De-Arteaga, Maria

Prof. De-Arteaga holds a Ph.D. in Machine Learning and Public Policy from Carnegie Mellon University, where she also earned an M.S. in Machine Learning. Prior to that, she completed her undergraduate studies in Mathematics at Universidad Nacional de Colombia.

Her research focuses on human-centered machine learning ML and artificial intelligence AI, with particular emphasis on algorithmic fairness and human-AI augmentation. Her work characterizes the risks of algorithmic bias and proposes novel algorithms and sociotechnical interventions to mitigate those risks. She also seeks to understand how humans interact with algorithms and to develop systems that foster human-AI collaboration. Her work is driven by a belief in our collective agency and responsibility to shape the technologies we build or adopt. 

Reflecting the interdisciplinary nature of her work, her research has been published in top venues across domains, including journals such as Management Science, Production & Operations Management, Data Mining & Knowledge Discovery, and Big Data & Society, as well as premier computer science conferences such as CHI, IJCAI, WWW, CSCW, and FAccT, among others. Her research has received funding awards from various organizations including NIH, Microsoft, and Google.

Before joining ESADE, she was an Assistant Professor in the Information, Risk, and Operations Management Department at the University of Texas at Austin, McCombs School of Business. From 2022 to 2025, she served as a member of the Executive Committee of the ACM Conference on Fairness, Accountability, and Transparency FAccT.