Scott Acton

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VIVA Affiliation

Director, Professor of ECE and BME
2000 - Present

Personal Info

Curriculum Vitae: .pdf

Degrees

PhD. Electrical and Computer Engineering, University of Texas at Austin
M.S. Electrical and Computer Engineering, University of Texas at Austin
B.S. Electrical Engineering, Virginia Tech

Biographical Sketch

Scott Acton received the M.S. degree in Electrical and Computer Engineering and the Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin in 1990 and 1993, respectively. There, he worked for the incomparable Al Bovik. He has a B.S. degree in Electrical Engineering from Virginia Tech (1988). He has worked in industry for AT&T, the MITRE Corporation and Motorola, Inc. and in academia for Oklahoma State University. For his research in video tracking, Dr. Acton was given an ARO Young Investigator Award. He received the Halliburton Outstanding Young Faculty Award in 1998. In 1997, he was named the Eta Kappa Nu Outstanding Young Electrical Engineer -- a national award that has been given annually since 1936. Here at U.Va., he was named the Outstanding New Teacher in 2002. Dr. Acton is a senior member of the IEEE and serves as Associate Editor for the IEEE Transactions on Image Processing and served as an AE for the IEEE Signal Processing Letters. Dr. Acton was the 2004 Technical Program Chair and the 2006 General Chair of the Asilomar Conference on Signals, Systems and Computers. He is the 2007 Special Sessions Chair for the International Conference on Image Processing and the 2008 Technical Co-Chair for the IEEE SW Symposium on Image Analysis and Interpretation.

Research Interests

Dr. Acton's areas of research include image analysis, with an emphasis on biomedical image analysis. His theoretical interests include multiscale image representations, diffusion algorithms, active contours, image morphology, and image correspondence problems. Applications include bioimaging, cell tracking, cardiovascular image analysis, military tracking, image classification/segmentation, and multimedia content-based retrieval.

Funded Research

• NIH
• Whitaker Foundation
• NSF
• ARO
• NASA
• U.S. Army Medical
• Mellon Foundation
• U.Va. Cancer Center