Biography
Primary Research Area
Computer Engineering
Research Interests
Low-power design, reconfigurable computing, platform design, dynamic optimizations, hardware design, real-time systems. Specifically, exploring challenges in leveraging Blockchain technology in Internet of Things (IoT) devices for enhanced data privacy, security, ownership, and monetization. Research focus ranges from holistic system-level layouts to per-device System-on-Chip (Soc) architectural designs considering dynamic and heterogeneous resources for low power-/energy-based Blockchain operations.
PUBLICATIONS:
H. Alsafrjalani and A. Gordon-Ross. “Quality of Service-Aware, Scalable Cache Tuning Algorithm in Consumer-based Embedded Devices,” ACM Great Lakes Symposium on VLSI (GLSVLSI), May 2016.
Ding, A. Lizarraga, A. Shenoy, A. Gordon-Ross, S. Lysecky, and R. Lysecky, “Application-Specific Customization of Dynamic Profiling Mechanisms for Sensor Networks,” IEEE Open Access, Vol 3, Issue 1, pages:1-20, Dec 2015.
A. Munir, A. Gordon-Ross, and S. Ranka, “Multi-core Embedded Wireless Sensor Networks: Architecture and Applications,” IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 6, pp. 1553-1562, June 2014.
A. Munir, A. Gordon-Ross, S. Ranka, and F. Koushanfar, “A Queueing Theoretic Approach for Performance Evaluation of Low-Power Multi-Core Embedded Systems,” Elsevier Journal of Parallel and Distributed Computing, vol. 74, no. 1, pp. 1872–1890, January 2014.
W. Zang and A. Gordon-Ross, “A Survey on Cache Tuning from a Power/Energy Perspective”, ACM Computing Surveys, Volume 45, Issue 3, Sept 2013
Honors and Awards
NSF CAREER Award, 2010
Best Paper Award, International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, 2010
Best Paper Award, ACM Great Lakes Symposium on VLS, 2010
Education
PhD, Computer Science and Engineering, University of California-Riverside, 2007
BS, Computer Science and Engineering, University of California-Riverside, 2000