Haofan Wang

Computer Vision Engineer, TAL
Email: haofanwang.ai (at) gmail.com
Research Interests
  • Computer Vision
  • Graph Neural Network
  • Explainable Neural Network
  • Adversarial Attack and Robustness

Haofan Wang (王浩帆) is a computer vision engineer at TAL AI. He graduated from Carnegie Mellon University in December 2020, advised by Prof. Piotr (Peter) Mardziel. Previously, he worked as a research intern with Prof. Bernard Ghanem at KAUST in 2020 Summer and Prof. Xia (Ben) Hu at Texas A&M University in 2019 Summer. He obtained undergraduate degree from Dalian Maritime University and exchanged at UC Berkeley in 2017 Fall. He also spent time at RealAI, Everspry, Horizon Robotics and Institute of Software Chinese Academy of Sciences.


2020.9.25: Our paper "Smoothed Geometry for Robust Attribution" has been accepted to NeurIPS 2020!

2020.7.10: I will join KAUST IVUL as a remote intern, advised by Prof. Bernard Ghanem.

2020.4.12: Our paper "Score-CAM" has been accepted to CVPR 2020 Workshop!

Haofan Wang*, Zifan Wang, Mengnan Du, Fan Yang, Zijian Zhang, Sirui Ding, Piotr Mardziel and Xia (Ben) Hu
IEEE CVPR 2020 Workshop on Fair, Data Efficient and Trusted Computer Vision
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