Duncan Elliott

Biography

Duncan G. Elliott received his BASc degree in engineering science and PhD degree in electrical and computer engineering from the University of Toronto, Toronto, ON, Canada, in 1998. He is currently a Professor with the Department of Electrical and Computer Engineering at the University of Alberta. Previously, he was with Nortel in data communications, MO-SAID Technologies as a DRAM designer, and IBM Microelectronics as a contractor in application-specific memory design. He spent his last sabbatical at the MIT Microsystems Technology Laboratories. His research interests include logic-enhanced memories, computer architecture, 3-D IC architecture, high-speed circuits, and merged microfluidic-microelectronic systems. Prof. Elliott is a member of the IEEE Solid-State Circuits, Circuits and Systems, Computer, and Communications Societies and the ACM. He was the 2001 winner of the Colton Medal in microelectronics for his work on Computational RAM, which has been commercialized.

Research Interest

RF Circuits and Architectures Innovating at the architectural level to build phase lock loops with faster acquisition times & higher speeds, new architecture for integrated phased array radar Spacecraft Design, Satellite Systems Open source cubesat circuit boards, firmware, designs Electronics for communications, phased array antennae, reliable hardware & software real-time systems Autonomous Aircraft UAVs (unmanned aerial vehicles) and sensors Microfluidic-Electronic Systems Microfluidic and integrated instrumentation for DNA analysis Multi-valued DRAMs Storing multiple levels (and therefore multiple bits) per DRAM cell can increase the density and lower the cost. This is an idea which has been around, but new circuit techniques show promise in canceling the effects of IC process variations. Computational RAM:. Computational RAM is memory with SIMD processors at the sense amps which runs GIPS around the CPU. The processing should be placed in the memory because there's 3000 times the memory bandwidth in a workstation's main memory than at the processor. I back up my claims with silicon, parallel applications and a programming language. Research topics are available in computer architecture and VLSI design. Digital FEC Decoders Low-power high-throughput circuits for LDPC encoding and decoding Parallel Processing Using massively parallel processing to solve problems in image and signal processing, VLSI CAD, optimization and data mining.