In this webinar hosted by the Optics in Digital Systems Technical Group, Francesco Da Ros will review some of the promising photon hardware proposals to implement analog photonic computing. A strong focus will be dedicated to programming the hardware to perform the desired computation discussing open challenges and promising directions.

Online (in situ) optimization methods, take into account all the physical effects (including crosstalk, fabrication errors, noise, etc.) of the specific device but generally require a lengthy iterative process and additional monitoring devices integrated throughout the computing circuit. Alternatively, training offline (in silico) models of the full photonic hardware can provide a faster optimization and relax the requirements of additional hardware. However they introduce challenges in terms of model accuracy and necessary measurement to fit the model to the specific device. Combination of data-driven and physics-informed models can be highly beneficial for improving the accuracy of offline models and the models' ability to generalize to multiple devices, as will be discussed.

What You Will Learn:
• A brief overview of the state of the art in photonic analog computing
• Challenges and benefits of in situ and in silico programming approaches
• Data-driven and physics-inspired modeling of photonic integrated devices

Who Should Attend:
• Post Graduate Students
• PhD research scholars
• Early stage researchers/Post Doctoral fellows

About the Presenter: Francesco Da Ros from Technical University of Denmark

Francesco Da Ros is an associate professor in the Machine Learning in Photonic Systems (MLiPS) at DTU Electro. He received his Ph.D. in 2015 from the Technical University of Denmark (DTU) including a research stay at the Fraunhofer Heinrich-Hertz-Institute. Between 2015 and 2018, he worked within the Center for Silicon Photonics for Optical Communications at DTU and joined the MLiPS group in 2019. Dr. Da Ros has co-authored 200+ papers in the fields of optical communication and signal processing, and he is currently leading a Villum Young Investigator project on optical implementations of machine learning techniques (OPTIC-AI). He is an OPTICA Ambassador and Senior Member, an IEEE Senior Member, and is serving in several technical program committees including CLEO (Program Chair 2022, General Chair 2024), ECOC, PSC and SPIE Europe.