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Advancing Photonic Device Design and Quantum Measurements with Machine Learning
Join the OSA Photonic Metamaterials Technical Group for a webinar with Alexandra Boltasseva from Purdue University on advancing photonic device design and quantum measurements with machine learning. Discovering unconventional optical designs via machine-learning promises to advance on-chip circuitry, imaging, sensing, energy, and quantum information technology. In this webinar, photonic design approaches and emerging material platforms will be discussed showcasing machine-learning-assisted topology optimization for thermophotovoltaic metasurface designs and machine-learning-enabled quantum optical measurements.

Subject Matter Level:
• Intermediate - Assumes basic knowledge of the topic

What You Will Learn:
• Photonic design using machine learning
• Quantum measurements using machine learning

Who Should Attend:
• Graduate students, postdocs, faculty, and industry members interested in photonic design

Jan 27, 2021 04:00 PM in Eastern Time (US and Canada)

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Alexandra Boltasseva
@Purdue University
Alexandra Boltasseva is a Ron and Dotty Garvin Tonjes Professor of Electrical and Computer Engineering with courtesy appointment in Materials Engineering at Purdue University. She received her PhD in electrical engineering at Technical University of Denmark in 2004. Boltasseva specializes in nanophotonics, nanofabrication, optical materials, and quantum photonics. She is 2018 Blavatnik National Award for Young Scientists Finalist and received the 2013 IEEE Photonics Society Young Investigator Award, 2013 Materials Research Society Outstanding Young Investigator Award, the MIT Technology Review Top Young Innovator, the Young Researcher Award in Advanced Optical Technologies from the University of Erlangen-Nuremberg, and the Young Elite-Researcher Award from the Danish Council for Independent Research. She is a Fellow of IEEE, the Optical Society (OSA) and SPIE. She served on MRS Board of Directors and is currently Editor-in-Chief for OSA’s Optical Materials Express journal.