Edward R Dougherty

Distinguished professor, Texas A&M University

Edward R. Dougherty is a Professor in the Department of Electrical and Computer Engineering at TexasA&MUniversity in College Station, TX, where he holds the Robert M. Kennedy ‘26 Chair in Electrical Engineering and is Director of the Genomic Signal Processing Laboratory. He is also co-Director of the Computational Biology Division of the Translational Genomics Research Institute in Phoenix, AZ. He holds a Ph.D. in mathematics from RutgersUniversity and an M.S. in Computer Science from Stevens Institute of Technology, and has been awarded the Doctor Honoris Causa by the Tampere University of Technology in Finland. He is a fellow of both IEEE and SPIE, has received the SPIE President’s Award, and served as the editor of the SPIE/IS&T Journal of Electronic Imaging. At Texas A&M University he has received the Association of Former Students Distinguished Achievement Award in Research, been named Fellow of the Texas Engineering Experiment Station, and named Halliburton Professor of the Dwight Look College of Engineering. Most recently, he has been awarded the status of University Distinguished Professor. Prof. Dougherty is author of 16 books, editor of 5 others, and author of over 300 peer-reviewed journal papers. His publications have received over 19,000 citations. Prof. Dougherty has contributed extensively to the statistical design of optimal nonlinear operators for image processing and the consequent application of pattern recognition theory to nonlinear image processing. During the past two decades his research has focused on genomic signal processing. It has been aimed at optimal disease diagnosis and prognosis based on genetic signatures and the application of gene regulatory networks to develop optimal therapies based on the disruption or mitigation of aberrant gene function contributing to the pathology of a disease. In these veins he and his colleagues have developed the theory of small-sample classifier design and error estimation, as well as the application of control theory to dynamic gene regulation.

Experience

  • –present
    Distinguished professor, Texas A&M University