Hanchen David Wang
Let's talk, chitchat, and grab coffee :)
About Me
Welcome! My name is David. I recently defended my PhD at Vanderbilt University, advised by Prof. Meiyi Ma, with a thesis titled Explanation-Guided Adaptive Learning for Human-Centered Cyber-Physical Systems. My research focuses on eXplainable AI in Healthcare and Deep Learning. Outside of research, I love staying active through workouts, expressing creativity through drawing, and exploring the outdoors. I'm also a big cat lover! Whether it's grabbing boba or coffee, I'm always up for a good conversation. ☕🧋
Research Interests
My research spans across multiple areas of artificial intelligence and computer science, with a focus on making AI systems more explainable, reliable, and beneficial for healthcare applications.
Key Areas: Explainable AI (XAI), Healthcare AI, Machine Learning, Physical Therapy & Motion Analysis, Nursing Education Simulations, Formal Verification, Multimodal Learning, Continual Learning
Education
Ph.D. in Computer Science (Defended)
Vanderbilt University
Aug 2021 - May 2026
Advisor: Prof. Meiyi Ma
Master of Science in Computer Science
Vanderbilt University
Aug 2021 - May 2023
Bachelor of Science in Computer Science, Magna cum Laude (top 6%) GPA: 3.89
University of California, Irvine
Aug 2017 - Jun 2021
Recent Highlights
Latest Research
AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education (Jul 2024 - Mar 2026)
Proposed a three-stage framework for automated competency assessment from egocentric nursing simulation video using frozen visual encoders and few-shot learning
Recent Publication
AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education
CVPR Workshop on Computer Vision for Education (CV4EDU) - Accepted
Current Position
Research Assistant @ Vanderbilt University (May 2022 - Present)
Researched activity recognition using deep learning methodologies, focusing on enhancing the quality assessment of exercises through Explainable Artificial Intelligence (XAI) techniques.
Latest Talk
Learning with Preserving for Continual Multitask Learning
AAAI 2026 (Oral Presentation)
Quick Links
Let's connect! Feel free to reach out for collaborations or discussions about AI and healthcare.