Xiao Zhang
Scholar

Xiao Zhang

Google Scholar ID: xImPgj4AAAAJ
University of Pennsylvania
computer visiondeep learningmachine learning
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
1,109
 
H-index
6
 
i10-index
6
 
Publications
7
 
Co-authors
0
 
Contact
Emailxzhang11@seas.upenn.eduCVOpen ↗
Resume
Academic Achievements
  • - Falcon: Fractional Alternating Cut with Overcoming Minima in Unsupervised Segmentation, 2025 Preprint
  • - Rhythm Gate: Invisible Conversations in the Elevator, 2025 ACM International Conference on Multimedia (MM)
  • - Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-Identification, 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • - RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax, 2020 European Conference on Computer Vision (ECCV)
  • - Adacos: Adaptively Scaling Cosine Logits for effectively Learning Deep Face Representations, 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) [Oral]
  • - P2SGrad: Refined Gradients for Optimizing Deep Face Models, 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • - Range Loss for Deep Face Recognition with Long-tailed Training Data, 2017 IEEE International Conference on Computer Vision (ICCV)
Research Experience
  • - Research Intern at Nvidia (Jul. 2021 to Jul. 2022), worked on self-supervised representation learning with Dr. Charles Cheung
  • - Computer Vision Research Intern at SenseTime Research (Jul. 2017 to Jul. 2019), worked on large-scale smart city projects with Dr. Rui Zhao and Dr. Junjie Yan
  • - Visiting student at MMLab, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (Jul. 2016 to Jul. 2017), Advisor: Prof. Yu Qiao
Education
  • - Postdoc, University of Pennsylvania, Advisor: Prof. Konrad Kording
  • - Ph.D., Multimedia Lab (MMLab), The Chinese University of Hong Kong, Supervisors: Prof. Xiaogang Wang and Prof. Hongsheng Li
  • - B.Eng, College of Intelligence and Computing, Tianjin University, Minor in Finance
Background
  • - Research Interests: Representation learning and theory in foundation vision, language, and multi-modal data and their applications; human movement and cognition modeling; eye-movement analysis in medical areas; real-time scalable AI systems and infrastructures; AI systems empowered creative industries and contemporary arts research.
  • - Professional Field: Advancing scalable AI systems that address diverse machine learning challenges in real-world environments.
  • - Introduction: Dedicated to developing robust, scalable, and flexible representation learning methods, employing optimization, statistics, and high-performance computing systems to overcome challenges in large-scale, uncurated, and even ill-posed data.