About Me

I am Mehmet Eren Ahsen, an Assistant Professor in the Gies College of Business at the University of Illinois Urbana-Champaign. I am also a Health Innovation Professor in Biomedical and Translational Sciences at the Carle Illinois College of Medicine. This role brings together my interests in healthcare, artificial intelligence, medical decision-making, and interdisciplinary innovation.

My research sits at the intersection of machine learning, healthcare, information systems, and operations. I develop and apply data-driven methods to help organizations and decision makers make better use of complex data, with a particular interest in healthcare, society, and high-stakes decision environments. My work brings together machine learning, causal inference, computational biology, and decision analytics, with an emphasis on problems where rigorous methods need to be combined with an understanding of the institutional and human context in which decisions are made.

This perspective has led me to work on topics ranging from healthcare AI and clinical decision support to drug combinations, cancer biology, crowdsourcing, platform regulation, and data-driven social science. Across these projects, I am particularly interested in moving beyond prediction toward explanation, causal understanding, calibrated decision support, and interpretable analytics.

I have a strong mathematical and engineering background. I received two bachelor’s degrees from Middle East Technical University, one in Electrical and Electronics Engineering and another in Mathematics. Studying mathematics alongside engineering gave me a foundation that continues to shape the theoretical side of my research and my approach to developing analytical methods.

I received my M.S. degree in Control Theory from Bilkent University, where I worked with Prof. Hitay Ozbay. I then moved to the University of Texas at Dallas for my Ph.D., where I worked with Prof. Mathukumalli Vidyasagar on topics including machine learning, compressed sensing, and computational biology. This training shaped my interest in developing rigorous mathematical and computational approaches to real-world problems.

After my Ph.D., I joined IBM as a postdoctoral researcher, where I worked with Gustavo Stolovitzky on crowdsourcing, machine learning, and cancer biology. That experience broadened my research toward collaborative and data-intensive approaches and gave me the opportunity to work at the intersection of computation, biology, and large-scale scientific discovery.

Before joining Gies, I was an assistant professor at the Icahn School of Medicine at Mount Sinai, where I spent two years working in a medical-school environment. That experience deepened my interest in healthcare applications and in understanding how machine learning methods can be translated into meaningful decisions in clinical and organizational settings.

My current work continues to build bridges between business, medicine, engineering, and data science. Through my role at Carle Illinois, I have the opportunity to engage with an engineering-based medical education environment and contribute to interdisciplinary efforts focused on healthcare innovation and medical education.

Ultimately, I enjoy working on problems where new analytical methods can make a concrete difference: improving how decisions are made, uncovering mechanisms that are otherwise difficult to see in data, and helping translate advances in artificial intelligence and quantitative methods into useful applications.

For a current list of my publications and scholarly work, please visit my Google Scholar profile.