I am a professor at the McCombs School of Business, the University of Texas at Austin.
My research aims to advance machine learning and artificial intelligence methods to improve decision-making and to benefit people, organizations, and society.
My recent work focuses on trustworthy human-AI collaborative decision-making and human-AI integration. This work focuses on developing novel human- and decision-centric AI methods. My collaborators, students, and I develop AI methods that consider a rich set of human- and decision-centric goals that matter in important contexts in practice, and that both identify and then effectively take advantage of human-AI complementarities.
The integration of AI into practice has exposed not only the power of AI, but also important gaps between general-purpose methods and necessary or advantageous capabilities in many important contexts.
Over the years, my research has aimed to advance AI by bringing to bear real-world goals and challenges and the idiosyncrasies of important contexts in practice, and we develop methods that focus on goals that matter in practice, while accounting for the constraints and exploiting the opportunities presented in these environments. I have addressed challenges in broad set of domains, including health care, smart electricity grid, fraud, finance, and online labor markets.
Ph.D Students: If you are interested to work with me, please reach out to me at firstname.lastname@example.org
Below are descriptions of some of my works. See more details in my CV and Google Scholar profile.
In 2014 I co-founded Sweetch, a platform for large-scale prediction, prevention and outcome improvement of chronic diseases.