Towards Trauma-Informed Data Donation of Sexual Experience in Online Dating to Improve Sexual Risk Detection AI
October 29, 2023·,,
,,,,,·
0 min read
Wenqi Zheng
Emma Walquist
Isha Datey
Xiangyu Zhou
Kelly Berishaj
Melissa Mcdonald
Michele Parkhill
Dongxiao Zhu
Douglas Zytko
Type
Publication
Adjunct Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology

Authors
Xiangyu Zhou
(he/him)
Ph.D. Candidate in Computer Science
I am a Ph.D. candidate in Computer Science at Wayne State University, advised by Prof. Dongxiao Zhu in the Trustworthy AI Lab. My research focuses on trustworthy AI: making AI systems robust and aligned so they can be deployed safely.
I work across large language models (LLMs), large reasoning models (LRMs), and agentic AI, spanning safety alignment, fine-tuning, reinforcement learning, in-context learning, and machine unlearning. My work has been published at venues including NeurIPS, ICLR, CVPR, and AAAI (oral). In industry, I worked on generative retrieval as an AI/ML engineer intern at LinkedIn.
I am always happy to connect with others working on trustworthy AI. Feel free to reach out!