About me

• Experience
  • Working
  • Education
  • Publications
• Talks
• Honors and Awards

Chihao Zhang

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Zhang Chihao holds a Ph.D. in Operations Research and Control Theory from the Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences (CAS), under the supervision of Prof. Shihua Zhang. After completing his Ph.D., he served as a Postdoctoral Researcher at the International Research Center for Neurointelligence, The University of Tokyo, under the guidance of Prof. Kazuyuki Aihara and Prof. Luonan Chen. Since 2023, he has been an Assistant Professor at AMSS, CAS. His research focuses on machine learning, statistical optimization, large-scale data analysis, and bioinformatics, with applications in developing advanced algorithms for data mining, clustering, and integration.

Experience

Working

• Assistant Professor
  Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences (CAS)
  2023 – Present

• Postdoctoral Researcher
  International Research Center for Neurointelligence, The University of Tokyo
  Advisors: Kazuyuki Aihara, Luonan Chen
  2021 – 2023

Education

• Ph.D. in Operations Research and Control Theory
  Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences (CAS)
  Advisor: Shihua Zhang
  2015 – 2021

• Visiting Graduate Student
  Department of Statistics, University of California, Los Angeles (UCLA)
  Advisor: Jingyi Jessica Li
  2020 - 2020

• Bachelor of Science in Statistics
  Beijing Normal University
  2011 – 2015

Publications

• Zhang, C., Gai, K., & Zhang, S. (2024). Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling. Pattern Recognition, 154, 110591.

• Zhang, C., Dong, K., Aihara, K., Chen, L., & Zhang, S. (2023). STAMarker: Determining Spatial Domain-specific Variable Genes with Saliency Maps in Deep Learning. Nucleic Acids Research, 51(20), e103. (slides)

• Zhang, C., Chen, E-Y., Zhang, S., & Li, J-J. (2022). Information-theoretic Classification Accuracy: A Data-driven Approach to Combining Ambiguous Outcome Labels. Journal of Machine Learning Research, 23, 1–65. (code | slides)

• Zhang, C., Yang, Y., Zhou, W., & Zhang, S. (2022). Distributed Bayesian Matrix Decomposition for Big Data Mining and Clustering. IEEE Transactions on Knowledge and Data Engineering. (code)

• Wang, H., Zhang, C., & Zhang, S. (2021). Robust Bayesian Matrix Decomposition with Mixture of Gaussian Noise. Neurocomputing.

• Zhang, C., & Zhang, S. (2021). Bayesian Joint Matrix Decomposition for Data Integration with Heterogeneous Noise. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(4), 1184–1196.

Talks

• Information-theoretic classification accuracy: a criterion that guides data-driven combination of ambiguous outcome labels in multi-class classification (1/4/2025). Shandong Mathematical Society Annual Academic Conference, Qingdao, China | slides

• STAMarker: Determining spatial domain-specific variable genes with saliency maps in deep learning (10/21/2023). The Third Mathematical and Life Science Conference, Wuxi, China. | slides

Honors and Awards

• Outstanding Graduate of Beijing and Outstanding Graduate of the University of Chinese Academy of Sciences, 2021
• President’s Excellence Award, Chinese Academy of Sciences, 2021
• President’s Excellence Award, Chinese Academy of Sciences, 2020
• National Scholarship for Doctoral Students, 2019