Professor of Computer Science and Statistics, Committee on Computational and Applied Mathematics
Rebecca Willett is a Professor of Statistics and Computer Science at the University of Chicago. Willett’s work in machine learning and signal processing in the natural sciences reflects broad and interdisciplinary expertise and perspectives. She is known internationally for her contributions to the mathematical foundations of machine learning in the natural sciences and computational imaging, with nearly two hundred book chapters and scientific articles in top-tier journals and conference proceedings at the intersection of machine learning, signal processing, statistics, mathematics, and optimization. Willett’s work in this space has had important implications in materials science, astronomy, climate science, national security, medical imaging, and several other fields. Her group has made contributions both in the mathematical foundations of signal processing and machine learning and in their application to a variety of real-world problems in STEM. In addition to her technical contributions, Willett is a strong advocate for diversity in STEM and AI and has organized multiple events to support women in middle school, as undergraduate and graduate students, and as faculty members.
Professor and Chair of Astronomy and Astrophysics; Kavli Institute of Cosmological Physics
Joshua Frieman is a Professor and Chair of the Department of Astronomy & Astrophysics at the University of Chicago, where he is a Senior Member of the Kavli Institute for Cosmological Physics. He is also a Distinguished Scientist and former Head of the Particle Physics Division at Fermilab. Frieman’s research spans theoretical and observational cosmology, including studies of the early universe, large-scale structure, gravitational lensing, supernovae, dark matter and dark energy. His research has increasingly relied on the use of machine learning techniques in the analysis of cosmic surveys, e.g., in estimating photometric redshifts, in automated artifact filtering of astronomical time-domain images, and in the discovery and modeling of strong gravitational lens systems. The co-author of over 600 publications, he was a co-founder and later Director of the Dark Energy Survey (DES), an international collaboration of 500 scientists from 25 institutions in 7 countries that carried out a six-year survey to map the Universe using a 570-megapixel camera it built for a 4-meter telescope in Chile. DES has cataloged several hundred million galaxies and discovered several thousand supernovae, yielding state-of-the-art measurements of cosmological parameters. Frieman previously played leadership roles in the Sloan Digital Sky Survey (SDSS) and led the SDSS-II Supernova Survey. Over 30 years, he has mentored over 40 postdocs and 20 graduate students at UChicago and Fermilab. He is active in outreach through public lectures (his “Probing the Dark Universe” has 7.5 million views on YouTube), K-12 school presentations, podcast interviews, and venues such as the World Science Festival. He is actively engaged in improving diversity and inclusion in STEM institutions.
Professor of Neurobiology, Committees on Computational Neuroscience and Neurobiology
David Freedman is a Professor in the Department of Neurobiology and the Neuroscience Institute at the University of Chicago. He has a broad background in cognitive, systems, and computational neuroscience, with expertise in electrophysiological approaches for recording neuronal population activity in awake non-human primates trained to perform complex behavioral tasks which require learning, memory, and decision-making. His research program also has a major focus on artificial intelligence (AI) approaches for studying neuroscience-related questions in artificial neural networks, and on designing novel biologically-inspired AI approaches. His research, supported by NIH, NSF, DOD, and private foundations, investigates the neuronal computations of higher-order perceptual and cognitive functions. Following graduate and postdoctoral training at MIT and Harvard Medical School, he established his laboratory at the University of Chicago in 2008, from which he has trained numerous graduate students and postdoctoral scholars that have successfully established their own independent research careers. His work has been recognized by the Troland Research Award from the National Academy of Sciences, the Vannevar Bush Faculty Fellowship from the Department of Defense, the NSF Career Award, and Faculty Fellowship Awards from the Sloan, McKnight, and Brain Research Foundations. In 2018, he received the University of Chicago Faculty Award for Excellence in Graduate Teaching and Mentoring.
Simona Ahmed is the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Administrator at the University of Chicago, responsible for leading the program administratively and supporting selected postdoctoral scholars in using AI methods to improve their research activities. She works closely with faculty leadership, manages budget and project schedules, and develops partnerships across divisions and national laboratories. Simona previously served as Associate Director of the Office of Academic Affairs at the University of Chicago for over eight years, providing support and expertise to 23 basic science departments in recruitment and faculty appointments. She managed systems and processes related to academic recruiting, collaborated with various university offices, and contributed to strategic planning. Simona’s prior industry leadership roles include Director of Training and Contact Center at Planned Parenthood, Trainer at SXC, Behavior Counselor Supervisor at Mayo Clinic in Rochester, and Behavior Analyst at Laura Baker Services Association. Overall, Simona has a diverse background in both industry and academic administration, contact center management, and training, with a focus on supporting leadership in leading programs and improving operational efficiency.
Fellow Selection Committee:
- Joshua Frieman (Committee Chair), Astronomy and Astrophysics
- Junhong Chen, Molecular Engineering
- Aaron Dinner, Chemistry
- David Freedman, Neurobiology
- Pedram Hassanzadeh, Geophysical Sciences
- Daniel Holz, Physics and Astronomy and Astrophysics
- Jason MacLean, Neurobiology
- Catherine Pfister, Ecology and Evolution
- Tiffany Shaw, Geophysical Sciences
- Rebecca Willett, Statistics and Computer Science
Mentorship & Evaluation Committee:
- David Freedman (Committee Chair), Neurobiology
- Seppe Kuehn, Ecology and Evolution
- Elisabeth Moyer, Geophysical Sciences
- Daniel Nicolae, Statistics and Human Genetics
- Vincenzo Vittelli, Physics
Training & Events Committee:
- Rebecca Willett (Committee Chair), Computer Science and Statistics
- Alex Drlica-Wagner, Astronomy and Astrophysics
- Ian Foster, Computer Science and Argonne National Lab
- Robert Grossmann, Biomedical Data Science and Computer Science
- Abhishek Kumar, Imaging Science and Marine Biological Laboratory