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Michelle LaPlaca, PhD, MSE Georgia Institute of Technology Assistant Professor, GT/Emory Biomedical Engineering, School of Biomedical Engineering, Petit Institute for Bioengineering & Bioscience Georgia Institute of Technology Dr. Michelle LaPlaca is an Assistant Professor in the School of Biomedical Engineering, Petit Institute for Bioengineering and Bioscience, at the Georgia Institute of Technology. She earned a BBE in biomedical engineering (1991) at the Catholic University of America before beginning graduate work at the University of Pennsylvania, where she earned both an MSE (1992) and PhD (1996) in bioengineering and completed postdoctoral training in neurosurgery (1998). Her accomplishments as a researcher and academic were recognized with a 2001 National Science Foundation CAREER Award. She is a Councilor in the American Society for Neural Transplantation and Repair, and a member of the Society for Biomaterials, the Society for Neuroscience, the National Neurotrauma Society and the Biomedical Engineering Society. She has published more than a dozen articles in peer-reviewed journals. Dr. LaPlaca’s research interests include tissue engineering of the injured nervous system; traumatic brain and spinal cord injury; acute mechanisms of injury induced cell dysfunction and death; and, clinical assessment of mild traumatic brain injury. She is co-developer of DETECT (Display Enhanced Testing for Concussions and mTBI system), a device used to quickly detect mild concussions. DETECT uses a headset and portable computer to run a battery of neuropsychological tests in the field, and can be used immediately after injury to determine if there is a concussion. Her SCIB research project is attempting to determine the primary mode of acute dysfunction and structural failure in neural cells subjected to prescribed traumatic mechanical loads, and to correlate secondary cellular responses that may lead to cell dysfunction and death with load parameters in injured neural cells. The overall objective is to develop load criteria that are model-independent and based on cellular properties. |
