Leslie M. Collins
Professor of Electrical and Computer Engineering
Leslie M. Collins earned the BSEE degree from the University of Kentucky, and the MSEE, and PhD degrees from the University of Michigan, Ann Arbor. From 1986 through 1990 she was a Senior Engineer at Westinghouse Research and Development Center in Pittsburgh, PA. She joined Duke in 1995 as an Assistant Professor and was promoted to Associate Professor in 2002 and to Professor in 2007. Her research interests include physics-based statistical signal processing, subsurface sensing, auditory prostheses and pattern recognition. She is a member of the Tau Beta Pi, Sigma Xi, and Eta Kappa Nu honor societies. Dr. Collins has been a member of the team formed to transition MURI-developed algorithms and hardware to the Army HSTAMIDS and GSTAMIDS landmine detection systems. She has been the principal investigator on research projects from ARO, NVESD, SERDP, ESTCP, NSF, and NIH. Dr. Collins was the PI on the DoD UXO Cleanup Project of the Year in 2000. As of 2015, Dr. Collins has graduated 15 PhD students.
Appointments and Affiliations
- Professor of Electrical and Computer Engineering
- Faculty Network Member of the Duke Institute for Brain Sciences
- Faculty Network Member of The Energy Initiative
- Office Location: 3461 CIEMAS, Durham, NC 27708
- Office Phone: (919) 660-5260
- Email Address: firstname.lastname@example.org
- Ph.D. University of Michigan, Ann Arbor, 1995
- M.Sc.Eng. University of Michigan, Ann Arbor, 1986
- B.S.E. University of Kentucky, Lexington, 1985
Physics-based machine learning algorithms for big data, including developing remediation strategies for the hearing impaired and sensor-based algorithms for the detection of hazardous buried objects
- BME 493: Projects in Biomedical Engineering (GE)
- ECE 280L9: Signals and Systems - Lab
- ECE 280L: Introduction to Signals and Systems
- ECE 392: Projects in Electrical and Computer Engineering
- ECE 493: Projects in Electrical and Computer Engineering
- ECE 494: Projects in Electrical and Computer Engineering
- ECE 590: Advanced Topics in Electrical and Computer Engineering
- ECE 891: Internship
- ECE 899: Special Readings in Electrical Engineering
- ENERGY 395: Connections in Energy: Interdisciplinary Team Projects
- ENERGY 396: Connections in Energy: Interdisciplinary Team Projects
- ENERGY 795: Connections in Energy: Interdisciplinary Team Projects
- ENERGY 796: Connections in Energy: Interdisciplinary Team Projects
- PSY 756: Research Practicum
In the News
- Listening to Broken Hearts, Saving Lives (Sep 21, 2018 | Pratt School of Engineering)
- Smart Meters: Duke Engineers Seek Energy Insights by Reading a Building's Electrical Signatures (Oct 4, 2016)
- Pratt Researchers Are Using Deep Learning to Distinguish Solar Panels from Swimming Pools (Aug 31, 2016)
- Chen, XJ; LaPorte, ET; Olsen, C; Collins, LM; Patel, P; Karra, R; Mainsah, BO, Heart Sound Analysis in Individuals Supported With Left Ventricular Assist Devices., Ieee Trans Biomed Eng, vol 68 no. 10 (2021), pp. 3009-3018 [10.1109/TBME.2021.3060718] [abs].
- Mainsah, BO; Patel, PA; Chen, XJ; Olsen, C; Collins, LM; Karra, R, Novel Acoustic Biomarker of Quality of Life in Left Ventricular Assist Device Recipients., Journal of the American Heart Association, vol 10 no. 6 (2021) [10.1161/JAHA.120.018588] [abs].
- Chu, K; Collins, L; Mainsah, B, A causal deep learning framework for classifying phonemes in cochlear implants, 2015 Ieee International Conference on Acoustics, Speech, and Signal Processing (Icassp), vol 2021-June (2021), pp. 6498-6502 [10.1109/ICASSP39728.2021.9413986] [abs].
- Huang, B; Yang, J; Streltsov, A; Bradbury, K; Collins, LM; Malof, J, GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery, Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2021) [10.1109/JSTARS.2021.3124519] [abs].
- Huang, B; Bradbury, K; Collins, LM; Malof, JM, Do Deep Learning Models Generalize to Overhead Imagery from Novel Geographic Domains? the xGD Benchmark Problem, International Geoscience and Remote Sensing Symposium (Igarss) (2020), pp. 1476-1479 [10.1109/IGARSS39084.2020.9323080] [abs].