Research Teams

The modeling and simulations related research focus is extending Kohn-Sham density functional theory and first-principles derived atomistic simulation techniques to understand the dynamics of phase transformation, transport and chemical reactions in condensed matter. Current research areas include investigations of dynamic changes due to pressure, temperature, electric field and dynamic loading (shock and shear) using atomistic and mesoscale simulations for connecting atoms-to-grain level changes in materials. We leverage petascale DOD/DOE/NSF supercomputing resources for developing open source tools for data-enabled computational material discovery. Learn more: https://publish.illinois.edu/santc/.

Dr. Dalal's group studies the nonlinear evolution of cosmological structures, like galaxies, clusters, and voids, with a focus on probing the relation between large-scale structure and fundamental physics. Specific topics of interest include dark matter, dark energy, neutrinos, cosmic inflation, and gravity. Dr. Dalal's group uses ICCP resources to perform N-body simulations of cosmic structure formation, and to analyze gravitational lensing measurements of dark matter halos observed by the Atacama Large Millimeter/sub-millimeter Array (ALMA).

Our research interests focus on studying soft matter physics at the molecular/atomic scale using extensive molecular dynamics simulations guided by neutron scattering measurements. Currently, we are using the ICCP for three main categories of research: investigating the behaviors of proteins under nanoscopic confinements, simulating applicational materials—such as ionic liquids and water—to provide atomic-scale interpretations for experimental results, and devising novel computational techniques to enhance the sampling of the energy landscape of materials.

The CatchenLab is interested in the evolution of the genome. Their computational biology lab investigates whether the architecture of the genome is a passive or active force in the adaptation of species to new environments, including Antarctic notothenioid fish and Northwestern threespine stickleback fish. Learn more: http://catchenlab.life.illinois.edu.

One of the primary current research interests of our team is the development of a new theory—and its numerical implementation—of fracture and healing for soft organic solids. In its current version, the theory amounts to solving a system of two coupled and nonlinear PDEs for the deformation field and an order parameter, or phase field. We are investigating numerical schemes based on non-conforming finite element discretizations that are able to deal with the typical near incompressibility of soft organic solids, as well as with the sudden large deformations that ensue from nucleation of fracture.

Ted Underwood and his collaborators study century-spanning literary trends in large digital libraries, including the changing ways writers imagine gender, genre, and literary prestige. They use ICCP for natural language processing and machine learning on collections of millions of volumes, drawn mostly from HathiTrust Digital Library. Learn more: https://tedunderwood.com/ted-underwood/.

Prof. Aluru's research group is part of the Computational Multiscale Nanosystems Group in the Molecular and Electronics Nanostructures Research Initiative in the Beckman Institute at Illinois. They study nanofluidics, nanobiotechnology, nanomaterials/nanoelectromechanical systems, soft matter, and MEMS. Learn more: https://webhost.engr.illinois.edu/~aluru/.

Dr. Bellon's research program is mainly focused on alloys or mixtures submitted to a sustained external forcing: such conditions are often met during either the processing of materials (e.g. by ball-milling or during thin film growth) or during the use of these materials (e.g. during frictional wear or under irradiation). Learn more: https://matse.illinois.edu/directory/profile/bellon.

The Ferguson Lab are using their ICCP resources to support their research into the understanding and engineering of biomolecular folding, colloidal self-assembly, self-assembling organic electronics, and computational vaccine design. Learn more: http://ferguson.matse.illinois.edu/.

See the provided link for information on the work being done by the various Physics research groups: https://physics.illinois.edu/research/groups-and-centers/.

The School of Integrative Biology studies evolution, ecology, behavior and conservation in a broad set of taxa. The School is home to three departments all engaged in these themes: Animal Biology, Plant Biology, and Entomology. Learn more: http://sib.illinois.edu.

Ras proteins are a key element of signal transduction where extracellular growth factors control nuclear transcription events involved in cell division, proliferation, and apoptosis. Ras activity is controlled, and signaling mediated by, critical protein-protein interactions. GTPase activating proteins (GAPs), such asp120, bind to activated Ras, dramatically increasing the rate of GTP hydrolysis thus returning the system to the inactive GDP bound state. Guanine exchange factors (GEFs), such as Son of Sevenless (SOS), bind and effect the exchange of GDP for GTP, thus turning "on" KRas4b. Most importantly, these multi-protein complexes all operate on a membrane surface, which is a critical partner in signaling. Despite this critical role of the membrane, there is incomplete knowledge as to the role of the bilayer composition in anchoring the protein to the membrane and the importance of specific lipid type in dictating the final orientation of KRas4b on the surface. In order to understand the molecular details of this protein-lipid interaction, we conducted molecular dynamics simulations to look for an origin of this specificity. In the case of membranes containing PIP2 the protein formed long-lived salt bridges with PIP2 head groups but not the monovalent DMPS, explaining the experimentally observed lipid specificity. Additionally, we found that PIP2 forms key contacts with Helix-4 on the catalytic domain of KRas4b that orient the protein in a manner expected to facilitate association with upstream and downstream signaling partners.

Dr. Warnow's research combines mathematics, computer science, probability, and statistics, in order to develop algorithms with improved accuracy for large-scale and complex estimation problems in phylogenomics, multiple sequence alignment, and metagenomics. Her team works especially on the hardest computational problems in these areas, where large dataset sizes and model complexity make existing approaches have insufficient accuracy. For these problems, she develops innovative strategies (often including graph-theoretic algorithms that employ divide-and-conquer, combined with machine learning methods), develops software, analyzes biological datasets (in collaboration with biologists around the world), and proves theorems about the methods they develop. Learn more: http://tandy.cs.illinois.edu/research-overview.html.

The Wagner group uses the Campus Cluster to study electrons in materials. They use Monte Carlo algorithms to approximately solve the Schrödinger equation for hundreds of electrons, in order to extract effective models for collections of quantum particles. Learn more: http://wagner.physics.illinois.edu.

The Watershed-Ecosystem Research Group of the Department of Agricultural and Biological Engineering conducts studies that seek to understand the dynamics between watershed and the ecosystem under climate and land use changes. The overarching goal of our research is to find the zone of intersection where productivity, social relevance, and environmental soundness are optimized to achieve a sustainable agro-production system. Learn more: http://abe-research.illinois.edu/Faculty/MariaChu/.