Graduation Year
2011
Thesis Title
Computer-aided design of nanostructures from self- and directed-assembly of soft matter building blocks
Current Job
Visiting Scholar at the Institute of Mechanics, Vietnam Academy of Technology and Science.
Graduation Year
2010
Thesis Title
Pooling Designs for High-Throughput Biological Experiments
Graduation Year
1997
Thesis Title
Kinetics of receptor, ligand, and G protein interaction for signal transduction: A modeling study
Supervisor
Jennifer Linderman
Current Job
Professor and Chair, Biomedical Engineering at the University of Michigan
Bryan Goldsmith is an Assistant Professor in the Department of Chemical Engineering. His works focus on the development of novel catalysts and materials. The world is facing a growing population, mass consumerism, and rising greenhouse gas levels, all the while people strive to increase their standard of living. Computational modeling of catalysts and materials, and making use of its synergy with experiments, facilitates the process to design new systems since it provides a valuable way to test hypotheses and understand design criteria. His research team focuses on obtaining a deep understanding of catalytic systems and advanced materials for use in sustainable chemical production, pollution abatement, and energy generation. They use first-principles modeling (e.g., density-functional theory and wave function based methods), molecular simulation, and data analytics tools (e.g., statistical learning and data mining) to extract key insights of catalysts and materials under realistic conditions, and to help create a platform for their design.
A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)
Heather Mayes is an Assistant Professor in the Department of Chemical Engineering. Her research group uses multi-scale modeling to discover protein-sugar interactions and to harness them for renewable energy and improved health. The study of carbohydrate-protein interactions is an important step to create renewable fuels and chemicals from non-food biomass, and the results can be applied to several human diseases, including cancer and autoimmune disorders. Prof. Mayes uses computational tools in her research, including quantum mechanics, molecular dynamics, and rare-event sampling methods. She collaborates with experimental groups to understand past and guide future wet-lab studies to advance renewable chemicals and fuels, as well as disease understanding.
Multiscale simulation to uncover mechanisms behind protein-sugar interactions, such as how the T. reesi Cel6A enzyme coordinates making and breaking four bonds for cellulose hydrolysis.
Angela Violi is a Professor in the Department of Mechanical Engineering, and adjunct faculty in Chemical Engineering, Biophysics, Macromolecular Science and Engineering, and Applied Physics. The research in the group of Violi is focused on the application of statistical mechanics and computational methods to chemically and physically oriented problems in nanomaterials and biology. The group investigates the formation mechanisms of nanomaterials for various applications, including energy and biomedical systems, and the dynamics of biological systems and their interactions with nanomaterials.
The Linderman group works in the area of computational biology, especially in developing multi-scale models that link molecular, cellular and tissue level events. Current areas of focus include: (1) hybrid multi-scale agent-based modeling to simulate the immune response to Mycobacterium tuberculosis and identify potential therapies, (2) models of signal transduction, particularly for G-protein coupled receptors, and (3) multi-scale agent-based models of cancer cell chemotaxis.
Hybrid multi-scale model of the immune response to Myobacterium tuberculosis in the lung. Selected immune cell behaviors and interactions captured by the model are shown. Not shown are single cell receptor/ligand dynamics involving the pro-inflammatory cytokine tumor necrosis factor (TNF) and the anti-inflammatory cytokine interleukin 10 (IL-10).
Professor Ziff carries out computational and theoretical studies of various physical problems, most notably percolation but also catalysis modeling and several reaction/diffusion systems. For percolation, he has developed various algorithms that have allowed substantial increases in performance, for the study of threshold behavior, crossing probability, etc. He also studies algorithms for efficiently simulating rare-event simulations such as chemical reactions and diffusion-limited aggregation.
Inside a diffusion-limited aggregation (DLA) cluster, grown using an accelerated rare-event algorithm.