Chaoning Zhang

Chaoning Zhang

Assistant professor at Kyung Hee University

Welcome to my website!

I am currently an assistant professor at Kyung Hee University. Prior to that, I worked under the supervision of Professor In So Kweon at KAIST. My research domain includes (but is not limited to) the following topics: (1) mode robustness (like adversarial attack/defense), (2) data efficiency (self-supervised learning), (3) generative AI (AIGC). I obtained Qualcomm Innovation Felowship (Korea) in 2020. In the past few years, I have published around 30 first or co-first author papers at AI conferences, including CVPR, ICCV, ECCV, NeurIPS, ICLR, AAAI, IJCAI, ACM MM, BMVC, WACV etc. I am recruiting motivated students for PhD, master, as well as post-doctoral (or intern) researchers. You can access my CV here and contact me through chaoningzhang1990@gmail.com.

Interests

  • Adversarial Machine Learning
  • Self-supervised learning
  • Generative AI

Education

  • Ph.D., 2018.2-2021.8

    KAIST, South Korea

  • Dual Master Degree, 2012.9-2015.7

    Harbin Institute of Technology (China) & Delft University of Technology (The Netherlands)

Recent Research Papers

Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness (ECCV 2022 Oral)
Dual temperature helps contrastive learning without many negative samples: Towards understanding and simplifying moco (CVPR 2022)
Investigating Top-k White-Box and Transferable Black-Box Attack (CVPR 2022)

Recent
Survey
Papers

A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI
Text-to-image Diffusion Model in Generative AI: A Survey
A survey on masked autoencoder for self-supervised learning in vision and beyond
A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material