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Zhiguo Zhou, Ph.D.

Zhiguo Zhou portrait
Assistant Professor, Biostatistics & Data Science

Professional Background

Dr. Zhou is an Assistant Professor in the Department of Biostatistics and Data Science at the University of Kansas Medical Center. He is also an Associate Member of University of Kansas Cancer Center. He received his B.S. and Ph.D. degrees in Computer Science from Xidian University. He was a student visiting scholar at Leiden University. Then he worked as postdoctoral fellow and research instructor at University of Texas Southwestern Medical Center. His research goal is to develop reliable artificial intelligence (RAI) in theory and apply RAI in medical innovation. His current research in methodology focuses on machine learning and deep learning, probabilistic inference, knowledge representation and reasoning, etc., whilst his clinical research includes treatment outcome prediction, clinical decision support, medical image analysis, radiomics, biomarker discovery and other clinical problems.

Education and Training
  • PhD, Computer Science, Xidian University, Xi'an, Shaanxi
  • BS, Computer Science, Xidian University, Xi'an, Shaanxi
  • Post Doctoral Fellowship, Medical Physics, University of Texas Southwestern Medical Center, Dallas, TX
Professional Affiliations
  • American Association for Cancer Research (AACR), Member, 2023 - Present
  • University of Kansas Cancer Center, Member, 2022 - Present
  • The Institute of Electrical and Electronics Engineers (IEEE), Member, 2019 - Present



My research mainly consists of reliable artificial intelligence (RAI) and medical innovation. In RAI, I will develop a unified methodology to build balanced, safe, robust and interpretable AI system. Several machine learning and deep learning based strategies have been developed. In medical innovation, I will develop RAI based model or method to solve the clinical problems, especially in cancer. Multiple models have been developed for treatment outcome prediction, radiomics, clinical diagnostic support, quantitative imaging biomarker discovery, and medical image processing.