THz Science and Technology Seminar (TSTS) Series: Terahertz-chip-scale Systems for Intelligent Sensing and 6G Communication: Can AI help?

In collaboration with the Poly-Grames Research Center, IEEE Student Branch of Polytechnique and INRS, STARaCom, and Academy of Science of the Royal Society of Canada, the IEEE Montreal Section and MTT Montreal IEEE Chapter are organizing THz Science and Technology Seminar (TSTS) Series, which will be delivered exclusively online by distinguished THz researchers, engineers, and leaders in the world to present state-of-the-art THz R&D progress, education, and applications. This TSTS series is made possible thanks to the sponsorship and conclusion of the NSERC-Huawei Industrial Research Chair Program. Our first TSTS presentation will be made by Prof. Kaushik Sengupta of Princeton University (9:30 AM – EDT, Dec. 4) Terahertz-chip-scale Systems for Intelligent Sensing and 6G Communication: Can AI help? ABSTRACT: Abstract: Silicon-based Terahertz systems are a field that is only about a decade old. In this time, we have seen a phenomenal growth of silicon systems operating at THz frequencies for a wide range of applications in sensing, imaging and communication. It can be argued that both the ‘THz gap’ and the ‘technology and applications gap’ is closing in meaningful ways in the THz range. Technologies beyond 100 GHz focusing on sensing, imaging and wireless back-haul links are getting attractive as we enter into a new area of highly dense network of autonomous systems requiring ultra-high speed and reliable links. In this talk, I will highlight approaches that cut across electromagnetics, circuits, systems and signal processing to enable THz beamforming arrays, programmable THz metasurfaces with CMOS tiling and physically secure sub-THz links (ISSCC’20, Nature Elec’21). In the end, I will comment on whether AI can help in the synthesis of these complex ICs. Co-sponsored by: PolyGrames, STARaCom, Academy of Science of the Royal Society of Canada Speaker(s):  Kaushik Sengupta , Virtual: https://events.vtools.ieee.org/m/384766