Materials Development and Integration Strategies for Neuromorphic Computing and AI Hardware

Neuromorphic and AI computing hardware is trending away from traditional von Neumann computational architectures. This transition is opening the door to a wide range of novel devices and integration solutions. Over the past 10 years, my research group has focused on fabrication and integration strategies for CMOS-compatible, non-volatile, analog memory devices (aka: memristors). These memristive devices have the potential to act as neuronal synapses in neural networks, but can also function as tunable elements in array-based accelerators. Introducing unique materials and novel memristive devices into the traditional CMOS fabrication process presents many challenges, from both the process integration and packaging standpoint. In this presentation I will discuss integration strategies that we have used to develop novel hardware solutions.

Bio: Prof. Cady obtained his BA and Ph.D. from Cornell University in Ithaca, NY. He is currently an Empire Innovation Professor of Nanobioscience in the Colleges of Nanoscale Science & Engineering at SUNY Polytechnic Institute. Prof. Cady has active research interests in the development of novel biosensor technologies and biology-inspired nanoelectronics, including novel hardware for neuromorphic computing.