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Engineering | School of Electrical, Computer and Energy Engineering

Suren Jayasuriya

Assistant Professor

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Research Expertise: Computational Imaging and Photography, Computer Vision, Sensors

Suren Jayasuriya joins ASU in Spring 2018 as an assistant professor jointly between the departments of Arts, Media and Engineering (AME) and Electrical, Computer, and Energy Engineering (ECEE). Prior to this, he was a postdoctoral fellow at the Robotics Institute at Carnegie Mellon University under the guidance of Dr. Srinivasa Narasimhan. He received his Ph.D. in 2017 from the ECE Department at Cornell University advised by Dr. Alyosha Molnar, and a B.S. in mathematics and a B.A. in philosophy from the University of Pittsburgh in 2012. His research focuses on designing new types of computational cameras, systems, and visual computing algorithms that can extract and understand more information from the world around us.


Ph.D., electrical and computer engineering, Cornell University, 2017

M.S., electrical and computer engineering, Cornell University, 2015

B.S. in mathematics, University of Pittsburgh, 2012

B.A. in philosophy, University of Pittsburgh, 2012

Recognition and awards:

NSF Graduate Research Fellowship (2013), Qualcomm Innovation Fellowship (2015), Cornell ECE Outstanding Ph.D TA Award (2015), Best paper award at ICCP 2014

Selected publications:

H. Chen, S. Jayasuriya, J. Yang, J. Stephen, S. Sivaramakrishnan, A. Veeraraghavan, A. Molnar, “ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels”, in Computer Vision and Pattern Recognition (CVPR), June 2016.

S. Jayasuriya, A. Pediredla, S. Sivaramakrishnan, A. Molnar, A. Veeraraghavan, “Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging”, in International Conference on 3D Vision (3DV), October 2015.

M. Hirsch, S. Sivaramakrishnan, S. Jayasuriya, A. Wang, A. Molnar, R. Raskar, G. Wetzstein, “A Switchable Light Field Camera Architecture using Angle Sensitive Pixels and Dictionary-based Sparse Coding”, in IEEE International Conference on Computational Photography (ICCP), May 2014.