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Affinity Workshop
Queer in AI @ ICML 2022 Affinity Workshop
Huan Zhang · Arjun Subramonian · Sharvani Jha · William Agnew · Krunoslav Lehman Pavasovic

Sat Jul 23 06:15 AM -- 12:00 PM (PDT) @ Room 337 - 338
Event URL: https://sites.google.com/view/queer-in-ai/icml-2022 »

Queer in AI’s demographic survey reveals that most queer scientists in our community do not feel completely welcome in conferences and their work environments, with the main reasons being a lack of queer community and role models. Over the past years, Queer in AI has worked towards these goals, yet we have observed that the voices of underrepresented queer communities, especially transgender, non-binary folks and queer BIPOC folks have been neglected. The purpose of this workshop is to highlight issues that these communities face by featuring talks and panel discussions on the inclusiveness of non-Western non-binary identities; and Black, Indigenous, and Pacific Islander non-cis folks. Additionally, this proposal outlines making virtual/hybrid conferences more inclusive of queer folks.

Author Information

Huan Zhang (CMU)
Arjun Subramonian (University of California, Los Angeles)

Hello! I am a PhD student at UCLA conducting machine learning research, advised by Prof. Yizhou Sun. I also work with Prof. Kai-Wei Chang. My research is broadly about graph representation learning, self-supervised learning, and fairness.

Sharvani Jha (University of California, Los Angeles)
William Agnew (University of Washington)
Krunoslav Lehman Pavasovic (ETH Zurich)

MSc student in Statistics at ETH Zurich/Organizer at QueerInAI/Researcher at INRIA - Sierra

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