Location
Chemical Engineering, 117E
Lab
Wilsdorf, A001 PO Box 400741
Ford Group Google Scholar Research Summary

About

Roseanne M. Ford is a Professor of Chemical Engineering at the University of Virginia. She holds a B.S. degree from the University of Delaware and a Ph.D. from the University of Pennsylvania, both in chemical engineering. She spent the spring of 1995 as a Visiting Professor at the University of Tennessee and Oak Ridge National Laboratory. In 2003 she was a visitor at the USGS in Boulder, CO and a Visiting Professor at EPFL in Lausanne, Switzerland. She recently completed a four-year term as department chair and was Associate Vice President for Research and Graduate Studies from 2004-2010. Professor Ford's research focus is on the transport of chemotactic bacteria in porous media and its impact on bioremediation. She was elected a fellow of the American Institute of Medical and Biological Engineering and was awarded the Cavaliers' Distinguished Teaching Professorship, which is the highest teaching award given at UVa. In 2016 she received the AIChE WIC Excellence in Mentoring Award.

Education

B.S. University of Delaware, 1984

M.S. University of Pennsylvania, 1985

Ph.D. University of Pennsylvania, 1989

Our goal is to improve the efficiency by which chemical pollutants in groundwater are removed using microorganisms that are able to biodegrade them."

Roseanne M. Ford, Professor

Research Interests

Computational Systems Biology
Environmental Engineering
Water Resources

Selected Publications

" Chemotaxis Increases the Retention of Bacteria in Porous Media with Residual NAPL Entrapment," Environ. Sci. Technol., 52(13): 7289-7295 (2018). Adadevoh, J. S., C. A. Ramsburg, and R. M. Ford
ABS
"Modeling Transport of Chemotactic Bacteria in Granular Media with Distributed Contaminant Sources," Environ. Sci. Technol., 51: 14192-14198 (2017). Adadevoh, J. S., S. Ostvar, B. Wood, and R. M. Ford
ABS
"Enhanced Retention of Chemotactic Bacteria in a Pore Network with Residual NAPL Contamination," Environ. Sci. Technol., 50(1):165-172 (2016). Wang, X., L. M. Lanning and R. M. Ford
ABS
"Chemotaxis Increases the Residence Time of Bacteria in Granular Media Containing Distributed Contaminant Sources," Environ. Sci. Technol., 50(1):181-187 (2016). Adadevoh, J. S. T., S. Triolo, C. A. Ramsburg and R. M. Ford
ABS
Quantitative Analysis of Chemotaxis Towards Toluene by Pseudomonas putida in a Convection-free Microfluidic Device," Biotechnol. Bioeng., 112:896-904 Wang, X., J. Atencia and R. M. Ford

Courses Taught

CHE 3321: Transport Processes I: Momentum Transfer
CHE 6630: Graduate Mass Transfer

Awards

AIChE Fellow 2024
William R. Kenan, Jr. Visiting Professorship for Distinguished Teaching, Princeton University 2017-2018
AIChE Women's Initiatives Committee's Mentorship Excellence Award 2016
Cavaliers' Distinguished Teaching Professorship 2011-2013
Thomas E. Hutchinson Faculty Award for dedication and excellence in teaching 2008
American Institute of Medical and Biological Engineering, Elected to College of Fellows 2005
University of Virginia President and Visitors' Prize for Scientific Research, Life Sciences 1996
Department of Energy, Environmental Restoration and Waste Management Program, Junior Faculty Award 1991

Featured Grants & Projects

Gulf of Mexico Research Initiative – Role of Microbial Motility in Degradation of Dispersed Oil We will test the hypothesis that in marine environments biodegradation of oil droplets occurs at a faster rate when exposed to chemotactic bacteria. We will use microfluidic devices that were developed in partnership with National Institute of Standards and Technology to evaluate chemotactic properties for a wide range of marine organisms and hydrocarbons. To mimic aspects of the environmental conditions in the Gulf of Mexico, we will consider the effects of surfactant, temperature and multiple chemical stimuli. These results will be used in models that incorporate the effect of chemotaxis on the fate and transport of dispersed oil droplets. Ultimately, these efforts will improve the reliability of models that are used to assess environmental impact and policy decisions.