• Technical Conference:  05 – 09 March 2023
  • Exhibition: 07 – 09 March 2023
  • San Diego Convention Center, San Diego, California, USA

What Will the Future Machine Learning and Artificial Intelligence Systems Look Like?

Sunday, 06 March 16:00 – 18:30


Sonia Buckley, NIST, USA
Martin Schell, Fraunhofer Institut, Germany
Volker Sorger, George Washington Univ., USA
S.J. Ben Yoo, Univ. of California Davis, USA


What will the future ML and AI Systems look like? Will photonic quantum and neuromorphic computing play a role?

This workshop addresses the future of the machine learning and artificial intelligence systems facing significant challenges from ML related workloads doubling every 3-4 months while Dennard’s law scaling has ceased to keep pace with Moore’s law nearly 15 years ago.  Modern data centers and computing systems are now showing intelligence comparable or surpassing the capabilities of human intelligence, but at the cost of extremely high power consumption.  On the other hand, neuromorphic accelerators promise 3-6 orders of magnitude improvements in energy-efficiency and throughput compared to the traditional von Neumann computing, and quantum computing claims quantum supremacy to solve nearly unsolvable problems in a record time. What will the future ML and AI systems look like? Will quantum and neuromorphic computing play an active role? What role will photonics play in this context?

The workshop will be organized in two parts:

AI/ML Computing & Data Systems at Scale (TRL)
Part I will address the challenges faced by today’s data centers and computing systems in coping with explosively growing ML and AI workloads.  In particular, Part I will discuss future trends and ML and AI computing systems, and covers opportunities for fundamental changes in computing system architectures enabled by intelligent programmable photonics.

AI/ML Emerging Photonic Computing Paradigms
Part II will discuss emerging neuromorphic and quantum computing technologies to efficiently and effectively accelerate ML training and inference workloads. In particular, we will address opportunities and challenges of photonics in computing for future hyperscale data centers and computing systems handling AI and machine learning workloads


Part 1:
Catherine (Katie) Schuman, University of Tennessee, USA
Neuromorphic Computing: From HPC to Edge

Michael Förtsch,  Q.ANT, Germany
The Q.ANT Approach Towards Solving Industry-Relevant Use Cases on Integrated Photonic Quantum Circuits

Behrouz Movahhed Nouri, Optelligence Company, USA
Electronic-Photonic Tensor Processor ASICs

Part 2
Demetri Psaltis, EPFL, Switzerland
History and Rationale for Optics for Computing

Hideo Mabuchi, Stanford University, USA
Coherent Ising Machines

Wolfram Pernice, University of Münster, Germany
Photonic Neuromorphic Processing


Behrouz Movahhed Nouri,
Optelligence Company, USA
Behrouz has expertise in High Tech industry of over 10 years. He is a computer science engineer, whose experience in business is in acquiring funds through investments or sales. Mr. Movahhed is acquainted with markets from all around the globe, including North America, South America, Europe, and Asia. Mr. Movahhed’s firm does continual worldwide agreements with corporations and government agencies in the locations listed above. He has also raised over $188M for project executions and managed a delegation that raised $500M in numerous different sectors.

Michael FörtschQ.ANT, Germany
Michael Förtsch is founder and CEO of Q.ANT, a start-up developing photonic quantum technologies. Q.ANT's product developments include sensors for autonomous driving as well as for human-machine interaction and photonic quantum computing. After studying mathematics and physics, Michael Förtsch earned his doctorate at the Max Planck Institute for the Physics of Light in Erlangen. For his scientific achievements in the field of quantum information processing he was awarded the Otto Hahn Medal by the Max Planck Society. After an international research stay at the National Institute for Standards and Technology in Boulder, he started as a strategy consultant at TRUMPF GmbH + Co. KG in Stuttgart in 2015. After successfully completing several strategy projects, he became the personal assistant to the CTO vice chairman of the management board of the TRUMPF Group in 2016.

Hideo Mabuchi, Stanford University, USA
Hideo Mabuchi received his A.B. (Physics, 1992) from Princeton University and Ph.D. (Physics, 1998) from the California Institute of Technology.  After spending nine years as a faculty member at Caltech he joined the Department of Applied Physics at Stanford University in 2007.  His research group has worked broadly across the field of quantum engineering and currently focuses on two complementary topics: quantum broadband nonlinear photonics and fundamental operating principles of Coherent Ising Machines.

Wolfram Pernice, University of Münster, Germany
Wolfram Pernice received the Dipl. Ing. degree in Microsystems Technology from the University of Freiburg in 2004 and a DPhil in Electrical Engineering from the University of Oxford in 2007. After at Postdoc at Yale University, he joined the Karlsruhe Institute of Technology (KIT) as an Emmy-Noether research group leader in 2011. From 2015 till 2021 he was a professor of physics at the University of Münster. In 2021 he joined the Kirchhoff-Institute of Physics at Heidelberg University. His research interests cover neuromorphic photonics, quantum photonics, circuit optomechanics and non-linear integrated optics.

Demetri Psaltis, EPFL, Switzerland
Demetri Psaltis is Professor of Optics and the Director of the Optics Laboratory at the Ecole Polytechnique Federale de Lausanne (EPFL). He was a professor at the California Institute of Technology from 1980 to 2006. He moved to EPFL in 2007. His research interests are imaging, holography, biophotonics, machine learning, nonlinear optics, electrolysis for hydrogen production and optofluidics. Dr. Psaltis is a fellow of the IEEE, the Optical Society of America, the European Optical Society and the Society for Photo-optical Systems Engineering. He received the International Commission of Optics Prize, the Humboldt Award, the Leith Medal, the Gabor Prize and the Joseph Fraunhofer Award/Robert M. Burley Prize.

Catherine (Katie) Schuman, University of Tennessee, USA
Catherine (Katie) Schuman is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee (UT) in Knoxville, Tennessee.  She received her Ph.D. in Computer Science from UT in 2015, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems.  She served as a research scientist in neuromorphic computing algorithms, software, and applications at Oak Ridge National Laboratory from 2015 until 2021. Katie has over 70 publications as well as seven patents in the field of neuromorphic computing. She received the U.S. Department of Energy Early Career Award in 2019. She co-leads the TENNLab neuromorphic computing research group at UT.