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ABOUT ME

I am a Machine Learning a Provost STEMJazz Postdoctoral Fellow at Brown University in Biostatistics with Dr. Rebecca Hubbard. She earned her Ph.D. in Computer Science from the University of Illinois Chicago, under the mentorship of Dr. Mesrob I. Ohannessian. I am a recipient of several prestigious fellowships, including the Bill and Melinda Gates Millennium Scholarship, NSF Bridge to Doctorate Fellowship, GEM Fellowship, and Google + Black in Robotics (BiR) Fellowship.

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My core questions of interest include:

 

1. How can we define and measure non-linear, non-separable harms (often tied to demographic features) in high-stakes contexts? How can we design optimization objectives that explicitly compensate for such harms?

2. How can we leverage the intersectional nature of demographic/clinical/environmental features to identify, target, and mitigate sub-optimal downstream predictions/outcomes?

3. How might intentional interventions (i.e, compensatory justice: compensation of harms) aid in expanding/correcting the shape/scope of the prediction space for a model?

4. How can we evaluate if ML systems are reducing structural barriers to access in high-stakes contexts, using justice rather than traditional equality/equity standards (i.e, parity)?

 

I graduated as a part of the Dual Degree Engineering Program at Spelman College, where I studied Computer Science, and Auburn University, where I studied Computer Engineering.

Kenya S. Andrews, Ph.D.
Photograph by: Royal Photography

RESEARCH INTERESTS

Artificial Intelligence Ethics & Justice

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Machine Learning

Algorithmic Justice

EDUCATION

2013-2017

Spelman College​

Dual Degree Computer Science & Engineering, BS

2017-2019

Auburn Univeristy

Computer Engineering, BCMPE

2020 - 2025

University of Illinois Chicago

Computer Science, Ph.D.

Human-Robot Interaction

Ethical Algorithms

HIGHLIGHTED UPDATES + NEWS

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  • Invited Talk: Spelman College  | April 2026

  • Workshop: LLM Unplugged NSBE Workshop with Dr. Sarah Brown [ Check out our resource guide artifact here]

  • Awarded: Data Science Institute Seed Grant | Jan 2026

  • Invited Talk: Howard University  | Oct 2025

  • Started Postdoctoral Research at Brown University! WHOOT WHOOT! 🐻 | July 2025

  • Awarded: Spelman Alumna 40 under 40 2025!

  • **Plenary Talk**: Equity and the Societal Implications of Global Technologies Cluster Symposium, New York University (NYU) | April 2025

  • Invited Talk: UIC EIEP First Gen: Navigating Graduate School | March 2025

  • DISSERTATION SUCCESSFULLY DEFENDED!!! WHOOT WHOOT! | March 2025

  • Paper accepted at AAAI Workshop - DOCU@AAAI-25! | Jan 2025

  • Invited Talk: ENGIE SA Keynote Panelist: Ethics and AI | November 2024

  • Invited Talk: EAAMO Keynote Panelist: Decolonizing STEM Curriculum | October 2024

  • PhD Candidacy Passed!!! | March 2024

  • Awarded: Google + BlackinRobotics Fellowship! | August 2023

  • Poster Presentation: CRA-WOMEN in San Francisco, CA | April 2023

  • Invited Talk: UIC ECE 418 in Chicago, IL | April 2023

  • Invited Talk: UIC ECE 394 in Chicago, IL | March 2023

  • Lightening Talk: CRA-IDEALS in Honolulu, HI | March 2023

  • Oral Presentation: LSMRCE'22 in Schaumburg, IL | October 2022

  • Oral Presentation: EAAMO'22 in Washington D.C. | October 2022

  • Awarded: GEM Fellowship! | August 2022

  • Invited Talk: PTC and Rockwell Automation Keynote Panelist: Technology As an Equalizer | Feb 2022

  • Sat on Diverse Voices Panel for Trustworthy Machine Learning Textbook | Jan 2022

  • Awarded: NSF Bridge to Doctorate Fellowship! | August 2021​​

  • Poster Presentation: Women in Data Science (WiDS) Cambridge | "Equity, Access, and Vulnerability in COVID-19 Vaccine Allocation" | Poster Presenter | March 2021

  • Invited Talk: Silicon Valley Robotics: Society, Robots, and Us: Inclusive Robotics | Panelist | January 2021

  • Started Grad School at the University of Illinois at Chicago in the DICE Lab!!! WHOOT WHOOT! 🔥| August 2020

PUBLICATIONS

  • Kenya S. Andrews, Lili Yan, Francisco Enrique Vicente Castro, Benjamin Xie, Jaemarie Solyst. 2025. A Note from the Advisory Board. Journal of Computing in Higher Education. DOI: 10.1007/s12528-025-09480-2

  • Kenya S. Andrews. 2025. Moving from Fairness to Justice: Intentional Algorithmic Solutions Through an Intersectional Lens. ACM Interactions Vol. 32, Issue 5, Pages 58–60. https://doi.org/10.1145/3760549

  • Kenya S. Andrews, Deborah D. Kanubala* (co-first author), Kehinde Aruleba, Francisco E.V. Castro, Renata A. Revelo. 2025. A Justice Lens on Fairness and Ethics Courses in Computing Education: LLM-Assisted Multi-Perspective and Thematic Evaluation. arXiv preprint arXiv:2510.18931, Under Review for Peer-Reviewed Publication. 

  • Kenya S. Andrews. 2025. Finally Seen: Algorithmic Solutions to Access & Injustice through Proper Visibility. University of Illinois Chicago. Thesis. 

  • Kenya S. Andrews and Lamogha Chiazor. 2025. Epistemological Bias As a Means for the Automated Detection of Injustices in Text. In Proceedings of the Workshop on Document Understanding and Intelligence at the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), Philadelphia, Pennsylvania. AAAI Conference on Artificial Intelligence (AAAI).

  • Kenya S. Andrews, Mesrob I. Ohannessian, and Elena Zheleva. See Me and Believe Me: Causality and Intersectionality in Testimonial Injustice in Healthcare. arXiv preprint arXiv:2410.01227. Under Review for Peer-Reviewed Publication. 

  • Kenya S. Andrews, Bhuvni Shah, and Lu Cheng. 2023. Intersectionality and Testimonial Injustice in Medical Records. In Proceedings of the 5th Clinical Natural Language Processing Workshop, pages 358–372, Toronto, Canada. Association for Computational Linguistics (ACL).

  • Kenya S. Andrews, Mesrob Ohannessian, and Tanya Berger–Wolf. 2022. Modeling Access Differences to Reduce Disparity in Resource Allocation. In Proceedings of the 2nd Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '22). Association for Computing Machinery, Article 17, 1–11. 

  • Girmaw Abebe Tadesse, Celia Cintas, Roxana Daneshjou, Kush Varshney, Peter Staar, Skyler Speakman, Kenya S. Andrews et al. 2021. Racial Representation Analysis in Dermatology Academic Materials. In American Medical Informatics Association (AMIA) Annual Symposium. San Diego, CA

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