Dr. Dusan Gostimirovic聽and Professor Odile Liboiron-Ladouceur, both Electrical and Computer Engineering, for 鈥淧reFab AI Photonics鈥�
Executive summary:
The semiconductor industry can now integrate light on a chip, leading to higher data capacity in communications and many emerging applicationssuch as sensors, optical quantum computing, and optical neuromorphic computing. Light, however, is more susceptible to fabrication process deviations than its electronic counterpart. Our invention uses machine learning (ML) to predict and correct deviations in the design of photonic (optical) integrated circuits prior to nanofabrication, saving on cost, time, and energy. Since the publication of our paper and recent discussions with potential customers at an international conference earlier in November, it is evident that our solution addresses an invaluable need for better design tools that enable the next generation of photonics. Indeed, our technology is the first ML-based solution to correct design prior to fabrication, which will have considerable impact in the industry. The WRSA grant will enable us to deploy our next minimum viable product to gather feedback and validate its performance with a target group of users.
聽This program was made possible thanks to the Chwang-Seto families, in honour of the late Ronald Chwang (B.Eng.'72, D. Sc.'12), a pioneering entrepreneur and venture capitalist who served on the Faculty of Engineering Advancement Board.
