Camille Little is a PhD student in Electrical and Computer Engineering at Rice University in Houston, Texas. Her research interests include Machine Learning (ML) fairness, ML interpretability, ML ethics, optimization, and causality where Camille explores, develops, and tests new machine learning methods for algorithmic fairness. Additionally, she mentors undergraduate and early graduate students on various research projects related to ML fairness and interpretability.
In the Spring of 2021, she was awarded the National Science Foundation (NSF) Graduate Research Fellowship, which recognizes and supports those who have potential to be high achieving scientists and engineers, early in their careers. Outside of her research pursuits, she founded and now leads the Black Data Processing Associates (BDPA) Data Science Academy. The Academy aims to provide relevant data science experience for Black college students through technical workshops and professional development seminars.
Camille holds an M.S. in Electrical Engineering and a B.A. in Statistics from Rice University. During her time as an undergraduate student, she was extremely involved in the National Society of Black Engineers (NSBE), holding numerous leadership positions within Rice’s chapter of NSBE including Secretary, Fundraising Senator, and President. Moreover, she was a member of the Rice Women’s Track and Field Team, competing in Long Jump, 100m, 200m 4x1 relay, and 4x4 relay at the Division I level. She is also a proud graduate of Phillips Academy Andover.
In her free time, Camille enjoys running, walking her goldendoodle, and tutoring students in math.