Scott Rickard *03

Scott Rickard
Electonic, Electrical & Mechanical Engineering
University College Dublin
Belfield, Dublin D4, Ireland

Ph.D: Electrical Engineering, 2003

Thesis: Time-frequency and time-scale representations of doubly spread channels

Advisor: Vincent Poor, Sergio Verdu

Biography

Scott Rickard was born in New York in 1970. He received the S.B. degree in Mathematics in 1992, the S.B. degree in Computer Science and Engineering in 1993, and the S.M. degree in Electrical Engineering and Computer Science also in 1993, all from the Massachusetts Institute of Technology (M.I.T.). He received the M.A. and Ph.D. degrees in Applied and Computational Mathematics from Princeton University in 2000 and 2003 respectively.

From 1991 to 1993 he was a research assistant at the Charles Stark Draper Laboratory in Cambridge, Massachusetts and worked on a prototype analog neural network computer, designed neural networks for mine detection from sonar images, and designed large sets of frequency hopped waveforms with nearly ideal ambiguity properties for sonar applications. From 1993 to 2003 he was a member of technical staff at Siemens Corporate Research in Princeton, New Jersey. He spent 1995 and 1996 in Munich Germany with Siemens working in the Neural Networks Group. While with Siemens, he developed and applied machine learning technology to industrial problems such as vehicle navigation, automated image analysis, biomedical signal classification, and industrial plant state prediction.

Dr. Rickard moved to UCD in September 2003 and is currently a Senior Lecturer in the School of Electrical, Electronic and Mechanical Engineering. Since joining UCD, Dr. Rickard has obtained over 1.1M euro in individual funding including SFI's President of Ireland Young Researcher Award and over 30M euro in group funding.

His research for the past several years has focused on the application of time-frequency methods and sparse signal processing for the blind separation of more sources than sensors. His research interests include time-frequency/scale analysis applied to signal processing, wireless communications, blind source separation, multicarrier communication systems, and Costas arrays. Dr. Rickard's research group, the Sparse Signal Processing Group, consists of 8 Ph.D. students, 1 M.Eng. student, and 1 postdoc.

Dr. Rickard is keenly interested in science, mathematics, and engineering education, at all levels, and is co-founder of Science With Me! and co-created RoboRugby.