Stanford University
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Jens Hainmueller
Kimberly Glenn Professor and Professor of Political Science
BioJens Hainmueller is the Kimberly Glenn Professor of Political Science and Director of Graduate Studies in Stanford University’s Department of Political Science. He co-directs the Stanford Immigration Policy Lab and is a Faculty Affiliate at the Stanford Center for Causal Science, the Institute for Human-Centered Artificial Intelligence, and the Europe Center. He is also a member of the Maternal & Child Health Research Institute at Stanford’s School of Medicine.
Hainmueller’s research spans statistical methods, causal inference, immigration, and political economy, and he has published nearly 70 articles with over 40,000 citations. Many of his works appear in top journals, including Science, Nature, and PNAS, as well as leading field journals in political science, statistics, economics, and business.
He has developed widely adopted statistical methods—such as synthetic control methods, entropy balancing, Average Marginal Component Effects, and GeoMatch algorithms—and created several open-source software packages that support empirical research across disciplines. At Stanford, he teaches courses on causal inference and data science.
Hainmueller’s contributions have earned him prestigious awards, including the Gosnell Prize for Excellence in Political Methodology, the Warren Miller Prize, the Robert H. Durr Award, and the Emerging Scholar Award from the Society of Political Methodology. He is an Andrew Carnegie Fellow, an elected Fellow of the Society of Political Methodology, and holds an honorary degree from the European University Institute (EUI).
He earned his PhD from Harvard University, with additional studies at the London School of Economics, Brown University, and the University of Tuebingen. Before joining Stanford, he was a faculty member at the Massachusetts Institute of Technology (MIT).
For a full list of his publications, please refer to his Google Scholar Citation Page and CV. -
belal hakim
Clinical Assistant Professor (Affiliated), Medicine - Med/Nephrology
BioBelal grew up in Fremont and later lived in Singapore where he completed his secondary education. He received his bachelors in Biological Psychology and then his medical degree from Tufts University. He completed his internal medicine and chief residency at Santa Clara Valley Medical Center which solidified his interest in care for the medically underserved. His current research interests include improving diuretic management in advanced CKD and hemodialysis as well as CKD care for underserved communities
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Michael Halaas
Associate Dean and Chief Operating Officer, SoM, Chief Operating Officer - Operations
Current Role at StanfordIn my role as Chief Operating Officer and Associate Dean, I provide oversight and strategic leadership of the operations of the School of Medicine. This includes developing and leading the execution of major strategic initiatives and ensuring foundational operations are rigorous and effectively support the tripartite missions of Education, Research and Patient Care. I am a member of the Dean's leadership team and a representative of the School of Medicine in a variety of forums throughout Stanford and externally
I also co-lead the Stanford Medicine Catalyst program with Dr. Euan Ashley. We focus on discovering, supporting and propelling healthcare innovation from within the Stanford community. When these innovations are ready, we assist in the commercialization and scaling to reach maximum impact and improve human health. https://smcatalyst.stanford.edu
The combination of these roles provides a unique opportunity to work at the forefront of transformative health innovation and the operations of complex academic medical center ecosystem. -
Lou Halamek
Professor of Pediatrics (Neonatology) and, by courtesy, of Obstetrics and Gynecology
Current Research and Scholarly Interests1. development of hospital operations centers coupled with sophisticated simulation capabilities
2. re-creation of near misses and adverse events
3. optimizing human and system performance during resuscitation
4. optimizing pattern recognition and situational awareness at the bedside
5. evaluation and optimization of debriefing
6. patient simulator design
