Computational Research

Biological Systems

Research projects in rational drug design, structural biology, modeling of large biological assemblies (such as ribosomes and liposomes), micro-array data analysis and biomechanics: One research group is focusing on the biological targets of phospholipid growth factors (PLGF) that include receptor proteins in two families, the membrane-bound G protein-coupled receptor (GPCR) family and the nuclear peroxisome proliferator activated receptor gamma. They develop structural models of the GPCR family members responsive to PLGF and use these models to understand, at the molecular level, interactions between PLGF and their receptors. The group uses several computational methods (homology modeling, docking, QSAR and pharmacophore) to develop receptor-selective molecules that can be used by experimental collaborators to probe the physiology of individual PLGF receptors.

Another research group is modeling the domain motion of proteins, RNA and biological assemblies. They use molecular dynamics, coarse-grained elastic network model, and normal mode analysis to understand how the enzyme dynamics is related to its function. The group currently is modeling the mechanics of ribosome.

Other researchers are interested in the structure and dynamics of lipid membranes from a biophysicist point of view. They use coarse-grained models to study the multi-component phase separation in lipid membranes. Researchers are also developing algorithms that can be applied in computational biology and bioinformatics, in micro-array data analysis and in biomechanics. This latter group uses finite element analysis to study the influence of the shape of the spacer on the stress distribution in the spine.

Materials and Mechanical Properties

Research projects that study metal oxides at the atomic level, soft condensed matter at molecular to meso-scale, fluid mechanics, to solid mechanical systems: One group uses statistical mechanical methods (Monte Carlo and molecular dynamics) to study how the nanoscale confinement could affect the properties of polymers.

Other groups are interested in computational modeling of the thermodynamic and kinetic behavior of polymer nanocomposites, the dynamics and transport of polymers in nanopores, modeling fluid flow, especially those with a highly deformable gas-liquid interface at which surface tension forces are significant and in dynamic analysis and design of standard gear transmission systems using computer simulation and modeling.

Geophysics Research

Research projects that study crustal deformation and earthquake clustering in intra-continental settings which include multiple earthquake cycles and linear and non-linear viscoelastic processes is the focus of one group. Other groups study: complex seismic hazard modeling using more realistic near-surface geology, crustal structure, and fault rupture processes; probabilistic seismic hazard analyses for estimates of hazard uncertainty using Monte Carlo modeling; and 3D finite-difference and finite-element ground motion simulations.

Network Research

Research projects in the design and evaluation of routing protocols for high-speed networks is the focus of one group. Another group is designing a scalable simulator that can be run on parallel computers to simulate tens of thousands of networks and millions of hosts to study the propagation of Internet worms which can infect millions of computers in a few minutes.

Simulations of Large Complex Networks

Research projects in simulating large complex systems, such as neural and social systems, using analysis tools from statistical physics: The models for these systems are specially structured lattices which are evolved in time and their global dynamics observed. The models are large and consist of thousands of components, each of them following local rules. Since in complex systems prediction of long term system's behavior based on the initial configurations is not in general analytically solvable (except for some simple cases), simulations are necessary and generally requiring many processors.