Invited speakers

  • Natalia Berloff, University of Cambridge, United Kingdom, “Space Structure, Basins of Attraction and Manifold Reduction in Ising Machines”
  • Connor Bybee,  University of California, Berkeley, USA “Efficient Optimization with Higher-Order Ising Machines”
  • Kerem Çamsarı, University of California in Santa Barbara, USA “Probabilistic Computing with p-bits: Optimization, Machine Learning and Quantum Simulation”
  • Claudio Conti, Dipartimento di Fisica Sapienza, Rome, Italy, “Optical Spatial Ising Machines and Hyperspins”
  • Massimiliano Di Ventra, University of California, San Diego, USA “MemComputing, long-range order and efficient computation”
  • Aaron Danner, National University of Singapore, Singapore “Photonic Chip-Based Ising Machines”
  • Jérémie Laydevant, USRA/Cornell University, New York, USA “Training an Ising Machine with Equilibrium Propagation”
  • Suyoun Lee, Institute Korea Institute of Science and Technology, South Korea “Nano-oscillator based on Ovonic Threshold Switch (OTSNO) and its application in energy-efficient Ising machine”
  • Daniel Lidar,  University of Southern California, USA “A quantum advantage in approximate optimization using quantum annealing”
  • Artem Litvinenko, University of Gothenburg, Sweden “Time-multiplexed Ising machines based on solid-state delay lines
  • Johan Mentink, Radboud University, “Identifying computational advantage of Ising machines for quantum many-body physics”
  • Masoud Mohseni, Distinguished Technologist at Hewlett Packard Enterprise “Training and Inference in Energy-Based Models with Nonlocal Monte Carlo”
  • Federico Ricci Tersenghi, Sapienza University of Rome, Italy “Physics-inspired hard benchmarks for Ising machines”
  • Ana Rusu, KTH Royal Institute of Technology, Sweden “Analog Ising Machines”
  • Nikhil Shukla, University of Virginia, USA “Computational Capabilities of Oscillator-based Dynamical Systems – Ising Machines and Beyond”
  • Hiroki Takesue, Osaka University, Japan “Coherent Ising machine based on degenerate optical parametric oscillators”
  • Kosuke Tatsumura, Toshiba Corporation, Japan, “Simulated Bifurcation Machines: Enabling NP-hard Optimization-based Judgement in Realtime systems by Quantum-inspired Technology”
  • Zoltan Toroczkai, University of Notre Dame, Notre Dame, USA “Continuous-time Analog Approach to Hard combinatorial Optimization Problems”
  • Davide Venturelli, USRA Research Institute for Advanced Computer Science, Quantum AI Laboratory at NASA ARC, “to be announced”
  • Hyunsoo Yang, National University of Singapore, Singapore “Magnetic tunnel junction based Ising machine”