I’m Xiaoyang Wang (王晓阳), a PhD candidate at Drexel University advised by Prof. Christopher C. Yang in the Health Informatics Research Group.

My research centers on trustworthy AI for healthcare, with a particular focus on fairness, explainability, and reliability in clinical predictive modeling. I develop algorithms that ensure equitable model performance across demographic subgroups while maintaining high predictive accuracy. Building upon this foundation, I am now exploring multimodal learning frameworks that integrate structured EHR data, clinical notes, and medical imaging to construct unified patient representations. In parallel, I am investigating LLM-based agentic AI systems that can autonomously reason, coordinate, and adapt in complex medical and health environments.

Before joining Drexel University for my doctoral studies, I earned my M.S. degree from the University of Pittsburgh, where I was advised by Prof. Peter Brusilovsky, and my B.E. degree from Shanghai Normal University.

🔥 News

2025.12: 🎉 A paper accepted by Pattern Recognition.
2025.11: ✈️ Attended the AMIA Annual Symposium 2025 in Atlanta, GA.
2025.10: 🚶 Attended ACM BCB 2025 in Philadelphia, PA and delivered a presentation.
2025.08: 🎉🎉 Two papers accepted by the 16th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB’25).
2025.07: 🎉 A paper accepted by IEEE Transactions on Information Forensics & Security.
2025.06: 👨🏻‍💻 Attended IEEE ICHI’25 & AIME’25 (both in Italy 🇮🇹) and presented remotely 🥹.
2025.04: 🎉 A paper accepted by the 23rd International Conference on Artificial Intelligence in Medicine (AIME’25).
2025.01: 🎉🎉 Two papers accepted by the 13th IEEE International Conference on Health Informatics (IEEE ICHI’25).
2024.12: ⛳ Successfully passed the Ph.D. candidacy examination at Drexel University.
2024.07: ✈️ Attended AIME’24 in Salt Lake City, UT 🩼 and delivered a presentation.
2024.06: ✈️ Attended IEEE ICHI’24 in Orlando, FL and delivered a presentation.
2024.04: 🎉 A paper accepted by the 22nd International Conference on Artificial Intelligence in Medicine (AIME’24).
2024.03: 🎉 A paper accepted by the 12th IEEE International Conference on Health Informatics (IEEE ICHI’24).

📝 Publications

IEEE TIFS

FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models

Yixuan Li, Xuelin Liu, Xiaoyang Wang, Bu Sung Lee, Shiqi Wang, Anderson Rocha, and Weisi Lin.

This work introduces FakeBench, a multimodal benchmark designed to evaluate large multimodal models (LMMs) on explainable fake image detection rather than simple binary classification.
The benchmark incorporates a fine-grained taxonomy of generative visual forgeries and human-in-the-loop textual descriptions to assess detection, reasoning, interpretation, and detailed forgery analysis.

Pattern Recognition

DeepSelective: Interpretable Prognosis Prediction via Feature Selection and Compression in EHR Data

Ruochi Zhang, Qian Yang, Xiaoyang Wang, Haoran Wu, Qiong Zhou, Yu Wang, Kewei Li, Yueying Wang, Yusi Fan, Jiale Zhang, Lan Huang, Chang Liu, Fengfeng Zhou.

This work proposes DeepSelective, a novel end to end deep learning framework for predicting patient prognosis using EHR data, with a strong emphasis on enhancing model interpretability.
DeepSelective combines data compression techniques with an innovative feature selection approach, integrating custom-designed modules that work together to improve both accuracy and interpretability.

ACM-BCB 2025 MoE-Health: A Mixture of Experts Framework for Robust Multimodal Healthcare Prediction, Xiaoyang Wang, Christopher C. Yang.
ACM-BCB 2025 Automated Clinical Problem Detection from SOAP Notes using a Collaborative Multi-Agent LLM Architecture, Yeawon Lee, Xiaoyang Wang, Christopher C. Yang.
IEEE ICHI 2025 Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling, Xiaoyang Wang, Christopher C. Yang.
AIME 2025 (Top 6% Oral) Balancing Fairness and Performance in Healthcare AI: A Gradient Projection Approach, Xiaoyang Wang, Christopher C. Yang.
AIME 2024 Explainable AI for Fair Sepsis Mortality Predictive Model, Chia-Hsuan Chang*, Xiaoyang Wang*, Christopher C. Yang.
IEEE ICHI 2024 An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion, Mary M. Lucas, Xiaoyang Wang, Chia-Hsuan Chang, Christopher C. Yang.
IEEE Access Achieving Equity via Transfer Learning with Fairness Optimization, Xiaoyang Wang, Chia-Hsuan Chang, Christopher C. Yang.

🎖 Honors and Awards

2025.06 The Student Scholar Award, AIME 2025 - €800
2025.06 The Student Scholar Award, IEEE ICHI 2025 - $1000
2017.10 Merit Student Researcher Scholarship, Chinese Academy of Sciences - ¥3000
2016.10 Second Prize Merit Scholarship, Shanghai Normal University - ¥1200

📖 Educations

2022.09 - 2027.06 (now) 🇺🇸 Ph.D. in Information Science, Drexel University, Philadelphia, USA.
2018.08 - 2020.05 🇺🇸 M.Sc. in Information Science, University of Pittsburgh, Pittsburgh, USA.
2014.09 - 2018.06 🇨🇳 B.Eng. in Telecommunication Engineering, Shanghai Normal University, Shanghai, China.

💻 Work Experience

2020.09 - 2022.09 Cloud Software Engineer (Full-time), China CITIC Bank, Beijing, China.
2017.12 - 2018.06 Software Engineer (Intern) Radar Institute, Shanghai, China.
2017.04 - 2017.07 Software Engineer (Intern) SIMIT, Shanghai, China.

⚖️ Academic Participation

Journal Reviewer: Journal of the American Medical Informatics Association(JAMIA), Journal of Healthcare Informatics Research (JHIR), IEEE Transactions on Information Forensics & Security (TIFS), Information Processing and Management (IPM)
Conference Reviewer: NeurIPS’24, AAAI’25, ICLR’25, ICWSM’25, IEEE ICHI’25, IEEE ICHI’26, WWW’26, Digital Twins for Health Society (DT4HS)

🍎 Teaching Experience

2026.01 - 2026.03 Teaching Assistant, INFO 103: Introduction to Data Science, Drexel University, Philadelphia, PA.
2024.09 - 2024.12 Teaching Assistant, INFO 212: Data Science Programming I, Drexel University, Philadelphia, PA.
2017.02 - 2017.05 Teaching Assistant, Digital Switching, Shanghai Normal University, Shanghai, China.
2015.09 - 2015.12 Teaching Assistant, Probability Theory and Mathematical Statistics, Shanghai Normal University, Shanghai, China.

Xiaoyang Wang