I am an Associate Professor in the Department of Data, Analytics, Technology, and Artificial Intelligence at ESADE Business School. My research focuses on human-centered machine learning (ML) and artificial intelligence (AI), with particular emphasis on human-AI augmentation and algorithmic fairness. I seeks to understand how humans interact with algorithms and to develop systems that foster human-AI collaboration. This work is complemented by research on algorithmic fairness, which characterizes the risks of algorithmic bias and proposes novel algorithms and sociotechnical interventions to mitigate those risks. My work is driven by a belief in our collective agency and responsibility to shape the technologies we build or adopt. 

Before joining ESADE, I was an Assistant Professor at the Information, Risk and Operation Management Department at McCombs School of Business at the University of Texas at Austin. From 2022 to 2025, I served as a member of the Executive Committee of the ACM Conference on Fairness, Accountability, and Transparency (FAccT). Previously, I served as co-Chair of Diversity & Inclusion for FAccT 2021-2022, and local arrangements co-Chair for WITS 2021. In 2017 I co-founded ML4D, which I co-led for five years.

Advising: I am lucky to work with many fantastic collaborators and students. I serve as a PhD co-advisor for Terry Neumann (UT Austin), and Yunyi Li (UT Austin).
Previously advised: Jakob Schoeffer (postdoc); Soumyajit Gupta (PhD, CS); Jennifer Mickel, Riya Cyriac (undergraduate).

News
11/25 – Our paper Should you use LLMs to simulate opinions? accepted to AAAI’26!

10/25 – Our paper Should you use LLMs to simulate opinions? awarded Best Paper Runner-Up Award at INFORMS ISS Cluster, 2025.

09/25 – Our paper More of the Same: Persistent Representational Harms Under Increased Representation accepted to NeurIPS’25!

08/25 – My family and I decided to leave the US and we are beginning a new chapter in Europe, where I will join ESADE.

05/25 – Our work on Perils of Label Indeterminacy accepted to FAccT’25!

04/25 – PhD student Terry Neumann will present our work on evaluating reliability of LLMs to simulate human opinions at Wharton’s AI and the Future of Work Conference.

03/25 – Our work on recovery potential in patients after cardiac arrest published in JAMA Network Open.

03/25 – PhD student Anubrata Das presenting our work on fair and accurate detection of toxic speech at the iConf.

03/25 – I was consulted as an expert for this Fast Company piece on AI literacy.