teanna barrett

I’m Teanna Barrett (she/her), a Ph.D. student at the University of Washington Allen School of Computer Science & Engineering. I'm co-advised by Amy Zhang, PhD and Leilani Battle, PhD. I'm the recipient of the 2024 - 25 College of Engineering Dean's Fellowship, 2024 - 27 ARCS Fellowship, the 2025 - 26 Herbold Fellowship , and a member of the LEAP Alliance.

I earned my B.S. in Computer Science with a minor in Philosophy at Howard University. I'm an alum of the Howard Universiy Karsh STEM Scholars program.

Current Aim: Empower responsible data science practices by understanding, developing, and building for the praxis (theory and practice) of data scientists.

Check out the Social Futures Lab's blog to read more emerging thoughts from my colleagues and I!

Email  /  CV  /  Scholar  /  BlueSky  /  Github  /  LinkedIn

Photo of Teanna Barrett. Teanna is a woman with dark-brown skin and her locs are styled into a professional updo with a pinned side part. She is wearing large brown glasses, small gold earrings, a green ribbed sweater and a green blazer with a navy blue accent on the lapels and shoulder. She stands in front of a red and brown brick wall. Even farther in the background is a metal staircase in front of a grayish blue wall.

cv

research

My research is an interrogation of the design, deployment and evaluation of data science (including and beyond ml) as a means to understand contemporary anti-blackness and inform the design paradigms of liberatory technology. Towards this research aim I engage with the frameworks and techniques of ml ethics/fairness, social computing, critical theory, and the philosophies of the Black Diaspora. Representative papers are highlighted.

Wooden blocks of various types and colors are arranged and scuplted into the continent of Africa. The wooden piece in behind a corrugated and slightly shiny black wall.
African Data Ethics: A Discursive Framework for Black Decolonial Data Science
Teanna Barrett, Chinasa T. Okolo, B. Biira, Eman Sherif, Amy X. Zhang, Leilani Battle
ACM FAccT, 2025
proceedings / undergraduate project website

African Data Ethics: A Discursive Framework for Black Decolonial Data Science is a theoretical knowledge contribution that presents one of the first collations of African data ethics perspectives for the pluralistic AI ethics community.

A screenshot of a animated diagram to represent the relationship between skin tone and race. An iceberg drawing for above and below the water. An orange bracket labeled race includes the full iceberg. A small small dot on the surface layer of the iceberg is labeled as skin tone. A dark-brown hand with white painted nails points to the image.
Skin Deep: Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark Datasets
Teanna Barrett, Quan Ze Chen, Amy X. Zhang
ACM FAccT, 2023
project page / proceedings

Comprehensive literature review and inter-rater reliability study on manual skin tone annotations to gain insight on skin tone stratification and other social aspects of subjectivity impact the annotations.

A gif of a Kiwibot running into a table. A small, white, and prism-shaped motorized robot. The kiwibot has a long black attena and a small blue screen for pixelized emotes. The kiwibot drives across a dark green and brown carpet in a room with white walls and a tan table with various papers placed on it. As the kiwibot travels across the carpet and then hits the table. The video cuts to the emote screen of the kiwibot to show two blue x's which indicate death.
KiwiBots on Kampus: A Case Study of Neoliberal Technology in Black Spaces
Teanna Barrett
GRACE: Global Review of AI Community Ethics, 2023

A opinion piece of the ethical concerns of Kiwibots on Howard University's campus.

A gif of a young Martin Lawrence showing off his big ears. Martin is a man with dark-brown skin, close shaven and shaped hair, a mustache and goatee. He is wearing a black collared shirt and a gold watch. In the gif he uses his middle and pointer finger for each hand to lift his ears forward with an exasperated look.
Evaluating Novel Mask-RCNN Architectures for Ear Mask Segmentation
Saurav K. Aryal, Teanna Barrett, Gloria Washington
International Conference on Bioinformatics and Biomedical Science, 2022
arXiv

This paper trains and compares three newer models to the state-of-the-art MaskRCNN (ResNet 101+FPN) model across four different datasets. The Average Precision (AP) scores reported show that the newer models outperform the state-of-the-art but no one model performs the best over multiple datasets.

media [under construction]

academic service
A dark-brown person with facial hair on their chin has their arms crossed. They are wearing a white t-shirt written with VOLUNTEER across the chest in black text. Student Volunteer, FAccT 2024 & 2025
Student Volunteer, TAPIA 2024
Young woman with dark hair carrying an armful of plastic binders. Teaching Assistant, HU Intro to Computer Science, Fall 2020 (in collaboration with Google in Residence)
Graduate Research Mentor, DUB REU, Summer 2024
Graduate Research Mentor, UW CSE 492R, Winter - Spring 2025 & Winter - Spring 2026 Teaching Assistant, UW CSE 440, Fall 2025 & Winter 2026

This website is a personalized version of Jon Barron's website. Based on Barron's recommendation, also consider using Leonid Keselman's Jekyll fork of this page.