Peter Santago II, PhD

Peter Santago II, Ph.D., Professor and Chair, Computer Science; Professor of Biomedical Engineering

Dr. Peter Santago is the chair of the Computer Science Department. Previously, he was the chair of the Department of Biomedical Engineering and Associate Director of the Virginia Tech – Wake Forest University School of Biomedical Engineering and Sciences (SBES). Dr. Santago has been instrumental in bringing engineering to the Medical Center, most recently and importantly through SBES.

A major contribution of these efforts is that these Biomedical Engineering (BME) initiatives have all been to build interdisciplinary research projects, and BME students are expected to select a project that build on the interface between engineering and biological systems. Dr. Santago was selected to receive the Graduate Student Association Faculty Excellence Award in 2001, the IEEE North Carolina Council Outstanding Engineer Award, and the IEEE Third Millennium Medal. Dr. Santago’s research can generally be categorized as image analysis and pattern recognition. As Associate Director for SBES, Dr. Santago is also responsible for facilitating collaborations between other researchers in the Colleges of Engineering and Veterinary Medicine at Virginia Tech and in the Medical School.

SYNOPSIS OF AREA OF INTEREST: Dr. Santago collaborates with researchers from many disciplines. His technical expertise includes signal analysis, pattern recognition, and medical imaging.

DETAILED AREA OF INTEREST: Dr. Santago's research can generally be categorized as pattern recognition, image and signal processing, and machine learning. More recently he has emphasized the use of high-performance cluster computing on various applications of pattern analysis. In particular he has recently had collaborations in computational drug discovery; tissue imaging and characterization with an emphasis on high-frequency ultrasound and fiber optic imaging; and CT colonography polyp detection and diagnosis. While these applications are quite different in many regards, by focusing pattern recognition technology on them, this diversity can bring new ways of thinking about each problem. Currently he is involved in projects that involve image analysis with anesthesiologists, pattern recognition for computation linguistics, ultrasound signal analysis for fault detection, and most recently studying agent-based modeling and simulation.

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Institute for Regenerative Medicine

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