Tao Sun
Hi! I am a final-year PhD student in Computer Science at Stony Brook University, fortunately advised by Prof. Haibin Ling.
I am broadly interested in machine learning and computer vision, particularly vision-language learning, domain adaptation, weakly-supervised learning. I also work on adversarial attack and defense of neural networks.
Contact: tao # cs.stonybrook.edu
news
| Aug 2024 | Finished my internship at Amazon, Seattle! We worked on multi-modal In-Context-Learning for LLaVA model. |
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| Aug 2023 | One paper accepted by Digital Discovery! |
| Jul 2023 | One paper on Active Domain Adaptation accepted by ICCV 2023! |
| Mar 2023 | One paper on Backdoor Cleansing accepted by CVPR 2023! A preliminary version appears in BANDS workshop as Oral Talk. |
| Feb 2023 | Attended AAAI 2023 and presented one paper on Domain Adaptation at Washington, DC. |
selected publications
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Mask and Restore: Blind Backdoor Defense at Test Time with Masked Autoencoder
Tao Sun, Lu Pang, Chao Chen, and Haibin Ling
arXiv 2023 | arXiv • Code
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Local Context-Aware Active Domain Adaptation
Tao Sun, Cheng Lu, and Haibin Ling
ICCV 2023 | Paper • arXiv • Code
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Backdoor Cleansing with Unlabeled Data
Lu Pang, Tao Sun, Haibin Ling, and Chao Chen
CVPR 2023 | Paper • arXiv • Code
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Domain Adaptation with Adversarial Training on Penultimate Activations
Tao Sun, Cheng Lu, and Haibin Ling
AAAI 2023 | Oral Presentation • Paper • arXiv • Code
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Prior Knowledge Guided Unsupervised Domain Adaptation
Tao Sun, Cheng Lu, and Haibin Ling
ECCV 2022 | Paper • arXiv • Code
industry experience
Applied Scientist Intern, Amazon Shopping (May 2024 - Aug. 2024)
Multimodal LLM, Instruction tuning
Machine Learning Engineer Intern, Adobe DX (May 2023 - Aug. 2023)
Time series forecasting
Machine Learning Engineer, Ant Group (July 2018 - July 2019)
Recommender system
Software Engineer Intern, Baidu NLP (Sept. 2017 - Dec. 2017)
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