Zijun Yao

Zijun Yao is an Assistant Professor at the Department of EECS, The University of Kansas, focusing on AI-driven healthcare applications. Previously, they worked as a research staff member at IBM Research, where they developed AI solutions for healthcare challenges.

Education: Ph.D. in Information Technology from Rutgers University (2018).

Research Interests: Their work bridges

• Data Mining
• Artificial Intelligence
• Health Informatics
• Medical Signal Processing
• Natural Language Processing
• Mobile Intelligence

. Current projects emphasize ECG analysis, survival modeling, and multimodal deep learning for clinical diagnostics.

Publication Trends: Recent articles highlight

• Explainable AI for Alzheimer's prediction
• Autoencoder-based ECG feature extraction
• Ontology-guided prescription recommendation
• Adversarial attacks in survival models
• Temporal dependency modeling in EHR
• Generative AI for personalized learning

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Technical Expertise: The University of Kansas faculty member specializes in AI architectures like graph transformers, recurrent networks, and contrastive learning frameworks, with a focus on clinical data interpretability and robustness.