Haofan Wang

Computer Vision Engineer
Work Email: wanghaofan (at) kuaishou.com
School Email: haofanw (at) alumni.cmu.edu
Personal Email: haofanwang.ai (at) gmail.com
Research Interests
  • Contrastive Learning
  • Cross-Modal Pre-training
  • Self-Supervised Learning
  • Interpretable Machine Learning
Biography

Haofan Wang (王浩帆) is a computer vision engineer at MMU of Kuaishou Technology, supervised by Dr. Debing Zhang on cross-modal retrieval. Before joined Kuaishou, he graduated from Carnegie Mellon University in December 2020, advised by Dr. Piotr (Peter) Mardziel. Previously, he worked as a research intern with Prof. Bernard Ghanem at KAUST (2020 Summer) and Prof. Xia (Ben) Hu at Texas A&M University (2019 Summer). He obtained undergraduate degree from Dalian Maritime University in June 2019 and exchanged at UC Berkeley (worked at RISE Lab, Clipper Group) in 2017 Fall. He also worked at OpenMined, RealAI, Everspry, Horizon Robotics and Institute of Software Chinese Academy of Sciences.

I have a plan to apply for a Ph.D. position started in 2023 Spring/Fall, if you are interested in my background and have positions, please don't hesitate to contact me! Outside work, I am also open to research discussion or work opportunities, find me via haofanwang.ai@gmail.com.

News
  • [06/2021]: One abstract is accepted to RCV workshop at CVPR 2021! The full paper is accepted to PPML at ACM CCS 2021!
  • [12/2020]: I moved from CMU to MMU of Kuaishou Technology as software engineer!
  • [11/2020]: One paper is accepted to SpicyFL workshop at NeurIPS 2020!
  • [09/2020]: One paper accepted to NeurIPS 2020!
  • [04/2020]: One paper accepted to TCV workshop at CVPR 2020!
  • Selected Publications (Full List)
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    Rakshit Naidu, Aman Priyanshu, Aadith Kumar, Sasikanth Kotti, Haofan Wang*, Fatemehsadat Mireshghallah
    IEEE CVPR 2021 Workshop on Responsible Computer Vision, Poster
    [Paper] [Poster]
    [scipy]
    Tushar Semwal, Haofan Wang*, Chinnakotla Krishna Teja Reddy.
    NeurIPS 2020 Workshop on Scalability, Privacy, and Security in Federated Learning, Poster
    [Paper]
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    Zifan Wang, Haofan Wang*, Shakul Ramkumar, Matt Fredrikson, Piotr Mardziel, and Anupam Datta
    NeurIPS 2020, Poster
    [Paper] [Poster] [Code] [Citation: 6]
    [Score-CAM]
    IEEE CVPR 2020 Workshop on Fair, Data Efficient and Trusted Computer Vision
    [Project Page] [Paper] [Slides] [News] [Citation: 133]
    [HeadPose]
    Haofan Wang*, Zhenghua Chen, and Yi Zhou,
    ArXiv 1901.06778
    [Project Page] [Paper] [Citation: 4]
    Talks
  • [06/2021] MMU, Kuaishou. An Overview of Large Scale Pre-Training
  • Teaching
  • TA of 18-793 Image and Video Processing, Summer 2020, Carnegie Mellon University
  • Professional Services
  • Conference Reviewer: NeurIPS'21, ICLR'22
  • Trajectory

    DMU (Bachelor) --> CMU (Master) --> MMU (Engineer) --> What's NeXT?