Chaowei Xiao
Email: xiaocw [at] umich [dot] edu
I am Chaowei Xiao, an assistant professor in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University and a research scientist at NVIDIA Research.
My research interests lie at the intersection of computer security, privacy, and machine learning, with the goal to build the soically responsible machine learning systems.
I obtained my PhD degree from University of Michigan, Ann Arbor under supervision of Peter and Evelyn Fuss Chair of Electrical and Computer Engineering Prof. Mingyan Liu . I obtained my bachelor's degree in School of Software from Tsinghua University in 2015, advised by Professor Yunhao Liu.
My group has multiple positions for PhD student, Summer interns and Visiting students. If you are interested, please send me an email with your CV, and publications (if any).
Recent News
- [09/2021] Three papers got accepted to NeurIPS. Thanks for all of my collaborators.
- [08/2021] I gave a talk at Tsinghua University
- [07/2021] One paper is accepted to ICCV.
- [07/2021] I am serving as an Area Chair for AAAI 2022.
- [06/2021] I gave a talk in CVPR 2021 Tutorial on Adversarial Machine Learning in Computer Vision.
- [04/2021] One paper is accepted to IEEE S&P.
- [03/2021] Best Paper Award at ESWN 2021
- [11/2020]: One paper is accepted to NeurIPS’20 .
- [11/2020]: One paper is accepted to NeurIPS’20 .
- [06/2020]: One paper is accepted to ECCV’20 .
- [12/2019]: One paper is accepted to ICLR’20 .
- [08/2019]: Our generated physical adversarial Stop Sign used in our CVPR’18 is on display at Science Museum in London.
- [07/2019]: One paper is accepted to ICDM 2019.
- [03/2019]: Our paper "MeshAdv: Adversarial Meshes for Visual Recognition" is accepted to CVPR 2019 as oral presentation.
- [03/2019]: We will organize the workshop on Adversarial Machine Learning in Real-World Computer Vision Systems at CVPR 2019. Please submit your papers.
More
Events
- [Call For Paper] I am serving as the Guest Editor of Frontiers in Big Data: Trustworthy Machine Learning. The submission deadline is Aug 31, 2021.
- [Workshop@ICCV2021] I am co-organizing the Workshop on Neural Architectures: Past, Present and Future in ICCV 2021.
- [Workshop@ICML2021] I co-organized the Workshop on Socially Responsible Machine Learning in ICML 2021.
- [Workshop@ACMMM2021] I co-organized the Workshop on 1st International Workshop on Adversarial Learning for Multimedia in ACM-MM 2021.
- [Workshop@CVPR2019] I co-organized the Workshop on Adversarial Machine Learning in Real-World Computer Vision Systems. in CVPR 2019.
Publications
(* represents equal contribution)
- Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions.
Jiachen Sun, Yulong Cao, Christopher Choy, Zhiding Yu, Anima Anandkumar, Z. Morley Mao, and Chaowei Xiao.
NeurIPS 2021
- AugMax: Adversarial Composition of RandomAugmentations for Robust Training.
Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
NeurIPS 2021
- Efficient Transformers for Language and Vision.
Chen Zhu, Wei Ping, Chaowei Xiao, Mohammad Shoeybi, Tom Goldstein, Anima Anandkumar, Bryan Catanzaro.
NeurIPS 2021 (84.1% Top-1 accuracy solely trained on ImageNet-1K)
- Can Shape Structure Features Improve Model Robustness?
Mingjie Sun*, Zichao Li*, Chaowei Xiao*, Haonan Qiu, Bhavya Kailkhura, MingyanLiu, Bo Li.
ICCV 2021
- Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks.
Yulong Cao*, Ningfei Wang*, Chaowei Xiao*, Dawei Yang*, Jin Fang, RuigangYang, Qi Alfred Chen, Mingyan Liu, Bo Li.
IEEE Symposium on Security and Privacy (Oakland) 2021
- Application-Driven Privacy-Preserving Data Publishing with Correlated Attributes.
Aria Rezaei, Chaowei Xiao, Jie Gao, Bo Li, Sirajum Munir.
Embedded Wireless Systems and Networks (EWSN 2021)Best Paper Award
- SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing
Haonan Qiu*, Chaowei Xiao*, Lei Yang*, Xinchen Yan, Honglak Lee, Bo Li.
ECCV 2020
- Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations
Huan Zhang*, Hongge Chen*, Chaowei Xiao, Bo Li, Mingyan Liu, Duane Boning, Cho-Jui Hsieh.
NeurIPS 2020 (Spotlight).
- Towards Stable and Efficient Training of Verifiably Robust Neural Networks
Huan Zhang, Hongge Chen, Chaowei Xiao, Sven Gowal, Robert Stanforth, Bo Li, Duane Boning, Cho-Jui Hsieh.
ICLR 2020.
- AdvIT: Adversarial Frames Identifier Based on Temporal Consistency In Videos
Chaowei Xiao, Ruizhi Deng, Bo Li, Taesung Lee, Jinfeng Yi, Ian Molloy, Mingyan Liu, Dawn Song
In International Conference on Computer Vision (ICCV) 2019.
- MeshAdv: Adversarial Meshes for Visual Recognition
Chaowei Xiao*, Dawei Yang*, Bo Li, Jia Deng, Mingyan Liu
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019. (Oral presentation) [pdf]
- Performing Co-Membership Attack Against Deep Generative Model
Kin Sum Liu, Chaowie Xiao , Bo Li, Jie Gao
In IEEE International Conference on Data Mining (ICDM) 2019
- Improving Robustness of ML Classifiers against Realizable Evasion Attacks Using Conserved Features
Liang Tong, Bo Li, Chen Hajaj, Chaowei Xiao, Ning Zhang, Yevgeniy Vorobeychik.
In USENIX Security 2019.
- Adversarial Sensor Attack on LIDAR-based Perception in Autonomous Driving
Yulong Cao, Chaowei Xiao, Benjamin Cyr, Yimeng Zhou, Won Park, Sara Rampazzi, Qi Alfred Chen, Kevin Fu, Z. Morely Map
In the 26th ACM Conference on Computer and Communications Security (CCS'19) [pdf]
- Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Chaowei Xiao, Duizhi Deng, Bo Li, Fisher Yu, Mingyan Liu and Dawn Song
In European Conference on Computer Vision (ECCV), 2018 [pdf][supplementary material]
- Spatially Transformed Adversarial Examples
Chaowei Xiao*, Jun-Yan Zhu*, Bo Li, Warren He, Mingyan Liu and Dawn Song
In International Conference on Learning Representations (ICLR), 2018 [pdf]
- Generating Adversarial Examples with Adversarial Networks
Chaowei Xiao, Bo Li, Jun-Yan Zhu, Warren He, Mingyan Liu and Dawn Song
In International Joint Conference on Artificial Intelligence (IJCAI), 2018. [pdf]
- From Behavior Similarity to Symptom Similarity: Using Community Detection for Early Discovery of Software Exploits
Chaowei Xiao, Armin Sarabi,Yang Liu , Bo Li, Mingyan Liu and Tudor Dumitras
In USENIX Security Symposium (USENIX Security), 2018 [pdf]
- Robust Physical-World Attacks on Machine Learning Models
Kevin Eykholt*, Ivan Evtimov*, Earlence Fernandes, Bo Li, Amir Rahmati, Chaowei Xiao, Atul Prakash, Tadayoshi Kohno and Dawn Song
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 [pdf]
- Static Power of Mobile Devices: Self-updating Radio Maps for Wireless Indoor Localization
Chenshu Wu, Zheng Yang, Chaowei Xiao, Chaofan Yang, Yunhao Liu and Mingyan Liu
In IEEE International Conference on Computer Communications (INFOCOM), 2015
- Tagoram: Real-time Tracking of Mobile RFID Tags to High Precision Using COTS Devices.
Lei Yang, Yekui Chen, Xiangyang Li, Chaowei Xiao, Mo Li and Yunhao Liu
In International Conference on Mobile Computing and Networking (MobiCom), 2014. Best Paper Award
