Ziyan An
Vanderbilt University, Department of Computer Science. 1025 16th Ave S, Nashville, TN 37212
(863) 303-2399
ziyan.an AT vanderbilt DOT edu
I am a fourth-year Ph.D. student in Computer Science at Vanderbilt University, where I have been awarded the Dean’s Graduate Fellowship. I am very fortunate to have the guidance and mentorship of Prof. Meiyi Ma as my advisor.
My primary research interest lies in the design of AI-based systems that integrate formal specifications and leverage prior knowledge. By combining these elements, I aim to develop advanced AI solutions that are more robust, reliable, explainable, and capable of addressing real-world challenges effectively. Another central theme of my work is enhancing the explainability of AI-driven decisions, ensuring that complex systems remain transparent and trustworthy to the people who rely on them.
Prior to joining Vanderbilt University, I earned my B.S. in Computer Science from New York University. During my academic journey, I had the invaluable opportunity to intern at Sunthetics, UiPath, and Uber as an AI and Machine Learning software engineer. Additionally, I was an undergraduate research assistant at AI4CE Lab at NYU, under the mentorship of Prof. Chen Feng, where I worked on projects in computer vision.
Publications
A selection of representative publications. See the full list of publications for all of my work.
- LogiEx: Integrating Formal Logic and LLMs for Explainable Transit PlanningIn Proceedings of the 17th ACM/IEEE International Conference on Cyber-Physical Systems 2026
- Multi-agent reinforcement learning guided by signal temporal logic specificationsIn 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems 2025
- Combining LLMs with Logic-Based Framework to Explain MCTSIn The 24th International Conference on Autonomous Agents and Multi-Agent Systems 2025
- Formal Logic-Guided Harnessing Heterogeneous Fairness Rules in Smart CitiesACM Transactions on Cyber-Physical Systems 2025
- ISL: Monitoring Image Segmentation Logic in Medical Imaging AnalysisIn International Conference on Runtime Verification 2025
- Formal Logic Enabled Personalized Federated Learning Through Property InferenceIn Proceedings of the AAAI Conference on Artificial Intelligence 2024
- Runtime monitoring of accidents in driving recordings with multi-type logic in empirical modelsIn International Conference on Runtime Verification 2023
- V2X-Sim: Multi-agent collaborative perception dataset and benchmark for autonomous drivingIEEE Robotics and Automation Letters 2022