Chih-Duo Hong

Chih-Duo Hong

Assistant Professor at NCCU

I’m an Assistant Professor with the Department of Management Information Systems at National Chengchi University (NCCU) in Taiwan. Before my journey at NCCU, I had the opportunity to work as a postdoctoral researcher at Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU) in Germany. I earned my DPhil/PhD from the University of Oxford and completed my MSc and BSc at National Taiwan University.

Research Interests

I’m passionate about making software systems safe for everyone! My work involves employing formal and mathematical methods to gain insights and verify how systems behave, especially those made up of numerous similar components. I love using techniques from formal verification and logic to explore this fascinating field. Below, I’ve outlined the main areas I focus on:

  • Verification and testing of software and AI systems
  • Model checking and automated generation of proofs and programs
  • Automated reasoning about modal and temporal logic

I would love to supervise PhD, MSc, or BSc students interested in studying these topics. If you have an exciting project in mind, don’t hesitate to email me so we can chat more about it!

🚀 To new graduate students 🚀

Welcome aboard! Our lab’s research theme in 2025-2027 is the synergy between AI (e.g., neural networks and LLMs) and automated software engineering (e.g., program analysis and testing). Feel free to contact me if you’d like to explore this fascinating research area in your master’s program!

News

7.12.2024. A big congratulations to Ming-I Huang for winning the Best English Paper Award in the 20th Taiwan Conference on Software Engineering!

Services

Recent Publications

  • Ming-I Huang, Chih-Duo Hong, and Fang Yu, “Concolic Testing on Individual Fairness of Neural Network Models,” Journal of Information Science and Engineering, 2025. To appear. (preprint)
  • Chih-Duo Hong and Anthony Lin, “Regular Abstractions for Array Systems,” Proceedings of the ACM on Programming Languages (POPL), 2024. (arxiv)

For a complete list, please see my Google Scholar.

Manuscripts

  • Chih-Duo Hong, Hongjian Jiang, Anthony Widjaja Lin, Micha Schrader, Oliver Markgraf, Tony Tan, “Learning and Interpreting Register Automata.” Under review.
  • Chih-Duo Hong, Anthony W. Lin, Philipp Rümmer, Rupak Majumdar, “Probabilistic Bisimulation for Parameterized Anonymity and Uniformity Verification.” Under review.
  • Fang Yu, Chih-Duo Hong, Ya-Yu Chi, Yu-Fang Chen, “Constraint-Based Adversarial Example Synthesis for Neural Network Models.” Under review.

Teaching

Projects

Adversarial example generation for neural networks

Fairness verification of neural networks

Regular abstraction