CogSys Lab - Home
Cognitive Sensors Nodes and Systems Lab The cognitive sensor nodes and systems (CogSys) lab aims at cracking the inner workings of cognition for low-footprint adaptive computing. To do so, we embrace the synergies of neuroscience, machine learning / AI, and hardware design, where we combine: a bottom-up approach consisting in diving into neuroscience research to identify, and then to exploit, key computational primitives of the brain, a top-down approach that builds on the versatility and scalability of modern AI research. Tackling an interdisciplinary challenge requires a complementary team that can assemble all pieces of the puzzle at multiple scales. Some of our key research areas include: AI hardware accelerators (recurrent neural networks, graph neural networks, large language models, etc.), neuromorphic engineering and spiking/event-based neural network processors (digital, mixed-signal, in-memory), NeuroAI and learning algorithms (cortical microcircuits, approximations of backprop with scalable learning rules that are local in space and time, Bayesian frameworks, continual learning, few-shot learning, etc.), extreme-edge computing and on-device learning. Click on the People tab to meet us! Upcoming events No scheduled event News 22 April Open PhD vacancy Are you wondering how the neocortex works, how it is related to modern machine learning algorithms, and how this insight can be used to fuel next-gen neuromorphic hardware? The position is open until filled, so please apply early! View Details
