Thien Hang Nguyen

About me

I am a Member of Technical Staff (Research) at Contextual AI, working on agentic search and information retrieval.

I completed my Ph.D. in March 2025 at Khoury College of Computer Sciences at Northeastern University, where I started the Fall of 2020 and was very fortunate to be advised by Huy Le Nguyen. There, I worked on optimization and machine learning, which is the topic of my Thesis.

Before Khoury, I graduated from University of California, Irvine in 2020 with a B.S. in Computer Science and Engineering and a B.S. in Mathematics. In the Summer of 2019, I worked with Andrea Bertozzi at UCLA's REU program in Computational and Applied Mathematics.

Papers

* denotes equal contribution

  1. ExtractBench: A Benchmark and Evaluation Methodology for Complex Structured Extraction

    Nick Ferguson, Josh Pennington, Narek Beghian, Aravind Mohan, Douwe Kiela, Sheshansh Agrawal, and Thien Hang Nguyen.
    In Submission. 2026.
    [code]

  2. BLITZRANK: Principled Zero-shot Ranking Agents with Tournament Graphs

    Sheshansh Agrawal*, Thien Hang Nguyen*, and Douwe Kiela.
    In Submission. 2026.
    [code] [website]

  3. Lean and Mean Adaptive Optimization via Subset-Norm and Subspace-Momentum with Convergence Guarantees

    Thien Hang Nguyen and Huy Le Nguyen.
    International Conference on Machine Learning, Vancouver. 2025.
    [code]

  4. Memory Efficient Adaptive Stochastic Optimization via Subset-Norm

    Thien Hang Nguyen and Huy Le Nguyen.
    Optimization for Machine Learning Workshop at NeurIPS, Vancouver, 2024.

  5. Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise

    Duy Nguyen*, Thien Hang Nguyen*, Alina Ene, and Huy Le Nguyen.
    Neural Information Processing Systems, New Orleans. 2023. [Spotlight]

  6. High Probability Convergence of Clipped-SGD Under Heavy-tailed Noise

    Duy Nguyen*, Thien Hang Nguyen*, Alina Ene, and Huy Le Nguyen.
    Preprint. 2023.

  7. High Probability Convergence of Stochastic Gradient Methods

    Zijian Liu*, Duy Nguyen*, Thien Hang Nguyen*, Alina Ene, and Huy Le Nguyen.
    International Conference on Machine Learning, Honolulu. 2023.

  8. META-STORM: Generalized Fully-Adaptive Variance Reduced SGD for Unbounded Function

    Zijian Liu*, Duy Nguyen*, Thien Hang Nguyen*, Alina Ene, and Huy Le Nguyen.
    Preprint. 2023.

  9. Improved Group Robustness via Classifier Retraining on Independent Splits

    Thien Hang Nguyen, Hongyang Zhang, and Huy Le Nguyen.
    Transactions on Machine Learning Research. 2023.
    [code]

  10. Structural Equivalence in Subgraph Matching

    Dominic Yang, Yurun Ge, Thien Hang Nguyen, Denali Molitor, Jacob D. Moorman, and Andrea L. Bertozzi.
    IEEE Transactions on Network Science and Engineering. 2022.

  11. Applications of Structural Equivalence to Subgraph Isomorphism on Multichannel Multigraphs

    Thien Hang Nguyen, Dominic Yang, Yurun Ge, Hao Li, and Andrea Bertozzi.
    IEEE Big Data Conference, Los Angeles. Dec 9, 2019. [Oral Presentation]

Blogs