Machelle Pardue is a research career scientist at the Atlanta VA Medical Center. Pardue received her B.S. in zoology from the University of Wyoming and her doctorate in vision science and biology at the University of Waterloo. Her post-doctorate training in visual electrophysiology was completed at the Loyola School of Medicine and Hines VA Hospital in Chicago. Her research has been continuously supported by the Department of Veterans Affairs, NIH, and private companies.

Her research interests center around characterizing and treating retinal disease using functional and anatomical methods. The main projects in the laboratory investigate neuroprotective agents that could slow the progression of retinal degeneration and diabetic retinopathy, providing potentially years of improved visual function. Such treatments include electrical stimulation produced by retinal prosthetics, exercise to increase growth factors, and anti-apoptotic agents. In addition, she is investigating how defects in retinal pathways and the visual environment influence refractive development.

Peng Qiu received his B.S. degree from the University of Science and Technology of China, and a Ph.D. degree from the University of Maryland College Park, both in electrical engineering. After spending three years as a postdoctoral fellow in the Center for Cancer Systems Biology at Stanford, and three years as an assistant professor in the Department of Bioinformatics and Computational Biology at UT MD Anderson Cancer Center, he joined the Department of Biomedical Engineering at the Georgia Institute of Technology and Emory University.

His main research interests are in the area of bioinformatics and computational biology, focusing on machine learning, visualization, signal processing, systems modeling and network analysis. He has developed a computational framework for discovering biological progression underlying high-dimensional data, which gave rise to SPADE, the first algorithm for extracting cellular differentiation hierarchy from single-cell data generated by flow cytometry and CyTOF. He has expertise in integrative analysis of large-scale multi-omics data, and one recent project is to identify cancer-specific gene-drug interactions by integrating drug, survival and genomic data in TCGA. He has been developing a manifold learning framework to computational address the problems of experimental design and model reduction, which led to an NSF CAREER award last year.

Media Contact:
Walter Rich
Communications Manager
Wallace H. Coulter Department of Biomedical Engineering
Georgia Institute of Technology