I am Jun Hou, a PhD student at the Department of Computer Science, Virginia Tech, advised by Dr. Xuan Wang. My research focuses on developing robust, trustworthy, and explainable multimodal AI models, particularly aimed at improving accessibility and interpretability in healthcare. My research journey spans Multimodal Learning, Personalized LLM Agents, Explainable AI, and Clinical NLP.

Past: Previously, I conducted research on Explainable AI (XAI) in clinical settings under Dr. Lucy Lu Wang , developing techniques to validate and enhance clinicians' trust in NLP-driven clinical models. I hold Master's degrees in Data Analytics Engineering from Northeastern University and Actuarial Science from Columbia University, as well as a Bachelor's in Mathematics from Rutgers University.

Future: I aim to continue advancing AI research in multimodal fusion, interpretability, and personalized LLM agents. My goal is to design generalizable AI systems that are transparent, fair, and reliable, particularly for high-impact areas such as healthcare.

I am always open to collaboration and discussions. Please feel free to reach out to explore ideas together or simply chat about research and life!