Advancing Quantum and Nano-Photonics with Machine Learning

Nov 1, 2023
Facebook X LinkedIn Email
Login  Register
About This Webinar
The discovery of unconventional optical designs via machine learning promises to advance on-chip circuitry, imaging, sensing, energy, and quantum information technology. In this talk, Alexandra Boltasseva of Purdue University discusses photonic design approaches and emerging material platforms for showcasing machine learning-assisted topology optimization for optical metasurface designs with applications in thermophotovoltaics, reflective optics, quantum photonic circuitry, and lightsail technology. She demonstrates the effectiveness of autoencoders for compressing the vast design space of metasurfaces into a smaller search space. By employing global optimization via adjoint methods or quantum annealing, one can find the optimal metasurface designs within the smaller space constructed by the autoencoder. The techniques employed in this work extend well beyond the metasurface optimization space and into many inverse design problems for engineering and physics. Machine learning approaches are also applied to advance quantum measurements and superresolution imaging.

Who should attend:
Researchers, engineers, R&D scientists, and manufacturers who design optics or work with machine learning in their industry or use imaging, sensing, quantum, reflective optics, metrology, and thermophotovoltaics in their work. Those who are interested in nano-photonics and quantum photonics who work with optical metasurface design.  

About the presenter:
Alexandra Boltasseva, Ph.D., 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 doctorate in electrical engineering at Technical University of Denmark (DTU) in 2004. Boltasseva specializes in nanophotonics, quantum photonics, and optical materials. She is the 2023 recipient of the R.W. Wood Prize from Optica (formerly OSA, the Optical Society of America), the 2022 Guggenheim Fellow, a 2018 Blavatnik National Award for Young Scientists Finalist, and received the 2013 Institute for Electrical and Electronics Engineers (IEEE) Photonics Society Young Investigator Award, 2013 Materials Research Society (MRS) Outstanding Young Investigator Award, the 2011 MIT Technology Review Top Young Innovator (TR35), the 2009 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 in 2008. She is a fellow of the National Academy of Inventors (NAI) (2020), MRS (2021), IEEE (2020), Optica (2017), and SPIE, the International Society for Optical Engineers (2015). She served on the MRS Board of Directors from 2014 to 2016 and was past editor-in-chief for the Optical Materials Express journal, Optica Publishing group from 2016 to 2021.

Portrait courtesy of Sam Barker Photography
Research & TechnologyImagingOpticsquantummachine visionnano
We use cookies to improve user experience and analyze our website traffic as stated in our Privacy Policy. By using this website, you agree to the use of cookies unless you have disabled them.