Maria De-Arteaga is an assistant professor at The University of Texas at Austin’s McCombs School of Business. She is also a core member of the Machine Learning Laboratory and a Good Systems researcher. She has taught courses on programming and AI ethics, and she serves as a Ph.D. adviser for students in the IROM Ph.D. Program and in other departments across campus, such as Computer Science.

De-Arteaga’s academic research focuses on algorithmic fairness and human-AI complementarity. She seeks to characterize and mitigate risk of algorithmic biases, and to develop algorithms and sociotechnical interventions to improve AI-supported decision making.

Her work has been published in top computer science conferences such as ACM Conference on Human Factors in Computing Systems (CHI), ACM Web Conference (WWW), International Joint Conference on Artificial Intelligence (IJCAI), ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), and ACM Conference on Fairness, Accountability, and Transparency (FAccT). Her research is in top journals across domains, including Data Mining and Knowledge Discovery, Production and Operations Management, Critical Care Medicine, Resuscitation, and Big Data and Society. She has been consulted as an expert by CNN, The New York Times, and The Wall Street Journal to discuss bias in artificial intelligence, and she has given keynotes at Harvard HDSI Annual Conference, MIT Lincoln Laboratory, Facebook, the International Conference on AI for People (CAIP), a UNESCO Tech4Dev Conference session, and the Colombian Mathematical Congress.

Prior to joining McCombs, De-Arteaga worked in investigative journalism. She has written pieces on the threats faced by Colombian social leaders, sexual violence in El Salvador, and algorithms and crime.

De-Arteaga earned a B.S. in mathematics from Universidad Nacional de Colombia and an M.S. in machine learning from Carnegie Mellon University, where she also earned a joint Ph.D. in machine learning and public policy.