Rebecca Willett is a Worah Family Professor in the Wallman Society of Fellows and the Departments of Statistics and Computer Science at the University of Chicago. She completed her PhD in Electrical and Computer Engineering at Rice University in 2005 and was an Assistant then tenured Associate Professor of Electrical and Computer Engineering at Duke University from 2005 to 2013. She was an Associate Professor of Electrical and Computer Engineering, Harvey D. Spangler Faculty Scholar, and Fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin-Madison from 2013 to 2018.  Prof. Willett received the National Science Foundation CAREER Award in 2007, was a member of the DARPA Computer Science Study Group 2007-2011, and received an Air Force Office of Scientific Research Young Investigator Program award in 2010. Prof. Willett has also held visiting researcher positions at the Institute for Pure and Applied Mathematics at UCLA in 2004, the University of Wisconsin-Madison 2003-2005, the French National Institute for Research in Computer Science and Control (INRIA) in 2003, and the Applied Science Research and Development Laboratory at GE Medical Systems (now GE Healthcare) in 2002. Her research interests include network and imaging science with applications in medical imaging, wireless sensor networks, astronomy, and social networks. She is also an instructor for FEMMES (Females Excelling More in Math Engineering and Science; news article here) and a local exhibit leader for Sally Ride Festivals. She was a recipient of the National Science Foundation Graduate Research Fellowship, the Rice University Presidential Scholarship, the Society of Women Engineers Caterpillar Scholarship, and the Angier B. Duke Memorial Scholarship.

Homepage

Staff

Tiana Pyer-Pereira

Research Administrator, Willett Research Group

tianap@uchicago.edu

Eric Horvitz serves as Microsoft’s Chief Scientific Officer. He spearheads company-wide initiatives, navigating opportunities and challenges at the confluence of scientific frontiers, technology, and society, including strategic efforts in AI, medicine, and the biosciences.

Dr. Horvitz is known for his contributions to AI theory and practice, with a focus on principles and applications of AI amidst the complexities of the open world. His research endeavors have been direction-setting, including harnessing probability and utility in machine learning and reasoning, developing models of bounded rationality, constructing systems that perceive and act via interpreting multisensory streams of information, and pioneering principles and mechanisms for supporting human-AI collaboration and complementarity. His efforts and collaborations have led to fielded systems in healthcare, transportation, ecommerce, operating systems, and aerospace.

He received Ph.D. and M.D. degrees at Stanford University. Before moving into the role of Chief Scientific Officer, he served as director of Microsoft Research overseeing research labs in Redmond, Washington; Cambridge, Massachusetts; New York City, New York; Montreal, Canada; Cambridge, United Kingdom; and Bangalore, India.

Vicky Kalogera’s research interests lie broadly in the astrophysics of compact objects across the electromagnetic spectrum and in gravitational waves. In binary systems, where two stars orbit each other, the interactions of compact objects are especially interesting. They can include a wide variety of violent phenomena such as powerful X-ray emissions, supernova explosions, black hole formation, and mergers.Kalogera’s research is focused mainly on how such systems are born, how they evolve, and how they end their lives. She is also interested in how the properties of such systems are affected by their galactic environments.

Kalogera is a leading astrophysicist in the LIGO Scientific Collaboration (LSC) and a member of this collaboration for more than 15 years. LIGO (Laser Interferometer Gravitational-wave Observatory) is the special kind of ‘telescope’ that first detected gravitational waves in 2015, 100 years after Einstein predicted them to exist. As a member of the discovery team of the first LIGO source (GW150914), she was awarded the 2016 Gruber Prize in Cosmology and the 2015 Special Breakthrough Prize in Fundamental Physics.

Kalogera is at the forefront of the emergent field of gravitational-wave astronomy, using data analysis and astrophysical modeling to understand the universe’s population of black holes and neutron stars. Her research is cross-disciplinary coupling gravitational-wave and stellar astrophysics to data science, machine learning and high-performance computing. In parallel to her gravitational-wave source studies, Kalogera also studies the formation and evolution of stars and their remnants detectable as gamma-ray, X-ray, and radio pulsar sources in the electromagnetic spectrum, in a wide range of stellar environments.

Pushmeet Kohli is a principal scientist and research team leader at DeepMind. Before joining DeepMind, Pushmeet was the director of research at the Cognition group at Microsoft. During his 10 years at Microsoft, Pushmeet worked in Microsoft labs in Seattle, Cambridge and Bangalore and took a number of roles and duties including being technical advisor to Rick Rashid, the Chief Research Officer of Microsoft. Pushmeet’s research revolves around Intelligent Systems and Computational Sciences, and he publishes in the fields of Machine Learning, Computer Vision, Information Retrieval, and Game Theory. His current research interests include 3D Reconstruction and Rendering, Probabilistic Programming, Interpretable and Verifiable Knowledge Representations from Deep Models. He is also interested in Conversation agents for Task completion, Machine learning systems for Healthcare and 3D rendering and interaction for augmented and virtual reality. Pushmeet has won a number of awards and prizes for his research. His PhD thesis, titled “Minimizing Dynamic and Higher Order Energy Functions using Graph Cuts”, was the winner of the British Machine Vision Association’s “Sullivan Doctoral Thesis Award”, and was a runner-up for the British Computer Society’s “Distinguished Dissertation Award”. Pushmeet’s papers have appeared in Computer Vision (ICCV, CVPR, ECCV, PAMI, IJCV, CVIU, BMVC, DAGM), Machine Learning, Robotics and AI (NIPS, ICML, AISTATS, AAAI, AAMAS, UAI, ISMAR), Computer Graphics (SIGGRAPH, Eurographics), and HCI (CHI, UIST) conferences. They have won awards in ICVGIP 2006, 2010, ECCV 2010, ISMAR 2011, TVX 2014, CHI 2014, WWW 2014 and CVPR 2015. His research has also been the subject of a number of articles in popular media outlets such as Forbes, Wired, BBC, New Scientist and MIT Technology Review. Pushmeet is a part of the Association for Computing Machinery’s (ACM) Distinguished Speaker Program.

Jesse Thaler is a theoretical particle physicist who fuses techniques from quantum field theory and machine learning to address outstanding questions in fundamental physics. His current research is focused on maximizing the discovery potential of the Large Hadron Collider (LHC) through new theoretical frameworks and novel data analysis techniques. Prof. Thaler is an expert in jets, which are collimated sprays of particles that are copiously produced at the LHC, and he studies the substructure of jets to enhance the search for new phenomena and illuminate the dynamics of gauge theories. Prof. Thaler joined the MIT Physics Department in 2010, and is currently a Professor in the Center for Theoretical Physics. In 2020, he became the inaugural Director of the NSF Institute for Artificial Intelligence and Fundamental Interactions.

Dr. Juan de Pablo is the inaugural Executive Vice President for Global Science and Technology, and the Executive Dean of the NYU Tandon School of Engineering. He leads cross-University, multidisciplinary, and globally focused efforts to accelerate the momentum of NYU’s vast science and technology enterprise for the purposes of solving humanity’s largest challenges. Dovetailing with those efforts, de Pablo steers Tandon’s engineering research and education to play a central role in addressing a multitude of areas, from human health, to advances in materials discovery, to the sustainability of the planet.

Before joining NYU, Dr. de Pablo served as the Executive Vice President for Science, Innovation, National Laboratories, and Global Initiatives at the University of Chicago; the Liew Family Professor in Molecular Engineering at Chicago’s Pritzker School of Molecular Engineering; and a Senior Scientist at Argonne National Laboratory.

A prominent materials scientist and chemical engineer, de Pablo’s research focuses on polymers, biological macromolecules such as proteins and DNA, glasses, and liquid crystals. He is a leader in developing molecular models and advanced computational approaches to elucidate complex molecular processes over wide ranges of length and time scales. He has developed advanced algorithms to design and predict the structure and properties of complex fluids and solids at a molecular level, and has been a pioneer in the use of data-driven machine learning approaches for materials design.