Kunal Handa

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I am a Research Scientist and Member of the Technical Staff at Anthropic. I focus on improving the societal impact of AI systems.

Previously, I was an MSc by Research student at the University of Oxford advised by Yarin Gal. Before that, I was a linguistics and computer science undergrad at Brown University working with Ellie Pavlick and Chen Sun. I also spent two summers at the Stanford NLP Group and Stanford CoCoLab advised by Diyi Yang, Dora Demszky, and Noah Goodman with whom I continue to collaborate frequently.

You can contact me at: kunal [underscore] handa [at] alumni [dot] brown [dot] edu.

Publications, Preprints, and Blog Posts

Anthropic Education Report: How University Students Use Claude
Kunal Handa*, Drew Bent** denotes equal contribution., Alex Tamkin, Miles McCain, Esin Durmus, Michael Stern, Mike Schiraldi, Saffron Huang, Stuart Ritchie, Steven Syverud, Kamya Jagadish, Margaret Vo, Matt Bell, Deep Ganguli. Anthropic, 2025.

Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations
Kunal Handa*, Alex Tamkin*, Miles McCain, Saffron Huang, Esin Durmus, Sarah Heck, Jared Mueller, Jerry Hong, Stuart Ritchie, Tim Belonax, Kevin K. Troy, Dario Amodei, Jared Kaplan, Jack Clark, Deep Ganguli. Under review, 2025.

Clio: Privacy-Preserving Insights into Real-World AI Use
Alex Tamkin*, Miles McCain*, Kunal Handa, Esin Durmus, Liane Lovitt, Ankur Rathi, Saffron Huang, Alfred Mountfield, Jerry Hong, Stuart Ritchie, Michael Stern, Brian Clarke, Landon Goldberg, Theodore R. Sumers, Jared Mueller, William McEachen, Wes Mitchell, Shan Carter, Jack Clark, Jared Kaplan, Deep Ganguli. Under review, 2024.

Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy
Benedict A. Tjandra, Muhammed Razzak, Jannik Kossen, Kunal Handa, Yarin Gal. In the Safe Generative AI Workshop, Conference on Neural Information Processing Systems (NeurIPS), 2024.

Bayesian Preference Elicitation with Language Models
Kunal Handa, Yarin Gal, Ellie Pavlick, Noah Goodman, Jacob Andreas, Alex Tamkin*, Belinda Z Li*. Under review, 2024.

“Mistakes Help Us Grow”: Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms
Kunal Handa, Margarett Clapper, Jessica Boyle, Rose E Wang, Diyi Yang, David S Yeager, Dorottya Demszky. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

Emergence of Abstract State Representations in Embodied Sequence Modeling
Tian Yun*, Zilai Zeng*, Kunal Handa, Ashish V Thapliyal, Bo Pang, Ellie Pavlick, Chen Sun. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.

Task Ambiguity in Humans and Language Models
Alex Tamkin*, Kunal Handa*, Avash Shrestha, Noah Goodman. In the International Conference on Learning Representations (ICLR), 2023.

Peekbank: An open, large-scale repository for developmental eye-tracking data of children's word recognition
Martin Zettersten, Daniel Yurovsky, Tian Linger Xu, Sarp Uner, Angeline Sin Mei Tsui, Rose M. Schneider, Annissa N. Saleh, Stephan C. Meylan, Virginia A. Marchman, Jessica Mankewitz, Kyle MacDonald, Bria Long, Molly Lewis, George Kachergis, Kunal Handa, Benjamin deMayo, Alexandra Carstensen, Mika Braginsky, Veronica Boyce, Naiti S. Bhatt, Claire Augusta Bergey, Michael C. Frank.outside of the position of the first and the last author, authorship position was determined by sorting authors' last names in reverse alphabetical order. In Behavior Research Methods (BRM), 2022.

Other Writing

The Role of Technology in Elections: The Voyage of Voters' Data
Kunal Handa. In Conduit, the Brown University Computer Science Annual Magazine, Volume 32, 2022.

Trying to Give a Shit About "Give a Shit": A Compositional Semantics Perspective
Kunal Handa

Teaching

At Brown, I served as the Socially-Responsible Computing Teaching Assistant for CS1470: Deep Learning. I designed contentsome of which is available via the course website on deep learning's potential societal harms and conducted exercises that examined ethical frameworks, the cyclical nature of language models' biases, and the pros and cons of regulating ML advancements.

As a senior, I founded and led Brown's Explainable AI Reading Group. We presented and discussed topics across language modeling, reinforcement learning, computer vision, and multi-agent systems literature.

I also tutor incarcerated and previously incarcerated individuals in HiSET test preparation and essay writing. Intermittently, I teach group classes such as Applying to College and Introduction to Philosophy at juvenile detention centers.