September 22, 2020
Please welcome the faculty joining the Physical Sciences Division in the '20-21 academic year.
David DeMille, Physics, JFI, Argonne
David DeMille is a professor in the Department of Physics and the James Franck Institute. He uses precise quantum control over diatomic molecules to address a broad range of scientific questions. One primary theme is using molecules as amplifying quantum sensors of effects that arise from previously undiscovered fundamental particles. His experiments of this type are small enough to fit in a single room, but sensitive enough to detect the existence of certain new particles far more massive than the Higgs boson. DeMille received his AB in Physics from the University of Chicago and his PhD in Physics from University of California, Berkeley. He was previously on the faculty of Amherst College and then professor of physics at Yale University. He has received awards and fellowships from the American Physical Society and numerous private foundations. In addition to his faculty role, DeMille is a senior physicist at Argonne National Laboratory.
Brent Doiron, Statistics, Neurobiology
Brent Doiron is a professor in the Departments of Statistics and Neurobiology where he is the director of the Grossman Center for Human Behavior and Quantitative Biology. His research focuses on theoretical neuroscience, dynamical systems, statistical mechanics, information theory, neural coding, and sensory processing. Previously, he served as a professor in the Department of Mathematics at the University of Pittsburgh. In 2017, he was named a Vannevar Bush faculty fellow. He also earned the 2012 Chancellor’s award for distinguished research and was a 2009 Sloan Research Fellow. He has a PhD from the University of Ottawa and completed postdoctoral training at New York University.
Claire Donnat, Statistics
Claire Donnat is an assistant professor in the Department of Statistics. Her research is at the intersection between statistics and machine learning, and she has focused on the statistical analysis of graphs and networks. She is especially interested in applying these methods to the analysis of biomedical data, and in particular, to neuroscience and brain connectomics. Prior to coming to Chicago, she graduated from Ecole Polytechnique with an MSc in Applied Mathematics in 2015, and with a PhD in Statistics from Stanford in 2020, where she was advised by Prof. Susan Holmes.
Laura Gagliardi, Chemistry, PME, JFI, CCTC
Laura Gagliardi is the Richard and Kathy Leventhal Professor in the Department of Chemistry, the Pritzker School of Molecular Engineering, and the James Franck Institute. She also directs the Chicago Center for Theoretical Chemistry. Gagliardi became an assistant professor at the University of Palermo in 2002. In 2005, she became associate professor at the University of Geneva in Switzerland. She joined the University of Minnesota as a professor of chemistry in 2009, was appointed as Distinguished McKnight University Professor in 2014, and was awarded a McKnight Presidential Endowed Chair in 2018. She has also served as the director of the DOE-funded Energy Frontier Research Center called Inorganometallic Catalyst Design Center since 2014.
Ewain Gwynne, Mathematics
Ewain Gwynne is an associate professor in the Department of Mathematics. He studies probability theory, with a particular focus on random fractal curves and surfaces which arise in theoretical physics. He has done work on mathematical objects such as Schramm-Loewner evolution (SLE), Gaussian free fields, Liouville quantum gravity, and random planar maps. Gwynne received a PhD in Mathematics from MIT and a BA in Mathematics from Northwestern University. Prior to coming to Chicago he was a postdoc at the University of Cambridge, supported by a Trinity College junior research fellowship, a Clay research fellowship, and a Herchel Smith fellowship.
Alisa Knizel, Statistics
Alisa Knizel is an assistant professor in the Department of Statistics. Her research focuses on the interplay between probabilistic and algebraic properties of lattice models in statistical mechanics. Her most recent work is related to random matrix theory and interacting particle systems with applications to random growth models, traffic models and combinatorics. Before coming to the University of Chicago, she was an NSF postdoctoral fellow at the Department of Mathematics at Columbia University. She received her PhD in Mathematics from MIT in 2017, advised by Alexei Borodin.
Sunyoung Park, Geophysical Sciences
Sunyoung Park will join the Department of the Geophysical Sciences as an assistant professor on June 1, 2021. Park has a wide range of interests in seismology, including the Earth’s internal structure, from the surface to the core; earthquake rupture processes; and seismic hazard assessment. Her work focuses on the development of new analytical and experimental approaches—for example, utilizing 3D printing technology to perform seismic experiments. Previously, Park was a Texaco Postdoctoral Fellow at Caltech. She received her PhD in Earth and Planetary Sciences from Harvard University. She also has BS and MS degrees in Energy Engineering, and a BA degree in Economics, from Seoul National University.
Robert Rand, Computer Science
Robert Rand is an assistant professor in the Department of Computer Science, with a research specialty in quantum programming. Rand applies his expertise in programming languages and formal verification to quantum computation, creating tools for writing, testing, and running reliable software on the quantum computers of today and tomorrow. He co-developed QWIRE, a quantum circuit language, and VOQC, a verified optimizing compiler for quantum programs, and incorporates elements of both in his online textbook, Verified Quantum Computing. Rand was previously a Victor Basili Postdoctoral Fellow at the University of Maryland and the Joint Center for Quantum Information and Computer Science, and earned his PhD from the University of Pennsylvania.
Sarah Sebo, Computer Science
Sarah Sebo is an assistant professor in the Department of Computer Science. Her work concentrates on human-robot interaction, developing robots that improve the performance of human-robot teams by shaping team dynamics to promote inclusion, trust, and cohesion. Sebo uses computational models that detect relevant verbal and nonverbal social cues, predict high-level social dynamics, and generate decision-making policies for robot actions. Her papers are among the first to demonstrate that robots can influence the behavior of human team members, finding that robots expressing vulnerability and support can increase trust and positively influence conversational dynamics within a team (watch a video here). Sebo completed her PhD at Yale University, where she worked in the Social Robotics Lab.
Elena Shevchenko, Chemistry, Argonne
Elena Shevchenko is a part-time professor in the Department of Chemistry and scientist in the Center for Nanoscale Materials at Argonne National Laboratory. Her research focuses on understanding the fundamental principles of the synthesis of nanostructures for technologically important applications. She has served as a staff scientist at Argonne since 2007. Prior to Argonne, she was a scientist at Lawrence Berkeley National Laboratory and the IBM T. J. Watson Research Center. She has a PhD from the University of Hamburg.
Yi Sun, Statistics
Yi Sun is an assistant professor in the Department of Statistics. Sun studies probability and its applications to machine learning and high-dimensional statistics. His recent work addresses probabilistic and representation theoretic approaches to conformal field theories, robustness and data augmentation for neural networks, applications of random matrix theory to high-dimensional linear models, and optimization theory for multi-reference alignment and cryogenic electron microscopy (cryo-EM). Previously, Sun was a Joseph F. Ritt Assistant Professor and Simons Junior Fellow at Columbia University and received his PhD in Mathematics from MIT.
Chenhao Tan, Computer Science, Harris School of Public Policy
Chenhao Tan is an assistant professor in the Department of Computer Science, and will also be affiliated with the Harris School of Public Policy. Tan combines natural language processing, artificial intelligence, and computational social science to study human-centered machine learning, using AI to empower humans and augment human intelligence. His research examines how machine learning can help humans detect deception, enhance creativity, and discover new knowledge from data. He has also studied how language influences social interaction, the ecosystem of ideas, and multi-community engagement. This year, Tan has received an NSF CAREER award, an Amazon Research award, an IBM faculty award, and a Salesforce research award. He comes to UChicago from the University of Colorado, Boulder, and he received his PhD from Cornell University. In a paper on life trajectories, he wrote "People, unlike trees, thrive by relocation.”
Victor Veitch, Statistics
Victor Veitch is an assistant professor in the Department of Statistics (as of Jan. 1, 2021) and a research scientist at Google Cambridge. His recent work revolves around the intersection of machine learning and causal inference, as well as the design and evaluation of safe and credible AI systems. Other notable areas of interests include network data and the foundations of learning and statistical inference. He was previously a Distinguished Postdoctoral Researcher in the Department of Statistics at Columbia University, where he worked with the groups of David Blei and Peter Orbanz. He completed his PhD in Statistics at the University of Toronto, where he was advised by Daniel Roy. In a previous life, he worked on quantum computing at the University of Waterloo. He has won a number of awards, including the Pierre Robillard award for best statistics thesis in Canada.
Bios for Department of Computer Science faculty adapted from Four New Faculty Join UChicago Computer Science for 2020-21