Scott Douglas, Ph.D.

Dr Scott Douglas

Scott C. Douglas, Ph.D.

Associate Vice Provost for Research

Professor of Electrical & Computer Engineering

Office Location: Junkins 305

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Education

Ph.D. Electrical Engineering, Stanford, 1992
M.S. Electrical Engineering, Stanford, 1989
B.S. Electrical Engineering, Stanford, 1988

Biography

Scott Douglas is Professor of Electrical and Computer Engineering and the Associate Chair of Undergraduate Studies and Outreach for the Department of ECE. His research interests include audio, wireless and acoustic array processing, blind source separation, machine learning, remote sensing, and speech enhancement. Dr. Douglas has over 200 publications in refereed journals and conference proceedings on these and related topics. He is also the co-author of two textbooks and the co-inventor of two patents (one pending).

Dr. Douglas current research efforts focus on advanced processing and assessments methods for remote sensing of vehicular emissions in joint work with the Environmental Protection Agency. He is an active consultant and technical expert for various industries. He was the co-designer of the Infinity Project, a joint effort between universities, pre-college schools, and industry to bring and deliver engineering education to middle- and high-school students.

Honors and Awards

National Science Foundation CAREER Award, 1995
IEEE Signal Processing Society Best Paper Award, Audio and Electroacoustics, 2003
Gerald J. Ford Research Fellowship, 2003
General Chair, IEEE International Conference on Acoustics, Speech, and Signal Processing, Dallas, Texas, 2010

Research

Audio, Array Processing, Machine Learning, Remote Sensing, Speech Enhancement

Recent Publications

C.R. Fulper, T.H. DeFries, and S.C. Douglas, "System and Method for Quantifying Source and Component Emission Rates from a Body in a Flow Field," patent application, Pub. No. US 2023/0101265 A1, U.S. Patent and Trademark Office, Mar. 30, 2023

S.C Douglas and T.H. DeFries, "Blind Source Separation Under Signal Covariance Constraints: Criteria and Algorithms," Proc. 55th Annual Asilomar Conf. Signals, Systems, Computers, Pacific Grove, CA, pp. 1329-1333, November 2021.

S.C. Douglas and Y. Hong, "Simple Iterative Algorithms for Approximate and Bounded Parameter Orthonormality," Proc. 53rd Annual Asilomar Conf. Signals, Systems, Computers, Pacific Grove, CA, pp. 2101-2105, November 2019.

T. Variddhisai, M. Xiang, S.C. Douglas, and D.P. Mandic, "Quaternion-Valued Adaptive Filtering via Nesterov's Extrapolation," Proc. IEEE Int. Conf. Acoust.,Speech, Signal Processing, Brighton, UK, pp. 4868-4872, May 2019.

S.C. Douglas and E.C. Larson, "Relationships Between Deep Learning and Linear Adaptive Systems," Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, Brighton, UK, pp. 7755-7759, May 2019.

Personal Website

https://lyle.smu.edu/~douglas/