Angelina Wang

Assistant Professor, Cornell University

Joined

February 2020

Names

Angelina Wang (Preferred)

Emails

****@gmail.com (Confirmed)

****@berkeley.edu (Confirmed)

****@princeton.edu (Confirmed)

****@alumni.princeton.edu (Confirmed)

****@stanford.edu (Confirmed)

****@cornell.edu (Confirmed)

Personal Links

Career & Education History

Assistant Professor

Cornell University (cornell.edu)

2025 – Present

Postdoc

Stanford University (stanford.edu)

2024 – 2025

PhD student

Princeton University (princeton.edu)

2019 – 2024

Undergrad student

University of California Berkeley (berkeley.edu)

2015 – 2019

Advisors, Relations & Conflicts

PhD Advisor

Olga Russakovsky

Present

Expertise

machine learning fairness

Present

algorithmic bias

Present

Publications

Who Measures What Matters? An Analysis of Social Impact Evaluations in Foundation Model Reporting
Anka Reuel, Avijit Ghosh, Jenny Chim, Srishti Yadav, Usman Gohar, Jennifer Mickel, Andrew Tran, Pawan Sasanka Ammanamanchi, Mowafak Allaham, Hossein A. Rahmani, Mubashara Akhtar, Felix Friedrich, Robert Scholz, Michael Alexander Riegler, Jan Batzner, Eliya Habba, Arushi Saxena, Anastassia Kornilova, Kevin Wei, Prajna Soni et al. (13 additional authors not shown)
- ICLR 2026 Conference Desk Rejected Submission
- Readers: Everyone
Measurement to Meaning: A Validity-Centered Framework for AI Evaluation
Olawale Elijah Salaudeen, Anka Reuel, Ahmed M Ahmed, Suhana Bedi, Zachary Robertson, Sudharsan Sundar, Benjamin W. Domingue, Angelina Wang, Sanmi Koyejo
- NeurIPS 2025 LLM Evaluation Workshop Poster
- Readers: Everyone
Challenges to Grassroot Organization Engagement with AI Policy
Jennifer Mickel, Carter Buckner, William Agnew, Yanan Long, Michelle Lin, B.V. Alaka, Angelina Wang, Sarthak Arora, Nandhini Swaminathan, Arjun Subramonian
- ACA-NeurIPS2025 Oral
- Readers: Everyone
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn, Angelina Wang, Fernando Diaz, Flavio Calmon, Margaret Mitchell, Michael Ekstrand, Reuben Binns, Solon Barocas
- NeurIPS 2025 Position Paper Track
- Readers: Everyone
Fallacies of Data Transparency: Rethinking Nutrition Facts for AI
Judy Hanwen Shen, Ken Liu, Angelina Wang, Sarah H. Cen, Andy K Zhang, Caroline Meinhardt, Daniel Zhang, Kevin Klyman, Rishi Bommasani, Daniel E. Ho
- ICML 2025 Workshop TAIG Poster
- Readers: Everyone
Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
Hanna Wallach, Meera Desai, A. Feder Cooper, Angelina Wang, Chad Atalla, Solon Barocas, Su Lin Blodgett, Alexandra Chouldechova, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Nicholas J Pangakis, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
- ICML 2025 Position Paper Track poster
- Readers: Everyone
Measuring Implicit Bias in Explicitly Unbiased Large Language Models
Xuechunzi Bai, Angelina Wang, Ilia Sucholutsky, Thomas L. Griffiths
- NeurIPS 2024 Workshop on Behavioral ML
- Readers: Everyone
Large language models cannot replace human participants because they cannot portray identity groups
Angelina Wang, Jamie Heather Morgenstern, John P Dickerson
- OpenReview Archive Direct Upload
- Readers: Everyone
Strategies for Increasing Corporate Responsible AI Prioritization
Angelina Wang, Teresa Datta, John P. Dickerson
- CoRR 2024
- Readers: Everyone
Evaluating Generative AI Systems is a Social Science Measurement Challenge
Hanna M. Wallach, Meera A. Desai, Nicholas Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alexandra Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs
- CoRR 2024
- Readers: Everyone

View all 42 publications

Co-Authors

View all 121 co-authors