Wei Zhu’s Homepage, University of Rochester

Hi, I am Wei Zhu, a 4-th year Ph. D. student from the department of computer science, University or Rochester Rochester, NY. My advisor is Prof. Jiebo Luo. Prior to coming to UR, I received my M.S. degree from Northwestern Polytechnical University, Xi’an China in 2018 advised by Prof. Feiping Nie and Prof. Xuelong Li. I am interested in representation learning, fairness/debiasing/domain generalization, federated learning, few-shot learning and their applications in natural images, molecular graph, multivariate time series data, and medical images.

Email: zwvews@gmail.com

last update: Sep. 2021

Publications: Google Scholar

Preprint Papers

  1. W. Zhu, Z. Zheng, H. Zheng, H. Lyu, and J. Luo, “Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis”. paper [noisy labels]
  2. W. Zhu, Andrew White, and J. Luo, “Federated Learning of Molecular Properties in a Heterogeneous Setting”. paper [federated learning], [graph neural network]
  3. H. Zheng, K. Wu, J. Park, W. Zhu, and J. Luo, “Personalized Fashion Recommendation from Personal Social Media Data: An Item-to-Set Metric Learning Approach”. paper [metric learning], [representation learning]
  4. Y. Feng, F. Peng, X. Zhang, W. Zhu, S. Zhang, Z. Li, T. Duerig, S. Chang, and J. Luo, “Unifying Specialist Image Embedding into Universal Image Embedding”. paper [representation learning]

Conference Papers

  1. W. Zhu, Z. Zheng, H. Liao, W. Li, and J. Luo, “Learning Bias-Invariant Representation by Cross-Sample Mutual Information Minimization,” ICCV 2021. paper, code available soon [debiasing/fairness], [mutual information estimation]
  2. W. Zhu, H. Liao, W. Li, W. Li, and J. Luo, “Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification,” MICCAI 2020. paper [few-shot learning], [contrastive learning], [metric learning] MICCAI 2020 NIH AWARDS
  3. W. Zhu, F. Shi and J. Luo, “Modeling Heterogeneity in Feature Selection for MCI Classification”, ISBI 2020. paper [feature selection], [clustering]
  4. W. Li, W. Zhu, R. Dorsey, J. Luo, “Predicting Parkinson’s Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data”, ICDM 2020. paper [multivarite time series]
  5. W. Zhu, F. Nie and X. Li, “Fast Spectral Clustering with Efficient Large Graph Embedding,” ICASSP 2017. paper [clustering], [metric learing]
  6. F. Nie, W. Zhu and X. Li, “Unsupervised Large Graph Embedding,” AAAI 2017. paper [metric learning]
  7. F. Nie, W. Zhu and X. Li, “Unsupervised Feature Selection with Structured Graph Optimization,” AAAI 2016, 1302-1308. paper [feature selection]

Journal Papers

  1. W. Zhu, W. Li, H. Liao, and J. Luo, “Temperature Network for Few-shot Learning with Distribution-aware Large-margin Metric,” Pattern Recognition, 2021. paper code [few-shto leanring], [metric learning]
  2. F. Nie, W. Zhu and X. Li, “Decision Tree SVM: An Extension of Linear SVM for Non-linear Classification,” Neurocomputing 2020. paper [SVM]
  3. F. Nie, W. Zhu and X. Li, “Unsupervised Large Graph Embedding Based on Balanced and Hierarchical K-means,” TKDE 2020. paper [clustering], [metric learning]
  4. F. Nie, W. Zhu and X. Li, “Structured Graph Optimization for Unsupervised Feature Selection,” TKDE 2019. paper [feature selection]


  • Ph.D. in Computer Science (Sep. 2018 - May. 2023 expected)
    • Department of Computer Science, University of Rochester, NY
    • Advisor: Prof. Jiebo Luo
  • M.S. in Computer Science (Sep. 2015 - May. 2018)
  • B.S. in Software Engineering (Sep. 2011 - Jul. 2015)
    • School of Software and Microelectronics, Northwestern Polytechnical University, Xi’an

Research Experiences

  • Reserach assistant: work with Prof. Jiebo Luo at the University of Rochester, NY (2018 - now)
    • Representation Learning, Federated Learning, and Domain Generalization/Debiasing
  • Research assistant: work with Prof. Andrew White and Prof. Jiebo Luo at the University of Rochester, NY (Jan. 2021 - now)
    • Federated Learning, Graph Neural Network, Molecular Property Prediction
  • Summer intern: work with Dr. Adam P. Harrison and Dr. Shun Miao at PAII, Bethesda, MD (May. 2021 - Aug. 2021)
    • Domain Generalization for Steatosis Diagnosis based on Ultrasound Images
  • Summer intern: work with Prof. Dongjin Song and Dr. Yuncong Chen at NEC American Lab, Princeton, NJ (May. 2020 - Aug. 2020)
    • Federated Anomaly Detection
  • Summer intern: work with Dr. Zhoubing Xu at Siemens Healthineer, Princeton, NJ (May. 2019 - Aug. 2019)
    • Self-supervised learning with CT images
  • Summer intern: work with Dr. Feng Shi at United-imaging Inc. Shanghai, China (May. 2018 - Aug. 2018)
    • MCI Diagnosis
  • Research assistant: work with Prof. Feiping Nie at the Northwestern Polytechnical University, Xi’an, China (2015 - 2018)
    • SVM, Spectral-based feature selection and clustering