The award-winning work, titled “Magnetic Tunnel Junction-Based High-Order Probabilistic Ising Machine”, addresses one of the key challenges in modern computing: solving complex combinatorial optimization problems efficiently and at scale.
Combinatorial optimization plays an important role in a wide range of applications, including logistics, scheduling, resource allocation, artificial intelligence, and network design. As these problems grow in complexity, there is an increasing demand for computing hardware that can deliver faster and more energy-efficient solutions.
In this work, Shuhan demonstrated a spin-based probabilistic Ising machine built using magnetic tunnel junction technology. The proposed system is capable of efficiently finding near-optimal solutions to challenging optimization problems, highlighting its potential for high-speed, large-scale, and energy-efficient computing.
The Best Poster Award recognises the quality and impact of research presented at the workshop, which brings together researchers working on Ising machines and emerging computing paradigms for optimization and artificial intelligence.
This achievement highlights the innovative research being conducted by Professor Hyunsoo Yang’s group and the growing contributions of NUS ECE to next-generation computing technologies.
