Short Bio

Ashwin Singh (she/they) is a PhD student at TU Wien, working on problems at the intersection of fair machine learning and theoretical computer science. Previously, they earned their MSc. in Artificial Intelligence from Universitat Pompeu Fabra in Barcelona, graduating as valedictorian. Their masters thesis contributed the first algorithm for accurately determining post-release outcomes in Catalonia, now used by the state government to compute criminal recidivism statistics. Prior to that, she served as the first DEI Admin of Queer In AI, where her work won the best paper award at FAccT 2023. Additionally, she has published in leading venues including AIES, Hypertext and ICTD. She has also worked as a machine learning engineer in the travel industry, building recommendation systems that now serve millions of users.

PhD Project – Fair and Representative Clustering for Data Summarization

Supervised by Stefan Neumann (TU Wien, Informatics)

Clustering is widely used in data summarization systems (e.g. web search and personalization) to produce representations consumed by society. Yet, such systems (and more broadly, representational harms) remain under-scrutinized by the EU AI Act. To address this gap, Ashwin’s research aims to develop efficient and practical algorithms that produce provably fair and representative clusterings.

Publications

• Ashwin Singh and Organizers Of Queerinai. Queer In AI: A Case Study in Community-led Participatory AI. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT ’23, page 1882–1895, New York, NY, USA, 2023. Association for Computing Machinery. ISBN 9798400701924. doi: 10.1145/3593013.3594134.

• Nathan Dennler, Anaelia Ovalle, Ashwin Singh, Luca Soldaini, Arjun Subramonian, Huy Tu, William Agnew, Avijit Ghosh, Kyra Yee, Irene Font Peradejordi, Zeerak Talat, Mayra Russo, and Jess De Jesus De Pinho Pinhal. Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms. In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, AIES ’23, page 375–386, New York, NY, USA, 2023. Association for Computing Machinery. ISBN 9798400702310. doi: 10.1145/3600211.3604682.

• Ashwin Singh, Arvindh Arun, Pulak Malhotra, Pooja Desur, Ayushi Jain, Duen Horng Chau, and Ponnurangam Kumaraguru. Erasing labor with labor: Dark Patterns and Lockstep Behaviors on Google Play. In HT ’22: Proceedings of the 33rd ACM Conference on Hypertext and Social Media, New York, NY, USA, 2022. ACM. ISBN 9781450392334. doi: 10.1145/3511095.3536368.