Additional Affiliations

• Assistant Professor of Electrical and Computer Engineering

Employment

• Assistant Professor: The University of Arizona, Department of Electrical and Computer Engineering, 2012-present
• Assistant Professor: The University of Arizona, College of Optical Sciences, 2011-present
• Senior Research Scientist: The University of Arizona, Optical Computing and Processing Lab, 2009-2011
• Graduate Research Assistant: The University of Arizona, Department of Electrical and Computer Engineering, 2002-2007
• Senior Scientist: OmniVision CDM Optics Inc., 2007-2009
• Graduate Research Assistant: University of Cape Town (South Africa), Department of Electrical Engineering, 2000-2001

Professional Affiliations and Activities

• IEEE: Member
• The Optical Society (OSA): Senior Member
  OSA: Conference on Computational Optical Sensing and Imaging, Program Chair
• SPIE: 2019 Senior Member

Awards and Honors

• SPIE: Three-Dimensional Imaging, Visualization and Display II, Best Paper Award, 2010
• University of Capetown (South Africa): International Student Scholarship, 1999 and 2000
• University of Swaziland: Dean's Award for Best Academic Performance, 1998
• University of Swaziland: Vice-Chancellor Award for Best Academic Performance, 1998
• University of Swaziland: Sino-Swazi Award for Best Academic Performance, 1995

Specific Research Interests

• Inverse problems.
• Bayesian inference.
• Information theory.
• Statistical signal processing.
• Image processing.
• Machine learning.
• Computational imaging.
• Compressive imaging.
• Optical engineering.
• High-dimensional imaging.
• Physical optics.

Research Summary

The Intelligent Imaging and Sensing Lab, under the direction of Amit Ashok, is engaged in conducting cutting-edge research to develop the next generation of optical imagers and sensors via the new paradigm of computational sensing. The computational sensing approach exploits knowledge about information-bearing signals and task-application to realize novel optical imager and sensor designs employing reconfigurable-unconventional optics and sophisticated image processing algorithms to achieve revolutionary performance. This multidisciplinary research draws from varied disciples such as physical optics, optical engineering, statistical optics, signal-image processing, machine learning, statistical inference and computer science. Students in the lab get the opportunity to gain hands-on experience with tabletop optical imaging experiments as well as develop advanced image processing algorithms for CPU-GPU based parallel architectures on the lab's computer cluster capable of six teraflops.