Robot Challenge competition including time trials for robots and oral presentations by the student teams. This is an exciting event for Middle School and High School students who have built robots from scratch. We need Judges! The interaction with working engineers is invaluable. Competition ends early afternoon, depending on the number of entries. Please join us for an entertaining event for all who participate. Co-sponsored by: Baltimore Museum of Industry Agenda: 08:00 - judges check in 08:15 - judges training 08:45 - competition begins 17:00 AWARDS CEREMONY ON LINE 1415 Key Highway, Baltimore, Maryland, United States

The IEEE Vehicular Technology Society (VTS) Philadelphia Chapter is holding a technical meeting. The topic is Electrical Substation Battery Systems. Our speaker is John Kim, Director of Industrial & Utility Markets at EnerSys. This presentation discusses technical aspects of 125 V dc battery systems used in electrical substations. Utility and traction power substations typically use 125 V dc battery systems to provide uninterrupted backup power to protective relay systems, switchgear controls, and switchyard equipment. Batteries are selected based on owners’ preferences and applications. They are sized based on the anticipated dc load profile upon a loss of power. Load profiles often include first minute equipment operation, an 8-hour loss of power, and expected switching operations to restore power. IEEE 485 is a recommended practice for sizing lead-acid batteries for stationary applications. Mr. John Kim will give a presentation on the history of batteries used in substations and today’s latest battery technologies. Attendees may apply for 1.0 PDH provided through the IEEE Certificates Program, accepted in all states. Send $5.00 (USD) payment to Brandon Swartley via Zelle at [email protected] and complete the online evaluation at https://r2.ieee.org/philadelphia-vts/forms/. Evaluation form must be completed and payment received within one week to receive PDH certificate. Speaker(s): John Kim Agenda: Introduction Technical presentation - History of substation batteries - Today’s latest battery technology - Battery and charger selection Questions Virtual: https://events.vtools.ieee.org/m/417421

This program allows you to share your interest in a specific subject by teaching STEM topics to students aged 13-18. IEEE Penn State Harrisburg will supply the equipment you need for the sessions, and we'll also arrange for your transport to the library. If you decide to sign up, you're looking at a commitment of just one hour on a Monday. It’s a direct way to engage with and excite young learners about STEM. Should you choose to participate, you could make a meaningful difference in a student's approach to learning. This initiative is a chance to contribute to the STEM field's future, and it's open to Penn State Harrisburg students interested in volunteering. Co-sponsored by: Middletown Public Library Room: Second floor , Bldg: Middletown Public Library, 20 N Catherine St, Middletown, Pennsylvania, United States, 17057

This initiative provides an opportunity for you to engage with and inspire young students aged 8-13 in the Middletown area by teaching them about STEM topics. Penn State Harrisburg's IEEE will provide all the necessary equipment for your sessions. By signing up, you commit to just one hour on a specific Monday. This represents a straightforward and impactful way to share your passion for STEM with eager young minds. Choosing to be part of this program can significantly influence a young student's learning perspective. It offers a valuable opportunity to play a part in nurturing the next generation's interest in the STEM fields. This opportunity is specifically available to Penn State Harrisburg students eager to volunteer their time and knowledge. Co-sponsored by: Middletown Public Library Room: Second floor , Bldg: Middletown Public Library, 20 N Catherine St, Middletown, Pennsylvania, United States, 17057

Prof Mary (Missy) Cummings (Director of the Mason Autonomy and Robotics Center (MARC) at George Mason University, USA) will present "Self-Driving Cars: The Good, the Bad & the Ugly" at 6pm (UTC+1) / 1pm EDT on 30 April '24. Click (https://www.timeanddate.com/worldclock/fixedtime.html?msg=IEEE+SSIT+Lecture%3A+Self-Driving+Cars%3A+The+Good%2C+the+Bad+%26+the+Ugly&iso=20240430T18&p1=78&ah=1) (https://www.ieee-ukandireland.org/chapters/society-on-social-implications-of-technology/) and SSIT IST-Africa SIGHT are cooperating with a number of IEEE OUs including: New Jersey Coast Section SIGHT; New Jersey Coast IM/Computer Joint Chapter; IEEE Region 1; IEEE Region 2; Vancouver Section Jt. Chapter,TEM14/PC26/E25/SIT30; North Jersey Section SSIT Chapter; Susquehanna Section Computer Chapter; Southeast Michigan Section Vehicular Technology Chapter; Phoenix Section Computer Chapter; Vancouver Section Jt Transportation Chapter, (https://www.ieee-ukandireland.org/chapters/computational-intelligence/); (https://www.ieee-ukandireland.org/chapters/computer-society/), (https://www.ieee-ukandireland.org/chapters/vehicular-technology/) (https://www.ieee-ukandireland.org/chapters/oceanic-engineering-chapter/), Chicago Section Computer Society Chapter and Vehicular Technology Chapter to organise this SSIT Lecture as a joint Webinar on 30 April '24. Registration IEEE and SSIT Members as well as non-IEEE Members are invited to (https://events.vtools.ieee.org/m/406173) and participate. IEEE Members should include their IEEE Membership Number when registering. Access to online Meeting (https://events.vtools.ieee.org/m/406173) will be provided with the link prior to the event. Guest Lecture Focus Self-driving cars have been a dream from almost the time the automobile was invented. With the rise of artificial intelligence (AI), this dream has seemingly become reality with driverless commercial operations already taking place in a handful of cities around the world. However, the recent tragic accident involving a pedestrian and a Cruise self-driving car, as well as a number of high-profile Tesla crashes, raise the possibility that such systems may not actually be as capable as envisioned, and questions have arisen about their safety both nationally and internationally. Given these concerns, it is important to step back and analyze both the actual safety records of these vehicles and just why AI is struggling to operate safely under all conditions in autonomous vehicles. This lecture will highlight the strengths and weaknesses of AI in self-driving cars, as well as in all safety-critical applications, and lay out a roadmap for safe integration of these technologies on public roadways. Speaker(s): Prof Missy Cummings, Agenda: 18:00 (UTC+1) Welcome and Introduction to Guest Speaker 18:05 Lecture 18:45 Questions and Discussions Virtual: https://events.vtools.ieee.org/m/406173

Abstract: Cyber-physical systems (CPS), such as robots and self-driving cars, demand rigorous scheduling to prevent failure, where every millisecond of processing time can be critical. These systems often rely on heterogeneous computing environments, which include CPUs, GPUs, and specialized accelerators, to meet their computational needs efficiently. However, leveraging these diverse processing units to fulfill strict physical constraints remains a significant challenge, as existing scheduling solutions often fall short of addressing the complexities involved in a comprehensive manner. This talk by Dr. Mehmet E. Belviranli delves into the intricate world of creating efficient compute schedules for CPS that not only cater to their diverse computational hardware but also adhere to real-world constraints critical for system safety. We begin by examining the role of neural network (NN) inference in CPS, exploring strategies to balance energy consumption, latency and throughput by distributing the layers of NN across different accelerators. We then introduce a novel, end-to-end framework that integrates physical constraints, heterogeneous computational resources, and latency considerations into a cohesive mixed-integer linear problem, demonstrating through case studies how this approach yields optimal scheduling solutions under varied conditions. Through this exploration, we aim to shed light on the untapped potential of heterogeneous computing in enhancing the reliability and performance of CPS. We will also outline future directions in developing a more robust ecosystem for these complex computing environments, highlighting our contribution to this evolving field. Speaker(s): Dr. Belviranli Virtual: https://events.vtools.ieee.org/m/417666

Join us Thursday, 2 May, for a Special IEEE-USA Washington Update to learn about how the Creating Resources for Every American To Experiment with Artificial Intelligence Act of 2023 (CREATE AI Act) shapes AI development. Our special guest, Katerina (Katie) Antypas from the National Science Foundation, will delve into the establishment of the National Artificial Intelligence Research Resource (NAIRR)—a vital hub for AI researchers and students. Speaker(s): Katerina (Katie) Antypas Virtual: https://events.vtools.ieee.org/m/417483

IEEE ComSoc Norther Virginia chapter and GMU Department of Computer Science invites you to attend the following Distinguished Lecture: Title: Why do small language models underperform? Speaker: Benoît Sagot, Director of Research at INRIA Date: May 2, 2024 Time: 11:00am – 12:00pm In person Location: GMU Fairfax campus, Nguyen Engineering Bldg., Conference Room 4201 Virtual: Microsoft Teams: (https://nam11.safelinks.protection.outlook.com/ap/t-59584e83/?url=https%3A%2F%2Fteams.microsoft.com%2Fl%2Fmeetup-join%2F19%253ameeting_OGUwZGI0OTktNTdhZS00NmNlLWEzZGEtZTJhNGI2Yjg5YmJi%2540thread.v2%2F0%3Fcontext%3D%257b%2522Tid%2522%253a%25229e857255-df57-4c47-a0c0-0546460380cb%2522%252c%2522Oid%2522%253a%2522f9586db0-74ee-4635-a01b-2383b74f8a0c%2522%257d&data=05%7C02%7Ckhassan1%40gmu.edu%7Cc082474ca0814691061508dc69ddedfd%7C9e857255df574c47a0c00546460380cb%7C0%7C0%7C638501649141618849%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=MUjIg2xib2wJ22N21llS60nE%2FSTEPpqg%2FSVOdLXJFHA%3D&reserved=0) Meeting ID: 292 789 339 112 Passcode: jM8w7c --------------------------------------------------------------- Dial-in by phone (tel:+15713972084,,218888141#) United States, Arlington (https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdialin.teams.microsoft.com%2F9424c9fe-3b57-41d6-9131-1d3b9b7cf4a9%3Fid%3D218888141&data=05%7C02%7Ckhassan1%40gmu.edu%7Cc082474ca0814691061508dc69ddedfd%7C9e857255df574c47a0c00546460380cb%7C0%7C0%7C638501649141626316%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=r6YY83JURqPLJf9J2QcdQ5H6w3QBZTlOs4HAUUBvvSQ%3D&reserved=0) Phone conference ID: 218 888 141# For organizers: (https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fteams.microsoft.com%2FmeetingOptions%2F%3ForganizerId%3Df9586db0-74ee-4635-a01b-2383b74f8a0c%26tenantId%3D9e857255-df57-4c47-a0c0-0546460380cb%26threadId%3D19_meeting_OGUwZGI0OTktNTdhZS00NmNlLWEzZGEtZTJhNGI2Yjg5YmJi%40thread.v2%26messageId%3D0%26language%3Den-US&data=05%7C02%7Ckhassan1%40gmu.edu%7Cc082474ca0814691061508dc69ddedfd%7C9e857255df574c47a0c00546460380cb%7C0%7C0%7C638501649141633701%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=KSJGsLYD3jKk7GBpn2XuSPetsCGuvQn9I6sJYXPZfs0%3D&reserved=0) | (https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdialin.teams.microsoft.com%2Fusp%2Fpstnconferencing&data=05%7C02%7Ckhassan1%40gmu.edu%7Cc082474ca0814691061508dc69ddedfd%7C9e857255df574c47a0c00546460380cb%7C0%7C0%7C638501649141641487%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=2ONDG7yjY3RckniAVPkRkliPHOBWdNqIhM2RgAA8O10%3D&reserved=0) Abstract: Language models, and in particular generative and conversational language models, are at the heart of recent advances in natural language processing (NLP). Understanding how these models represent textual content and how they learn these representations still raises multiple research questions. In this talk, I will start from an observation that small models are less efficient than expected. I will show that language models relying on the Transformer architecture tend to produce vector representations that are not isotropically distributed in space. This anisotropy is linked to the way in which these models are learned, which leads to the frequency of the tokens taking a preponderant place in their representation. I will show that this effect has negative consequences on the ability of small models to train satisfactorily (“performance saturation”) but does not seem to affect larger models. I will then describe a new approach for training language models intended to avoid the undesirable effects of this prevalence of frequency information. The resulting “headless” models display a number of advantages over standard models, including on downstream performance. Bio: Benoît Sagot is a computer scientist specialized in natural language processing (NLP). He is a Senior Researcher (Directeur de Recherches) at INRIA, where is heads the INRIA research project ALMAnaCH in Paris, France. He also holds a chair in the PRAIRIE institute dedicated to artificial intelligence, and currently holds the annual chair for computer science in the Collège de France. His research focuses on language modelling, machine translation, language resource development and computational linguistics, with a focus on French in all its form and on less-resourced languages. ________________________________________________________________________________ Co-sponsored by: GMU Department of Computer Science Bldg: Nguyen Engineering Bldg., Conference Room 4201, 4400 University Drive , Fairfax, Virginia, United States, 22030, Virtual: https://events.vtools.ieee.org/m/419402

Normally scheduled ExCom meeting for the 1st Thursday of each month. Agenda: TBD Bldg: MAI, (Checkpoint Surgical) 6050 Oak Tree Blvd, Independence, Ohio, United States, Virtual: https://events.vtools.ieee.org/m/417704