Jelena Vuckovic discusses how combining state-of-the-art optimization and machine learning techniques with high-speed electromagnetic solvers offers a new approach to "inverse" design and implementation of classical and quantum photonic circuits in a variety of materials and with superior properties, including robustness to errors in fabrication and temperature, compact footprints, novel functionalities, and high efficiencies.
About the presenterJelena Vuckovic, Ph.D., is a Jensen Huang Professor in Global Leadership in the School of Engineering, a Professor of Electrical Engineering and by courtesy of Applied Physics at Stanford, where she leads the Nanoscale and Quantum Photonics Lab. She is also a director of Q-FARM, Stanford-SLAC Quantum Science and Engineering Initiative, and is affiliated with Ginzton Lab, PULSE Institute, SIMES Institute, Stanford Photonics Research Center (SPRC), SystemX Alliance, Bio-X, and Wu-Tsai Neurosciences Institute at Stanford.
Vuckovic has received many awards including the James Gordon Memorial Speakership from the OSA (2020), the IET A. F. Harvey Engineering Research Prize (2019), and the Distinguished Scholar award of the Max Planck Institute for Quantum Optics - MPQ (2019). She is a Fellow of the American Physical Society (APS), of the Optical Society of America (OSA), and of the Institute of Electronics and Electrical Engineers (IEEE), as well a member of the scientific advisory board of the Max Planck Institute for Quantum Optics - MPQ (in Munich, Germany), of the Ferdinand Braun Institute (in Berlin, Germany), an advisory board member of the National Science Foundation (NSF) - Engineering Directorate, and a board member of SystemX at Stanford.