Queer in AI @ NeurIPS 2025: Organizers

• William Agnew (he/they) (william.agnew@ostem.org): William Agnew is a CBI postdoc fellow at CMU. His research covers AI ethics, participatory design, critiques of AI, queerness and AI, and resistance and AI. He received his PhD from University of Washington. His work had been recognized by three paper awards at FaccT and CHI, and covered by outlets including the Washington Post, Wired, and MIT Tech Review.

• Franziska Sofia Hafner (she/her) (Franziska.Hafner@oii.ox.ac.uk): Sofia is a Research Assistant at the University of Oxford, where she will be starting a PhD in October 2025. Her research lives at the intersection of Computer Science and Social Science, with a specific focus on algorithmic fairness.

• Michelle Lin (she/her) (Michelle.lin2@mail.mcgill.ca) : Michelle is a Research Assistant and Masters student at the University of Montreal and Mila - Quebec AI Institute. Her research uses deep learning, remote sensing, and computer vision for climate change mitigation applications. At Queer in AI, she helps organize workshops and events.

• Ankush Gupta (he/they) (ankushg0405@gmail.com): Ankush is a research assistant at the Centre for Human Centred Computing at IIIT-Delhi. He focuses his research on Human-Centred AI and edge computing. His research involves utilising deep learning and natural language processing to develop algorithms that improve human interaction and mitigate user biases to make AI systems more inclusive and effective.

• Zhendong Li (he/they) (zhl923@lehigh.edu): Zhendong Li, is a second-year PhD student in the ISE department of Lehigh University and he received his Bachelor of Science degree in Mathematics and Applied Mathematics at Shanghai University in 2023. His research interests mainly focus on optimal control problems governed by partial differential equations and saddle point systems.

• Nikolay Malkin (they/any) (https://malkin1729.github.io) is a Chancellor's Fellow in Informatics at the University of Edinburgh and a Fellow of CIFAR's Learning in Machines and Brains programme. Their research foci include probabilistic machine learning, generative models, and neurosymbolic methods for reasoning in language and formal systems. A mathematician by training and a Bayesian by conviction, they are committed to diversity-aware agent design and to challenging the perpetuation of all oppressive categories in science and beyond.