Hy Dang

Hy Dang

Ph.D Student in Computer Science & Engineering

About me

I am a forth-year (2022-now) Ph.D student in Computer Science and Engineering at Notre Dame, and work in DM2 Lab directed by Prof. Meng Jiang. My research interests lie in the fields of Natural Language Processing and Data Mining.

I received double degrees Bachelor of Science in Computer Science and Bachelor of Science in Mathematics from Texas Christian University in December 2021.

I have not failed. I’ve just found 10,000 ways that won’t work.… –Thomas A. Edison

⭐ Recent News

📄 Aug, 2025LLM Function Calling with Templates (Work done during Amazon Internship) accepted at EMNLP 2025 Main.
📄 May, 2025DYDECOMP paper accepted at ACL 2025 Main.
🎉 Aug, 2024Happy to announce that I will join Amazon as Applied Scientist Intern starting in September! See everyone in Palo Alto soon!
📄 May, 2023Community Recommendation Using Mental Helath Discourse Paper accepted at CODI 2023 - ACL 2023
🎓 Aug, 2022Joined University of Notre Dame as a PhD student in Computer Science & Engineering under the supervision of Prof. Meng Jiang. Go Irish ☘️.
🎓 Dec, 2021Graduated with 4.0 GPA (Summa Cum Laude) with double degrees in Computer Science and Mathematics from Texas Christian University.

📃 Publications

Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates thumbnail

Improving Large Language Models Function Calling and Interpretability via Guided-Structured Templates

Hy Dang, Tianyi Liu, Zhuofeng Wu, Jingfeng Yang, Haoming Jiang, Tao Yang, Pei Chen, Zhengyang Wang, Helen Wang, Huasheng Li, Bing Yin, Meng Jiang ·
EMNLP 2025
Project Page Paper
Optimizing Decomposition for Optimal Claim Verification thumbnail

Optimizing Decomposition for Optimal Claim Verification

Yining Lu, Noah Ziems, Hy Dang, Meng Jiang ·
ACL 2025
Paper
Embedding Mental Health Discourse for Community Recommendation thumbnail

Embedding Mental Health Discourse for Community Recommendation

Hy Dang*, Bang Nguyen*, Noah Ziems, Meng Jiang ·
CODI-ACL 2023
Project Page Paper arXiv
A Quantitative Review on Language Model Efficiency Research thumbnail

A Quantitative Review on Language Model Efficiency Research

Meng Jiang, Hy Dang, Lingbo Tong ·
Preprint
arXiv

📧 Contact

I’m best reached via email. I’m always open to interesting conversations and collaboration.

  • Email: hdang [at] nd [dot] edu
  • Office: 355 Fitzpatrick Hall of Engineering
  • Location: University of Notre Dame, Notre Dame, IN 46565