Karen A. McDonald, PhD

University of California-Davis
Professor
Karen McDonald is a Professor of Chemical Engineering at the University of California at Davis. She also serves as the Faculty Director and Co-PI of the UC Davis ADVANCE Institutional Transformation program (http:// http://ucd-advance.ucdavis.edu/) a NSF-funded program to recruit, retain, and advance women STEM faculty. Prior to leading the UC Davis ADVANCE program, she served as Associate Dean for Research and Graduate Studies in the College of Engineering for 13 years. She is a member of the graduate program/groups in Chemical Engineering, Biomedical Engineering, and Plant Biology and is a co-chair of the Designated Emphasis in Biotechnology program. From 2003-2015 she served as the Co-Director of the NIH Training Grant in Biomolecular Technology at UC Davis, an innovative multidisciplinary research and educational training for doctoral students working at the interface of life sciences and engineering/physical sciences in application areas related to human health. From 2006-2013, she was the PI and Director of the NSF Collaborative Research and Education in Agricultural Technologies and Engineering (CREATE) IGERT, an interdisciplinary graduate training program with Tuskegee University focused on applications of plant biotechnology to biopharmaceuticals, biorefineries and sustainable agriculture. She received her B.S. from Stanford University, her M.S. from the University of California, Berkeley and her Ph.D. from the University of Maryland, College Park, all in Chemical Engineering.<br><br>
Dr. McDonald and her collaborators apply synthetic biology tools in plants for the development of novel expression systems as well as applying bioprocess engineering technologies to produce recombinant proteins (including human therapeutic proteins) using whole plants, harvested plant tissues, or plant cells grown in vitro in bioreactors as hosts. As a biochemical engineer, she is interested in translational research and strives to develop novel biomanufacturing processes that are scalable, cost effective, and meet a variety of design constraints.