Ph.D. Candidate in Computer Science | Vanderbilt University
Hello! My name is Zirong (Rex) Chen (陈子荣), currently pursuing a Ph.D. in Computer Science at Vanderbilt University under Professor Meiyi Ma's supervision. My research focuses on AI Safety and Trustworthy AI, with particular emphasis on Natural Language Processing (NLP), reliable AI systems for critical applications, and trustworthy AI-driven solutions for Smart Cities and emergency response. I earned my bachelor's degree (B.E. in Computer Engineering) in China and my master's degree (M.S. in Computer Science) at Georgetown University. I am also a former basketball player in high school and college.
PACE is a personalized adaptive curriculum engine that tailors 9-1-1 call-taker training to individual trainees. By modeling trainee proficiency and dynamically adjusting scenario difficulty, PACE delivers targeted practice that improves learning efficiency in safety-critical emergency response training.
Keywords: Adaptive Learning, Trustworthy AI, Safety-Critical Training
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We develop trustworthy AI systems that decompose LLM runtime into modularized function calls enhanced with Signal Temporal Logic, ensuring reliable and interpretable performance evaluation for safety-critical call-taking scenarios.
Keywords: Trustworthy AI, AI Safety, Reliable LLMs
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Collaborating with Metro Nashville Department of Emergency Communications, we develop Angie/SimER - a safety-critical AI system that provides reliable, trustworthy simulation environments for call-taker training in high-stakes emergency response scenarios.
Keywords: Safety-Critical AI, Trustworthy LLMs, Reliable Systems
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We develop reliable AI systems with built-in safety guarantees that enhance emergency response decision-making. Our trustworthy machine learning approaches ensure robust performance in critical situations while maintaining transparency and accountability.
Keywords: AI Safety, Trustworthy ML, Reliable Decision Systems
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The Adaptable City Knowledge project aims to create a dynamic, data-driven platform that helps cities respond to evolving challenges. From traffic management to disaster preparedness, this initiative fosters collaboration between city officials, businesses, and residents to promote resilience.
Keywords: AI/ML, NLP, Life-long Learning
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[IJCAI-26 / ECAI-26] PACE: A Personalized Adaptive Curriculum Engine for 9-1-1 Call-taker Training
[AAAI-26] (Oral Spotlight - 17.6%) Learning with Preserving for Continual Multitask Learning
[ICCPS-26] LogiEx: Integrating Formal Logic and LLMs for Explainable Transit Planning
[IJCAI-25] (Oral Spotlight - 13%) LogiDebrief: A Signal-Temporal Logic based Automated Debriefing Approach with Large Language Models Integration
[AAMAS-25] Combining LLMs with a Logic-Based Framework to Explain MCTS
[AAAI-25] (Oral Spotlight - 4.9%) Sim911: Towards Effective and Equitable 9-1-1 Dispatcher Training with an LLM-Enabled Simulation
[AAAI-24] (Oral Spotlight - 6%) Auto311: A Confidence-Guided Automated System for Non-emergency Calls
[Pervasive and Mobile Computing] CitySpec with shield: A secure intelligent assistant for requirement formalization
[IEEE SmartComp 22] (Best Paper Finalist) Cityspec: An intelligent assistant system for requirement specification in smart cities
[IEEE SmartComp 22] An intelligent assistant for converting city requirements to formal specification
Email: zirong.chen AT vanderbilt.edu
Office: Institute for Software Integrated Systems, Vanderbilt University
Address: 1025 16th Ave S, Nashville, TN 37212
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