University of California, Riverside

Department of Electrical and Computer Engineering

Three new faculty in autonomous systems join ECE

Three new faculty in autonomous systems join ECE

Three new faculty in autonomous systems join ECE

July 10, 2017

Autonomous and semi-autonomous systems are being increasingly integrated into modern life.  Examples include self-driving cars, aerial robots for law enforcement or environmental monitoring, and personal robots for assisted living, among others.  In 2016-17, the ECE Department has hired three new assistant professors with research and teaching missions aligned to critical aspects of autonomous systems, further enhancing the existing strengths of the department in this area.  A brief profile of the new faculty is below.




Salman Asif received his PhD degree from the Georgia Institute of Technology in 2013. Prior to joining UCR, he worked as a Senior Research Engineer at Samsung Research America, Dallas and as a Postdoctoral Researcher at Rice University. His research interests lie in the areas of information processing and computational sensing with applications in signal processing, machine learning, and computational imaging. He develops algorithms that can learn and exploit latent signal structures for fast and efficient information recovery. His expertise also includes developing novel computational imaging systems by co-designing hardware and software components.




Konstantinos Karydis received his PhD in 2015 from the University of Delaware.  He was a Post-Doctoral Researcher at the University of Pennsylvania until May 2017 at which time he joined ECE.  His research interests lie in the intersection of dynamical systems, robotics, control and machine learning.  His work introduces mathematical and computational tools for resilient (semi-)autonomous (multi-)robot navigation under uncertainty that arises naturally during robot deployment in real-world settings.  Representative areas of his research include modeling and control of nonlinear stochastic systems, uncertainty quantification and probabilistic model validation, and motion planning, navigation and control of underactuated small-scale legged and aerial robots under uncertainty.  For more information see



Hyoseung Kim received the PhD degree in Electrical and Computer Engineering from Carnegie Mellon University in 2016. His research focuses on building real-time embedded and cyber-physical systems that are robust, predictable and reliable. He likes to develop and evaluate systems techniques, algorithms, and analytical methods for new applications and environments. The benefits of his research have been demonstrated in the context of autonomous vehicles. Other application domains include internet-of-things, aerospace, smart manufacturing, and medical devices.

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