This month's meeting will be preceded by a lecture hosted at WVU. Lecture will begin at 5:00pm. Please use this zoom link to access the lecture before the ExComm meeting: While this is an in-person seminar, those participants who are unable to be physically present may join remotely by Zoom at the following link: https://wvu.zoom.us/j/96394825532?pwd=CV6fo1mFPr97b9Vp2vYM9qACcvjmHu.1 You may use the following link to write a summary of any monthly updates from your committee, chapter or affinity group. Information received by 8 AM on WEDNESDAY the week of the event will be incorporated into the meeting agenda. IEEE members can access prior meeting minutes hosted on the Pittsburgh Section's (https://drive.google.com/drive/folders/1_UTt5t_dxNP1M5dO87OOeR25t8P7qQHp?usp=sharing). Access to the shared drive is restricted to the (https://www.ieee.org/membership/products/google-apps.html). Meeting Location: Advanced Engineering Research Building WVU 101 Research Way Morgantown, WV 26505 MEETING IS HYBRID. Meeting link and call-in information will be emailed one hour before the event. --------------------------------------------------------------- New to IEEE Pittsburgh? For those new to the Pittsburgh Section Executive and Administrative Meeting, we welcome all IEEE members in the area to attend! This is a standing meeting held on the 3rd Thursday of every month. We review our upcoming activities relevant to engineers in our section. Feel free to use the report link above to ask any questions you may have, join us on Slack, or read through our welcome guide for more information about how you can get involved with IEEE Pittsburgh. (https://ieeepittsburgh.slack.com/) (https://docs.google.com/document/d/1lyWneXlANAQAiJN2p6Bi9kAatooxIQ-YzlGpWRmRGBw/edit?usp=sharing) (https://webinabox.vtools.ieee.org/wibp_calendar/index/R20037) Speaker(s): Dr. Yu Gu, Agenda: First 30 minutes of the event are reserved for socializing. The meeting portion starts at 7 pm (eastern time zone). The meeting agenda will be emailed on Monday the week of the event for early registrants. Bldg: Advanced Engineering Research Building, 101 Research Way, WVU, Morgantown, West Virginia, United States, 26505, Virtual: https://events.vtools.ieee.org/m/437751

Executive Committee planning meeting for upcoming events. All ExCom's are Virtual. These are open to all members including students. At this time the meeting will be remote. Connection information will be sent out at 3:00pm on the day of the meeting to those who have registered. Please register for the meeting by noon of the day of, even if you are an Officer. We meet on the 3rd Thursday of each month We do not meet July, August, and December. With that in mind the 2024 dates are: Jan 18, Feb 15, Mar 21, Apr 18, May 16, Jun 20, Sep 19, Oct 17, Nov 21 Virtual: https://events.vtools.ieee.org/m/432667

IEEE Comsoc Distinguished Lecture Title - More is different: Complex Systems and AI inspiring Future Autonomous Networks and Industry 5.0 Speaker: Dr. Nicola Marchetti, Assoc. Professor, Head of EE Engineering Department, Trinity College Dublin, Ireland. (https://nam11.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.nicolamarchetti.wordpress.com%2F&data=05%7C02%7Ckhassan1%40gmu.edu%7Ca468cfd1e22e40732cd108dcc8fca3e4%7C9e857255df574c47a0c00546460380cb%7C0%7C0%7C638606234647313489%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=NgdXRlPHIiBgYX%2F37e2KvsQf21QDjkHb91spYOCfRpw%3D&reserved=0) Date and time: Friday, October 18, 2024. Time: 11:00am -12:30pm. EDT. Location: Virginia Tech Research Center, 900 N Glebe Rd, Arlington VA 22203 The talk will be on the 2nd floor of VT (there will be appropriate signage in the building). The talk is scheduled for 11:00am-12.30pm, with a small lunch-style reception afterwards. The talk will have an online webinar option, which can be accessed upon registration using the following link: Registration link: https://virginiatech.zoom.us/webinar/register/WN_64O6cpH4Q42q6nf5Ev3f0g Abstract - It is expected that future mobile networks will be ultra-large-scale, highly dynamic, and complex systems, encompassing a massive number of heterogeneous devices. However, the architecture of the current wireless networks is often fixed, and the optimization tasks are defined to cope with specific and identified challenges and services. Hence, the prevailing manual and predetermined optimization and configuration tasks are no longer appropriate for future networks. We are working on resolving such issues by proposing a framework inspired by theories and tools inspired by complex systems science, focusing on the impact of network topology on the system's (i) information representation and transfer, (ii) robustness, and (iii) self-synchronization capabilities. We will also look into how the IoT is creating a new structure of awareness – a cybernetic one – upon physical processes and discuss how industries of different kinds are expected to join soon this revolution, leading to the so-called Factories of the Future, also called Industry 5.0. We will then discuss different problems in this space and how to solve them resorting to tools from mmWave, AI, and semantic communications. Bio: Dr. Nicola Marchetti is Associate Professor in Wireless Communications at Trinity College Dublin, Republic of Ireland, where he leads the Wireless Engineering and Complexity Science lab (WhyCOM). He is an IEEE Communications Society Distinguished Lecturer, an IEEE Senior Member, and a Fellow of Trinity College Dublin. He received the PhD in Wireless Communications from Aalborg University, Denmark in 2007, the MSc in Electronic Engineering from University of Ferrara, Italy in 2003, and the MSc in Mathematics from Aalborg University in 2010. He has authored more than 190 journals and conference papers, 2 books and 9 book chapters, holds 4 patents, and received 4 best paper awards. His research interests span Complex Networks, Mathematics for Communications & Computing, Network Resource Allocation, and Signal Processing for Communications. He serves as Technical Editor for IEEE Network and IEEE Wireless Communications, and has served as an Associate Editor for the IEEE Internet of Things Journal and the EURASIP Journal on Wireless Communications and Networking. Room: 2nd floor, Bldg: Virginia Tech Research Center, 900 N Glebe Rd, Arlington, Virginia, United States, 22203, Virtual: https://events.vtools.ieee.org/m/433047

The continued growth in the digitization of data has created an immense wealth of information. With this data explosion, Artificial Intelligence (AI) techniques are becoming the tools of choice to transform them into knowledge and actionable investments. Digital Transformation (DT) aims to optimize business processes and deliver them digitally. This presentation will highlight some tools and techniques that are enablers for Digital Transformation and will also discuss case studies and different approaches to engage university-industry partnerships to address these growing needs. Presentation by Dr Adel Elmaghraby - Director of Research and Innovation for the Digital Transformation Center, University of Louisville [] Speaker(s): Dr Adel Elmaghraby Virtual: https://events.vtools.ieee.org/m/431172

Millimeter wave automotive radars are highly reliable in all-weather environments and are indispensable for both advanced driver assistant systems (ADAS) and autonomous vehicles. The presentation will highlight recent advancements that continue to push the boundaries of what’s possible in automotive radar technology for fully autonomous driving. Key topics include the use of sparse arrays synthesized with multi-input multi-output (MIMO) radar technology to achieve enhanced angular resolution, innovative waveform designs for mitigating mutual interference between automotive radars, and high-resolution direction-of-arrival (DOA) estimation from a single snapshot. We will also address the challenges of applying MIMO radar theories in automotive contexts, including the use of model-based deep neural networks for high-resolution DOA estimation and the integration of domain-knowledge-guided deep learning in radar perception for autonomous vehicles. Finally, we will discuss future directions for automotive radar, with a focus on enhanced collaborative sensing through the use of multiple automotive radar systems. Speaker(s): Prof Shunqiao Sun Room: 466, Bldg: Packard Lab, 19 Memorial Drive West, Lehigh University, Bethlehem, Pennsylvania, United States, 18015