February 20, 2026, Webb Hall 1100

In this talk, I explore how coupled oscillator networks can be employed to solve a variety of difficult computing problems. These systems are becoming more attractive as an alternative to conventional digital computers due to the increasing energy demands of the latter, particularly for large-scale problems in machine learning and artificial intelligence. The ubiquity of coupled oscillator networks means that oscillator-based computing can be thought of as a universal computing paradigm for systems with a diversity of physical realizations, e.g. as analog circuits, neurological systems, spintronic systems etc. I will focus specifically on oscillator Ising machines (OIMs), networks of phase oscillators that compute minimizers of the Ising model, a model of spin glasses that serves as a proxy for certain NP-hard problems (e.g. the graph maximum cut and Boolean satisfiability problem). I will highlight both the fascinating theory behind OIMs, blending concepts from statistical mechanics, control theory, random matrices, and optimal transport, as well as how these ideas can inform the practical design of the next generation of computing devices.

Ahmed Allibhoy is a postdoctoral scholar at UC Irvine in the Electrical Engineering and Computer Science department. His research interests include online optimization of dynamical systems, control of complex networks, and synchronization in coupled oscillator networks, and their applications to physics, neuroscience, and artificial intelligence.