معرفی
Raviv Raich is a Professor in the School of Electrical Engineering and Computer Science at Oregon State University. He holds a B.Sc. and M.Sc. from Tel-Aviv University (1994, 1998) and a Ph.D. from Georgia Institute of Technology (2004). His research focuses on signal processing, machine learning, optimization, and probabilistic modeling with applications in adaptive sensing, manifold learning, and sparse signal reconstruction. He has advised numerous graduate students and contributed to impactful work in bioacoustics, hyperspectral imaging, and medical diagnostics. Notable awards include the NSF CAREER Award (2013) and multiple best paper awards. His academic leadership includes editorial roles at IEEE Transactions on Signal Processing and contributions to the IEEE Signal Processing Society.
Education:
- B.Sc. Electrical Engineering, Tel-Aviv University (1994)
- M.Sc. Electrical Engineering, Tel-Aviv University (1998)
- Ph.D. Electrical Engineering, Georgia Tech (2004)
Research Interests:
- Statistical signal processing and machine learning frameworks
- Adaptive sensing strategies for optimization in imaging and tracking
- Manifold learning for high-dimensional data analysis
- Sparse representations in signal reconstruction and inverse problems
Publications: Over 100 peer-reviewed articles in top venues like IEEE Transactions on Signal Processing, IEEE Sensors Journal, and Pattern Recognition Letters, emphasizing theoretical guarantees and practical applications in bioacoustics, medical imaging, and environmental monitoring.
Grants: Active funding from NSF, DARPA, and industry partnerships supporting research in optimization, multi-instance learning, and hyperspectral sensing.
