Supported Projects
The Research Computing Center supports faculty labs and groups in over twelve divisions across the University of Chicago from the Humanities to the Biological Sciences to the recently established Institute for Molecular Engineering. See below for some examples of researchers, groups, and labs to which the RCC offers ongoing computational and consultation support.
If you are a RCC Principal Investigator and would like to see your lab or group featured on this page please email us with a short description of your project.
Gregory Voth's research involves theoretical and computer simulation studies of phenomena in biomolecular, condensed phase, and novel materials systems. A primary goal of this effort is to develop and apply new computational methods to explain and predict the behavior of complex systems. Such methods are developed, for example, to probe phenomena such as protein-protein self-assembly, membrane-protein interactions, biomolecular and liquid state charge transport, complex fluids, nanoparticle self-assembly, and charge-mediated energy storage. To learn more about the Voth Group visit their website and to explore some of the Voth Group's featured research publications that made use of RCC resources visit our publications page.
Juan de Pablo is the Liew Family Professor in Molecular Engineering at the recently created Institute for Molecular Engineering. The research of the de Pablo Group investigates the thermophysical properties of fluids and solids at a molecular level, and uses molecular-thermodynamic models and statistical-mechanical principles. Knowing and understanding the thermophysical properties of fluids and solids, respectively, is essential for designing efficient chemical processes and for developing new materials. Molecular simulations are important to the de Pablo Group's research. Using advanced methods and powerful computers, they examine molecular motion and probe the microscopic structure of fluids and solids. Based on these studies, the de Pablo Group tries to explain and predict the macroscopic behavior of these systems. These predictions are then compared with experimental laboratory data. The de Pablo Group has made extensive use of RCC systems. Visit our publications page to view some the group's featured research papers calculations for which were conducted on Midway.
Dorian Abbot is an Assistant Professor in the Geophysical Sciences department at the University of Chgicago, who along with students and postdoctoral researchers, uses the Midway Compute Cluster to make calculations of the atmospheric dynamics and cloud behavior of Earth-like exoplanets to try to understand how they can affect planetary habitability. Recently he has published an academic using RCC systems about planetary rotation rate as a key determinate of atmospheric circulation and the spatial pattern of clouds. To further explore Dr. Abbot's research visit our publications page.
Jack Gilbert's Lab is interested in deconvoluting microbial interactions in myriad ecosystems. The Gilbert Lab uses the RCC system extensively performing studies that explore the diversity and structure of microbial communities in marine, soil, freshwater, plant, animal, human, and built environments. The lab runs the Home and Hospital Microbiome Projects at University of Chicago and the Earth Microbiome Project, which is the largest microbial ecology database currently available. The Gilbert Lab works on genome assembly to try and capture the functional potential of key microbial genotypes associated with different metabolic processes in different ecosystems including pathogenesis in human and built ecosystems, and methanogenesis/methanotrophy in soils and marine systems. The Lab has a particular interested in oil remediation and work extensively on the Gulf of Mexico Oil Spill with companies to explore oil-eating bacteria. Jack Gilbert's Lab also uses the RCC servers to characterize the microbial interactions inside electromicrobiological bioreactors used to create chemical products from electrons through bacteria and archaea. To learn more about the Gilbert Lab visit their website.
Robert Gramacy studies Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimization under uncertainty. His application areas of interest include spatial data, sequential computer experiments, ecology, epidemiology, finance and public policy. An important aspect of Gramacy's research is implementation. Trained as an engineer, Gramacy believes that releasing high quality open source software for new statistical methodologies is just as important as putting them in print. His software packages for R include the widely used tgp package for nonparametric regression. In his research Robert Gramacy has extensively utilized both RCC hardware and consultation resources. To view some of his recent academic papers check out our publications page.
Stephanie and John Cacioppo lead the University of Chicago High Performance Electrical NeuroImaging (HPEN) Laboratory of the Center for Cognitive and Social Neuroscience, which aims to advance the scientific knowledge of the social brain. Combining high-density electrical neuroimaging, algorithms integrating brain source localization, noise suppression and boostrapping with high performance computing, HPEN offers cutting edge tools for the study of social interactions and interacting brains. The emphasis is placed on converging resources, sharing data and protocols and integrating scientific theoretical knowledge and methodologies from four main disciplinary fields: High Performance Computing (HPC), Psychology, Neurology and Social Neuroscience. Our mission is to create an open access scientific community with new interdisciplinary learning opportunities in social neuroscience, electrical neuroimaging and super computing for scientists, students, and teachers. The HPEN Laboratory utilizes the RCC to do computational calculations on many research projects. Visit our publications page to see how RCC resources help advance published academic research.