Chenshuang Zhang

I am currently a Ph.D. student advised by Professor In So Kweon and Professor Junmo Kim, from School of Electronical Engineering, KAIST. My current research interest lies in the interaction of computer vision and machine learning, including but not limited to：

Generative models
Multi-modality learning
Adversarial machine learning

Before join KAIST, I worked full time as a Senior Machine Learning Engineer in Alibaba Group, Beijing, China. As project leader, my work aimed to recommend the most suitable goods to the user on TaoBao online shopping platform and improved Taobao from multiple aspects (e.g., the click-through rate).

I got my master degree from Department of Electronic Engineering, Tsinghua University. Advised by Professor Guijin Wang, I worked on deep learning in medical applications.

I'm always open to collaborations on various research topics. If you are interested in my work, please feel free to contact me.

Email / Google Scholar / LinkedIn

Publications

* indicates equal contributions

	ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object Chenshuang Zhang, Fei Pan, Junmo Kim, In So Kweon, Chengzhi Mao IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. CVPR Highlight (2.8%)
	Towards Understanding Dual BN In Hybrid Adversarial Training Chenshuang Zhang, Chaoning Zhang, Kang Zhang, Axi Niu, Junmo Kim, In So Kweon Transactions on Machine Learning Research (TMLR), 2024
	Text-to-image Diffusion Models in Generative AI: A Survey Chenshuang Zhang, Chaoning Zhang, Mengchun Zhang, Junmo Kim, In So Kweon Under review, 2024
	A global and updatable ECG beat classification system based on recurrent neural networks and active learning Guijin Wang, Chenshuang Zhang (First student author), Yongpan Liu, Huazhong Yang, Dapeng Fu, Haiqing Wang, Ping Zhang Information Sciences (Impact factor 8.23), 2019
	Patient-specific ECG classification based on recurrent neural networks and clustering technique Chenshuang Zhang, Guijin Wang, Jingwei Zhao, Pengfei Gao, Jianping Lin, Huazhong Yang 2017 13th IASTED International Conference on Biomedical Engineering (BioMed), 2017
	A survey on masked autoencoder for visual self-supervised learning Chaoning Zhang, Chenshuang Zhang, Junha Song, John Seon Keun Yi, In So Kweon International Joint Conference on Artificial Intelligence (IJCAI), 2023
	How does simsiam avoid collapse without negative samples? a unified understanding with self-supervised contrastive learning Chaoning Zhang, Kang Zhang, Chenshuang Zhang, Trung X Pham, Chang D Yoo, In So Kweon International Conference on Learning Representations (ICLR), 2022
	Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness Chaoning Zhang, Kang Zhang, Chenshuang Zhang, Axi Niu, Jiu Feng, Chang D Yoo, In So Kweon European Conference on Computer Vision (ECCV) Oral, 2022
	A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI Chenshuang Zhang, Chaoning Zhang, Sheng Zheng, Mengchun Zhang, Maryam Qamar, Sung-Ho Bae, In So Kweon Arxiv, 2023
	One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era Chaoning Zhang, Chenshuang Zhang, Chenghao Li, Yu Qiao, Sheng Zheng, Sumit Kumar Dam, Mengchun Zhang, Jung Uk Kim, Seong Tae Kim, Jinwoo Choi, Gyeong-Moon Park, Sung-Ho Bae, Lik-Hang Lee, Pan Hui, In So Kweon, Choong Seon Hong Arxiv, 2023
	A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need? Chaoning Zhang, Chenshuang Zhang, Sheng Zheng, Yu Qiao, Chenghao Li, Mengchun Zhang, Sumit Kumar Dam, Chu Myaet Thwal, Ye Lin Tun, Le Luang Huy, Donguk kim, Sung-Ho Bae, Lik-Hang Lee, Yang Yang, Heng Tao Shen, In So Kweon, Choong Seon Hong Arxiv, 2023
	A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material Mengchun Zhang, Maryam Qamar, Taegoo Kang, Yuna Jung, Chenshuang Zhang, Sung-Ho Bae†, Chaoning Zhang Arxiv, 2023
	Bidirectional recurrent neural network and convolutional neural network (BiRCNN) for ECG beat classification Pengwei Xie, Guijin Wang, Chenshuang Zhang, Ming Chen, Huazhong Yang, Tingting Lv, Zhenhua Sang, Ping Zhang 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018

Thanks to Jon Barron for sharing the code of nice website.