Alexandra Boltasseva

Advancing Photonics 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 talk, photonic design approaches and emerging material platforms will be discussed showcasting machine-learning-assisted topology optimization for thermophotovoltaic metasurface designs and machine-learning-enabled quantum optical measurements.

Bio

Alexandra Boltasseva is a Professor at the School of Electrical&Computer Engineering at Purdue University. She received her PhD in electrical engineering at Technical University of Denmark, DTU in 2004. She is 2018 Blavatnik National Award for Young Scientists Finalist and received the 2013 IEEE Photonics Society Young Investigator Award, 2013 Materials Research Society (MRS) Outstanding Young Investigator Award, the MIT Technology Review Top Young Innovator (TR35), the Young Researcher Award in Advanced Optical Technologies from the University of Erlangen-Nuremberg, Germany, and the Young Elite-Researcher Award from the Danish Council for Independent Research. She is a Fellow of the OSA, IEEE and SPIE. She served on MRS Board of Directors and is Editor-in-Chief for OSA’s Optical Materials Express.