining (ISARC), July 2016, Auburn, AL. [Preprint]
T.-D. D. Phan, N. H. Pham, K.-N. Le-Huu, and A.-V. D. Dinh. Quadrotor Helicopter: A Practical Design Approach. IEICE International Conference on Integrated Circuits, Design and Verification, pp. 156-163, 2013, Ho Chi Minh, Vietnam.

T. T. Doan, L. M. Nguyen, N. H. Pham, and J. Romberg. Convergence Rates of Accelerated Markov Gradient Descent with Applications in Reinforcement Learning. arXiv:2002.02873, 2020 [Preprint]
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, 2020 [Preprint]