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Jeffrey L. Krolik

Professor of Electrical and Computer Engineering
Electrical and Computer Engineering
Box 90291, Durham, NC 27708-0291
3465 CIEMAS, Durham, NC 27708

Overview


Jeffrey Krolik is Professor of Electrical and Computer Engineering at Duke University in Durham, NC. Canadian-born, he received his Ph.D. in Electrical Engineering from the University of Toronto in 1987. He began his academic career as an Assistant Professor of Electrical and Computer Engineering at Concordia University in Montreal. Interested in signal processing applications in the ocean sciences, he joined the Scripps Institution of Oceanography, University of California San Diego as an Assistant Research Scientist in 1990. At Scripps, he developed physics-based sensor array processing methods that exploit multi-path underwater acoustic propagation. Since coming to Duke in 1992, he has broadened his research interests to include statistical signal processing for surveillance radars and microwave remote sensing, active and passive sonar, and medical imaging. Some of his current projects include the development of aircraft height finding for over-the-horizon HF radar, through-the-sensor environmental monitoring of near-surface atmospheric conditions using a shipboard microwave radar, active sonar array shape estimation from reverberation, and functional magnetic resonance imaging algorithms which are robust to head motion. As a consultant, he has worked for the Office of Naval Research, the Defense Advanced Research Projects Agency (DARPA), the Air Force Rome Laboratories.

Current Appointments & Affiliations


Professor of Electrical and Computer Engineering · 2001 - Present Electrical and Computer Engineering, Pratt School of Engineering

In the News


Published May 11, 2021
Bringing Radar Down From the Clouds to the City Streets

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Recent Publications


Adaptive focusing for wideband beamforming in multipath environments.

Journal Article The Journal of the Acoustical Society of America · January 2025 This paper addresses achieving the high time-bandwidth product necessary for low signal-to-noise ratio (SNR) target detection and localization in complex multipath environments. Time bandwidth product is often limited by dynamic environments and platform m ... Full text Cite

Athena – The NSF AI Institute for Edge Computing

Journal Article AI Magazine · March 1, 2024 The National Science Foundation (NSF) Artificial Intelligence (AI) Institute for Edge Computing Leveraging Next Generation Networks (Athena) seeks to foment a transformation in modern edge computing by advancing AI foundations, computing paradigms, network ... Full text Cite

Sample-Starved Wavefront Adaptive Sensing and GLRT for MTI Radar

Conference Proceedings of the IEEE Radar Conference · January 1, 2024 Moving target indicator (MTI) radars can suffer signal-to-noise ratio (SNR) losses due to: 1) the use of heavy non-adaptive tapers, and/or 2) poor estimation of space-time adaptive weight vectors. For ground-based radars, non-adaptive temporal and spatial ... Full text Cite
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Recent Grants


AI Institute: Athena: AI-Driven Next-generation Networks at the Edge

ResearchDirector · Awarded by National Science Foundation · 2021 - 2026

Integrating Adaptive Beamforming and Classification for Passive Sonar Detection in Complex Environments

ResearchPrincipal Investigator · Awarded by Office of Naval Research · 2023 - 2026

HF Towed-Array Calibration and Beamforming

ResearchPrincipal Investigator · Awarded by MIT Lincoln Laboratory · 2023 - 2025

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Education, Training & Certifications


University of Toronto (Canada) · 1987 Ph.D.
University of Toronto (Canada) · 1983 M.A.
University of Toronto (Canada) · 1980 B.A.