During this webinar a brief introduction to Altair Feko user interface (CADFEKO and POSTFEKO) will be presented, followed by live demo of the Feko to show case simulation of different antennas and application of various solver technologies explained in (https://events.vtools.ieee.org/m/444953). Speaker(s): Gopinath Gampala, Dr. C.J. Reddy Virtual: https://events.vtools.ieee.org/m/445102

The IEEE Magnetics Toronto Section invites you to a distinguished speaker seminar titled "Brain-Inspired Computing Using Magnetic Domain Wall Devices" by Dr. S. N. Piramanayagam. Neuromorphic computing or brain-inspired computing is considered as a potential solution to overcome the energy inefficiency of the von Neumann architecture for artificial intelligence applications . To realize spin-based neuromorphic computing practically, it is essential to design and fabricate electronic analogues of neurons and synapses. An electronic analogue of a synaptic device should provide multiple resistance states. A neuron device should receive multiple inputs and should provide a pulse output when the summation of the multiple inputs exceeds a threshold. Our group has been carrying out investigations on the design and development of various synaptic and neuron devices in our laboratory. Domain wall (DW) devices based on magnetic tunnel junctions (MTJs), where the DW can be moved by spin-orbit torque, are suitable candidates for the fabrication of synaptic and neuron devices . Spin-orbit torque helps in achieving DW motion at low energies whereas the use of MTJs helps in translating DW position information into resistance levels (or voltage pulses) . This talk will summarize various designs of synthetic neurons synaptic elements and materials . The first half of the talk will be at an introductory level, aimed at first-year graduate students. The second half will provide details of the latest research. K Roy, A Jaiswal and P Panda, Naure 575 607-617 (2019) WLW Mah, JP Chan, KR Ganesh, VB Naik, SN Piramanayagam, Leakage function in magnetic domain wall based artificial neuron using stray field, Appl. Phys. Lett., 123 (9) 092401 (2023). D Kumar, HJ Chung, JP Chan, TL Jin, ST Lim, SSP Parkin, R Sbiaa and SN Piramanayagam, Ultralow Energy Domain Wall Device for Spin-Based Neuromorphic Computing ACS Nano 17(7) 6261-6274 (2023) R Maddu, D Kumar, S Bhatti and S.N. Piramanayagam, Spintronic Heterostructures for Artificial Intelligence: A Materials Perspective, Phys. Stat. Sol. RRL 17(6) 2200493 (2023). Speaker(s): Prem Piramanayagam Room: ENG101, Bldg: George Vari Engineering and Computing Centre (ENG), Toronto Metropolitan University, 350 Victoria Steet, Toronto, Ontario, Canada, M5B2K3

From Intelligent Surfaces to Noise-Driven Communication: Innovative Technologies for 6G and Beyond Prof. Ertuğrul Başar Koç University, Turkey – ebasar@ku.edu.tr When: December 6th 2024, 11H00 AM Quebec-Canada Local Time Where: ONLINE VIA ZOOM: https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag6bhGwaOvn9.1 Meeting ID : 815 2108 4215 Password : 018477 Abstract - Our community has witnessed the rise of many exciting communication technologies in recent years. Notable examples include alternative waveforms, massive multiple-input multiple-output signaling, non-orthogonal multiple access, joint communications and sensing, AI-empowered systems, and so on. In this context, 6G wireless networks will inevitably require a rethinking of wireless communication systems and technologies, particularly at the physical layer, since the cellular industry reached another critical milestone with the development of 5G wireless networks with diverse applications. Within this perspective, first, this talk aims to shed light on the most recent developments in reconfigurable intelligent surface (RIS)-empowered communication towards 6G and beyond wireless networks by discussing promising candidates for future research and development. Specifically, we emphasize different RIS architectures and emerging RIS use cases. Second, taking RIS-based radio frequency chain-free transmitters one step further, we put forward the paradigm of noise-driven communication. We discuss the potential of noise-driven communication systems for three purposes: low/zero-signal-power transmission by indexing resistors or other noise sources according to information bits, noise-alike waveform/modulation design for improved communication efficiency, and unconditionally secure key generation using noise-based loops. Biography - [] Prof. Ertuğrul Başar received his Ph.D. degree from Istanbul Technical University in 2013. He is a Professor at the Department of Electrical and Electronics Engineering, Koç University, Istanbul, Turkey, and the director of the Communications Research and Innovation Laboratory (CoreLab). He had visiting positions at Ruhr University Bochum, Germany (2022, Mercator Fellow) and Princeton University, USA (2011-2012, Visiting Research Collaborator). His primary research interests include 6G and beyond wireless networks, communication theory and systems, reconfigurable intelligent surfaces, software-defined radio implementations, waveform design, physical layer security, and deep learning and signal processing for communications. In the past, Dr. Başar served as an Editor/Senior Editor for many journals, including IEEE Communications Letters (2016-2022), IEEE Transactions on Communications (2018-2022), Physical Communication (2017-2020), and IEEE Access (2016-2018). Currently, he is an Editor of Frontiers in Communications and Networks. He is the author/co-author of more than 170 international journal publications and 16 patents that received around 15K citations. He also supervised 5 PhD and 18 master’s students. He is an Associate Member of the Turkish Academy of Sciences (TÜBA). In recognition of his outstanding contributions to physical-layer design for next-generation wireless networks, Prof. Basar was elevated to IEEE Fellow in 2023, becoming one of the youngest IEEE Fellows of Turkey at the age of 37. He is also a Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) and the Artificial Intelligence Industry Academy (AIIA). Recently, Dr. Basar has been selected as an IEEE ComSoc Distinguished Lecturer for the Class of 2024-2025. Speaker(s): Prof. Başar, Virtual: https://events.vtools.ieee.org/m/443554