Tao Bai

About Me

I am a third-year Ph.D student at School of Computer Science & Engineering, Nanyang Technological University. Currently I am working closely with Prof. Bihan Wen. Prior to that, I obtained my Becholer degree from Wuhan University and worked with Prof. Hong Huang in 2018.

My current research interests lie in Adversarial Machine Learning, Image Forensics, Security and Privacy.

Please feel free to contact me for potential internships and collaborations!

News

• [Jun 08] One paper got accepted by IEEE IoT Journal!
• [Jun 07] Started my internship@Shield Lab, SRC, Huawei 2012 Lab!
• [May 20] One paper got accepted by ICIP 2021!
• [Apr 16] Our survey is accepted by IJCAI 2021! Check it
• [Nov 02] One paper got accepted by AAAI 2021 (Student Abstract & Poster)!

Publications

* Corresponding author

• Generating Adversarial yet Inconspicuous Patches with a Single Image
  Jinqi Luo, Tao Bai*, and Jun Zhao
  In Proceedings of the AAAI Conference on Artificial Intelligence 2021 (Student Abstract & Poster).
  [PDF]

• Recent Advances in Adversarial Training for Adversarial Robustness
  Tao Bai, Jinqi Luo, Jun Zhao, Bihan Wen, and Qian Wang
  In Proceedings of the 30th IJCAI 2021 Survey Track.
  [PDF] [Poster]

• AI-GAN: Attack-Inspired Generation of Adversarial Examples
  Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, and Alex Kot
  IEEE International Conference on Image Processing 2021.
  [PDF] [Poster]

Preprints

• Tao Bai, Jinqi Luo, and Jun Zhao, Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices. (In submission) [PDF]
• Helin Yang, Tao Bai, Jun Zhao , Kwok-Yan Lam, Zehui Xiong, Liang Xiao, Qingqing Wu, Federated Machine Learning for COVID-19 Diagnosis. (In submission)
• Tao Bai, Jinnan Chen, Jun Zhao, Bihan Wen, Xudong Jiang, and Alex Kot. Feature Distillation With Guided Adversarial Contrastive Learning. arXiv preprint arXiv:2009.09922 (2020). (In submission) [PDF]
• Jun Zhao, Teng Wang, Tao Bai, Kwok-Yan Lam, Zhiying Xu, Shuyu Shi, Xuebin Ren, Xinyu Yang, Yang Liu, and Han Yu. Reviewing and Improving the Gaussian Mechanism for Differential Privacy. arXiv preprint arXiv:1911.12060, 2019 (In submission). [PDF]
• Lin Sun, Jun Zhao, Xiaojun Ye, Shuo Feng, Teng Wang, and Tao Bai. Conditional analysis for key-value data with local differential privacy. arXiv preprint arXiv:1907.05014 (2019). [PDF]

Industrial Experience

• Huawei 2012 laboratories, Singapore Jun. 2021 - Present
  Mentor: Dr. Lin Hsiao Ying and Dr. Fang Chengfang
  Topic: Adversarial Attacks, Object Detection

Professional Service

Conference Reviewer

• The 29th International Joint Conference on Artificial Intelligence (IJCAI’20)
• AAAI 2021 Workshop: Towards Robust, Secure and Efficient Machine Learning (RSEML’21)

Journal Reviewer

• IEEE Transactions on Information Forensics and Security (T-IFS)
• IEEE Transactions on Network Science and Engineering (TNSE)
• IEEE Internet of Things Journal (IoTJ)

Volunteer

• The Thirty-eighth International Conference on Machine Learning (ICML’21)

Awards

• 2015 National Endeavor Scholarship, China
• 2016 First prize, Top 1.1%, Contemporary Undergraduate Mathematical Contest in Modeling, China
• 2017 National Endeavor Scholarship, China
• 2017 First Grade Scholarship, China
• 2017 Meritorious Winner, Mathematical Contest In Modeling, US
• 2019- Research Scholarship, Singapore
• 2020 University Teaching for Teaching Asisstants

Teaching Assistant

• CZ1012/CE1012 Engineering Mathematics (2019-2020, Semester 1/2, Labs)
• CZ3006/CE3005 Computer Networks (2019-2020, Semester 2/Special Term 1, Labs)
• CZ3006 Net-Centric Computing (2020-2021, Semester 1, Labs/Tutorials)
• CZ2001 Algorithms (2020-2021, Semester 1, Labs)

Mentees

• Chua Shan Jing (NTU SCSE, 2019)
• Terence Chan Chin Leng (NTU SCSE, 2019)
• Luo Jinqi (NTU SCSE, 2020)
• Chan Yan Cheng Jarod (NTU SCSE, 2020)
• Kant Mannan (NTU SCSE, 2020)
• Cao Shuxin (NTU EEE, 2020)
• Lu Yuhao (SJTU, 2020)
• Wang Xiaoyu (XJTU, 2020)
• Zhao Peizhu (NTU SCSE, URECA, 2020)

Last updated Jul. 2021