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Biological & Medical Systems


Prof. White uses deep learning as a tool for understanding complex biochemical systems that imagegovern the design of drugs. Deep learning can provide accurate data-driven predictions for the design of new drugs and is especially important in complex biologic therapeutics like peptide drugs or delivered drugs.

Prof. Foster has active projects with three different departments at the University of Rochester Medical Center, Neurosurgery, Eastman Dental and Urology, to simulateflow dynamics relevant to medical systems. Computational Fluid Dynamics (CFD) is the application of numerical methods to create simulations of systems of interest in many areas of engineering. The general mathematical approach is to discretize the governing equations of fluid flow using finite volume methods to solve the equations of motion numerically via iterative procedures. We use CFD in various medical related projects to assist physicians at URMC in patient care and treatment.

The Yates group synthesizes coatings designed to interact with biochemical species. Electrochemical synthesis has been used to apply coatings on titanium that have been designed promote bone growth and prevent bacterial infection in orthopedic implant applications. Polymer coatings have been designed to enhance the performance of photonic biosensors by promoting strong interaction of the analyte with the surface of the sensing element.

Active Faculty / Research Areas

A. White :  Modeling Peptide Self-Assembly; Data-Driven Molecular Simulation; Molecular Modeling Methods Development; Materials Design; Deep Learning; Artificial Intelligence in Chemical Engineering

D. G. Foster:  Fluid Mechanics; Computational Fluid Dynamics; Rheology of Non-Newtonian Fluids; Biological Transport Phenomena

M. Z. Yates:  Thin Films; Membranes; Coatings; Small Particles; Crystallization; Microencapsulation; Electrolytic Surface Coatings and Electrochemical Surface Modification