The ubiquity of modern communications systems has revolutionized the way we interact both with other people and with machines

We believe that interdisciplinary and cross-layer research, ranging from information-theoretic principles to VLSI implementation, is the most promising way to make future communications systems even faster, more reliable, and more energy efficient. For this reason, our work lies on the intersection between communications, hardware design, and machine learning. The specific research activities of our lab include algorithm and architecture co-design of VLSI circuits for communications, error-correction coding theory and practice, non-linear signal processing, massive MIMO, as well applications of approximate computing and machine learning to signal processing for communications.