Optical/Photonics Computing System (OPTSys) Seminar Series
A series of talks from experts in optics and photonics
In a world where Moore's law is encountering the physical limits and electronic circuits, after six decades of development, face formidable barriers, the pursuit of novel computing paradigms has become paramount. Among these frontiers, optical and photonic systems have emerged as a driving force. Yet, they present a unique challenge – the complexity of understanding optical/photonic systems, governed by Maxwell's equations, surpasses that of electronic circuits.
This is where our seminar series steps in! We have assembled some of the brightest minds from both industry and academia to bring the cutting-edge field of optical/photonic systems to your doorstep. Whether you are an enthusiastic junior student seeking to explore the wonders of this domain or a seasoned faculty member aiming to delve deeper, our seminars offer an ideal platform. Expect dynamic discussions, inspiration, and the potential for fruitful collaborations. Join us in shaping the future of computing. The future has arrived, and it's illuminated by optics!
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Upcoming Seminar
Title: Meta-Optical Encoders for High Resolution Real Time Computer Vision
Abstract: Light’s ability to perform massive linear operations parallelly has recently inspired numerous demonstrations of optics-assisted artificial neural networks (ANN). However, a clear advantage of optics over purely digital ANN in a system-level has not yet been established. While linear operations can indeed be optically performed very efficiently, the lack of nonlinearity and signal regeneration require high-power, low-latency signal transduction between optics and electronics. Additionally, a large power is needed for lasers and photodetectors, which are often neglected in the calculation of the total energy consumption. Here, instead of mapping traditional digital operations to optics, we co-designed a hybrid optical-digital ANN, that operates on incoherent light, and is thus amenable to operations under ambient light. Keeping the latency and power constant between a purely digital ANN and a hybrid optical-digital ANN, we identified a low-power/ latency regime, where an optical encoder provides higher classification accuracy than a purely digital ANN. We estimate our optical encoder enables ~ 10kHz rate operation of a hybrid ANN with a power of only 23mW. However, in that regime, the overall classification accuracy is lower than what is achievable with higher power and latency. Our results indicate that optics can be advantageous over digital ANN in applications, where the overall performance of the ANN can be relaxed to prioritize lower power and latency.
Biography: Arka Majumdar is a Professor in Electrical and Computer Engineering and Physics at the University of Washington. He received B. Tech. from IIT-Kharagpur (2007), where he was honored with the President’s Gold Medal. He completed MS (2009) and Ph.D. (2012) in Electrical Engineering at Stanford University. He spent one year at the University of California, Berkeley (2012-13), and then in Intel Labs (2013-14) as postdoc before joining UW. Prof. Majumdar is the recipient of multiple Young Investigator Awards from the AFOSR (2015), NSF (2019), ONR (2020) and DARPA (2021), Intel early career faculty award (2015), Amazon Catalyst Award (2016), Alfred P. Sloan fellowship (2018), UW college of engineering outstanding junior faculty award (2020), iCANX Young Scientist Award (2021), IIT-Kharagpur Young Alumni Achiever Award (2022) and DARPA Director’s Fellowship (2023). He is co-founder and technical advisor of Tunoptix, a startup commercializing software defined meta-optics.
Date and Time: April 11, 2025, 5:00 pm - 6:00 pm (U.S. Eastern Time)
Zoom Link: https://mit.zoom.us/j/95637372176
Organizers
Acknowledgment
This seminar was made possible through the generous contributions of our presenters and the active participation of our audience. Particualrly, we would like to extend our gratitude to the following individuals for their invaluable help in refining this seminar and making it accessible to a wider audience: Hanrui Wang.