Professor in the Practice
1983 B.S. Electrical Engineering, Purdue University
1986 M.S. Electrical and Computer Engineering, University of Wisconsin - Madison
1991 Ph.D. Electrical and Computer Engineering, University of Wisconsin - Madison
Complex Emergent Systems; Feedback Control of Networked Systems; Statistical Signal Processing; Pattern Recognition; Earth Science Applications of Signals and Systems Theory.
Dr. Saleh received a PhD in electrical and computer engineering from the University of Wisconsin-Madison in 1991 in the area of robust feedback control theory. He joined Shell Development Company in Houston in 1991 and served as a research engineer until 2003 focusing on applications of advanced digital signal processing and systems theory to seismic data processing and interpretation, including statistical pattern recognition, noise attenuation, data compression, and novel applications of multi-dimensional hexagonal sampling to speed up seismic imaging. From 2004 to 2008, Dr Saleh led the New Detection Methods R&D team in Shell International E&P Inc with responsibility for developing and deploying new geophysical techniques beyond traditional seismic methods, with emphasis on controlled-source electromagnetics and high-resolution gravity and magnetic capabilities. From 2009 to 2018, Dr Saleh managed Shell’s Integrated Geoscience R&D program, a large international multi-disciplinary team focused on creating new exploration technologies via the application of recent breakthroughs in computational science and machine learning to integrate the latest advances in geology, geophysics, and petrophysics. The program was also responsible for developing deep-water natural seep detection capabilities using autonomous underwater vehicles. After retiring from Shell, Dr Saleh joined Rice University as Professor in the Practice, where his current research interests are focused on complex emergent systems and their applications in engineering and the natural sciences, with particular emphasis on feedback control of multi-agent networks.