The research of the VLSI Information Processing (VIP) group is at the intersection of digital very-large scale integration (VLSI) circuit and system design, wireless communication, as well as signal and image processing, machine learning, and (non-)convex optimization. Our main focus is on integrating computationally complex algorithms into efficient (in terms of power consumption, throughput, and silicon area) application specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs). We are jointly considering theory, algorithm, architecture, and hardware implementation aspects, which enables far more efficient solutions than a conventional, atomistic VLSI design approach that solely focuses on architecture and circuit design. Our current research focus is on theory, algorithms, and VLSI circuits and systems for massive (or large-scale) multi-user multiple-input multiple-output (MU-MIMO) wireless systems, analog-to-feature (A2F) conversion, and real-time signal and image processing applications. In all three fields, we rely on recent progress in graphical models, convex and non-convex optimization, machine learning, compressive sensing, and we develop novel theoretical results and computationally efficient algorithms.