Brandon Lucia is an assistant professor in the Department of Electrical and Computer Engineering at Carnegie Mellon. He researches the boundary between computer architecture, computer systems, and programming languages. He leads the abstract research group.
Some of his current research interests include: making intermittent computing devices that harvest energy from their environment and are programmable, reliable, and robust to common-case power failures. These devices are really exciting because they are a great fit for sensing, medical implants, "extreme" scenarios, and many other applications. He also researches the need to create better software systems and computer architectures that make parallel computing correct, reliable, and efficient. The problem space is especially interesting now with the end of Moore's Law and Dennard Scaling, and the move to crazy heterogeneous parallel systems, approximate computing, distributed system architectures, and emerging (e.g., non-volatile, biological) technology maturing and becoming useful.
Orbital Edge Computing in Smart Nanosatellites
Energy Harvesting Computers: Extracting Energy from the Environment
Assistant Professor of Electrical and Computer Engineering Brandon Lucia designs the basic technology to support “energy harvesting computers,” or devices that can perform computations, sense their environments, and communicate using energy that they extract from their environments.
2013 Ph.D., Computer Science and Engineering, University of Washington
2010 MS, Computer Science and Engineering, University of Washington
2007 BS, Computer Science, Tufts University
Computing at the edges of the Earth—and beyond
Brandon Lucia has developed new hardware and software that enables reliable sensing and processing onboard nanosatellites smaller than the size of a playing card.
Lucia quoted on novel memory compression technique
ECE’s Brandon Lucia was recently quoted in a Technology Networks article about a novel memory compression technique developed by MIT researchers. Lucia praises the MIT researchers for finding a way to make systems “faster and more efficient with novel computer architecture features.”
Intelligence beyond the edge
Brandon Lucia, Nathan Beckmann, and their student present first-ever demonstration of machine learning inference using deep neural networks on a batteryless, intermittent computing device at ASPLOS 2019.
ACM Digital Library
Lucia and students receive Best Paper Award at ASPLOS
ECE’s Brandon Lucia and his students were awarded a Best Paper Award for their work on software for energy responsiveness in energy-harvesting devices.
Smarter networks to connect the edge to the cloud
Carnegie Mellon University will lead a $27.5 million Semiconductor Research Corporation (SRC) initiative to build more intelligence into computer networks.
Association for Computing Machinery
Lucia featured in People of ACM
ECE’s Brandon Lucia was featured in ACM’s People of ACM bulletin.
Lucia’s paper selected as IEEE Micro’s Top Picks
A paper from Brandon Lucia and his research group has been selected as one of IEEE Micro’s 12 top picks of all computer architecture papers published in 2016.