“It’s not what we were trying to get at, but I think maybe it should be” learning how to do trauma-informed design with a data donation platform for online dating sexual violence
May 11, 2024·,,
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0 min read
Wenqi Zheng
Emma Walquist
Isha Datey
Xiangyu Zhou
Kelly Berishaj
Melissa Mcdonald
Michele Parkhill
Dongxiao Zhu
Douglas Zytko
Type
Publication
In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems

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!