Managing the Evolution of influenza
Assistant Professor, Department of Ecology and Evolution
Sarah joined the Ecology & Evolution Department at the University of Chicago as an assistant professor in July 2013. Her research investigates the coevolution of hosts and pathogens, especially the ways in which immune-mediated competition drives pathogen evolution, and the ways in which infection and vaccination shape the specificity of the host response. She received the NIH New Innovator Award and the Complex Systems Scholar Award from the James S. McDonnell Foundation to support her work on the coevolution of adaptive immune system and influenza. Before Chicago, Sarah spent three years as a NIH Ruth Kirschstein Fellow in the Center for Communicable Disease Dynamics at the Harvard School of Public Health. Sarah received her PhD from the Ecology & Evolutionary Biology Department at the University of Michigan in 2009.
Learning Mechanisms of Cellular Dynamics by Combining Simulations and Image Analysis
Professor of Chemistry and Director of the James Franck Institute
Aaron Dinner is a Professor of Chemistry and the Director of the James Franck Institute at the University of Chicago. His work combines physical simulation, image analysis, statistics, and machine learning to understand complex biological dynamics, with present focuses on circadian rhythms, cytoskeletal dynamics, and algorithms for observing and interpreting rare events far from equilibrium. He obtained his undergraduate (AB in Biochemical Sciences, 1994) and graduate (PhD in Biophysics, 1999) degrees at Harvard University, where he worked with Martin Karplus on Monte Carlo methods and their application to protein folding. Subsequently, he pursued postdoctoral studies at the University of Oxford (1999-2001), where he used hybrid quantum-mechanical/molecular-mechanical (QM/MM) methods to elucidate mechanisms of DNA repair, and the University of California, Berkeley (2001-2003), where he worked with David Chandler on transition path sampling and Arup Chakraborty on models of T lymphocyte signaling. He joined the faculty at the University of Chicago in 2003.
Climate Science in the Era of Large Computing
Associate Professor, Atmospheric Chemistry
Elisabeth Moyer is an Associate Professor in the Department of the Geophysical Sciences and the director of the Center for Robust Decision-making on Climate and Energy Policy, an NSF-funded interdisciplinary center focused on open-source tools to support decisionmaking. She also leads a new NSF NRT (research traineeship) program aimed at transforming interdisciplinary graduate education, with a focus on computation: "Computational data science to advance research at the energy-environment nexus".
Moyer's research spans atmospheric science, climate statistics, and energy and climate policy analysis. Her climate research focuses on the statistics of evolving climate states; her atmospheric science research focuses on the processes that control the distribution of water vapor and formation of cirrus clouds in the upper troposphere and stratosphere.
Predicting the Conformational Variability of Abl Tyrosine Kinase using Molecular Dynamics Simulations and Markov State Models
Amgen Professor of Biochemistry and Molecular Biology
Benoit Roux was born in the city of Montreal, Canada, in 1958. In 1981, he received a B.Sc. in Physics from the University of Montreal, followed by a M.Sc. in Biophysics in 1985 under the supervision of Remy Sauve. In 1990, he obtained a Ph.D. in Biophysics from Harvard University under the direction of Martin Karplus. He has held positions at the University of Montreal, and the Weill Medical College of Cornell University.
He has been at the University of Chicago since 2005, where he is the Amgen Professor in the Department of Biochemistry and Molecular Biology and holds a joint appointment in the Chemistry Department as well as Argonne National Laboratory. Using theoretical techniques such as classical molecular dynamics to understand the functioning of biological systems at the molecular level, he has investigated the mechanism of biological macromolecular systems such as ion channels, receptors, and protein kinases.
Empirical Asset Pricing via Machine Learning
Associate Professor of Econometrics and Statistics, Booth School of Business
Xiu earned his PhD and MA in applied mathematics from Princeton University, where he was also a researcher at the Bendheim Center for Finance. Prior to his graduate studies, he obtained a BS in mathematics from the University of Science and Technology of China.
Dacheng Xiu’s research interests include developing statistical methodologies and applying them to financial data, while exploring their economic implications. His earlier research involved risk measurement and portfolio management with high-frequency data and econometric modeling of derivatives. His current work focuses on developing machine learning solutions to big-data problems in empirical asset pricing.
Xiu’s work has appeared in Econometrica, the Journal of Econometrics, the Journal of the American Statistical Association, and the Annals of Statistics. Additionally, he was invited to publish in the Journal of Business and Economic Statistics. He is an Associate Editor for the Journal of Econometrics and Statistica Sinica, and also referees for several journals in the fields of econometrics, statistics, and finance. He has received several recognitions for his research, including the Dennis J. Aigner 2017 Honorable Mention for the best paper in empirical econometrics published by the Journal of Econometrics in 2015 or 2016, and the Best Conference Paper Prize at the 2017 Annual Meeting of the European Finance Association. In 2017, Xiu launched a website that provides up-to-date realized volatilities of individual stocks. These daily volatilities are calculated from the stocks’ intraday transactions and the methodologies are based on his research of high-frequency data.