IEEE North Jersey Section

Dr Rui Li of will take a deep dive into the Multimodal Interaction and Affective Computing Lab (MIAC Lab) at Montclair State with a focus on Multimodal Human-Machine Interaction. This exciting work involves multimodal information processing, immersive interaction, intelligent systems for vehicles and robots. Her passion is for the interdisciplinary study of human emotion, behavior, and cognition to bring about excellent human-machine interaction and intelligent machines. Speaker(s): Dr. Rui Li PhD Virtual: https://events.vtools.ieee.org/m/456316

This talk will feature two families of machine learning, the diffusion network and the transformer. First, the two basic methodologies will be introduced from first principles. Second, two developments from the Virginia Image and Video Analysis laboratory will be described. A diffusion method for multiplicative noise will be outlined. And a special-purpose transformer for recognizing human activity from videos will be explained. The talk will conclude with recommendations regarding research in artificial intelligence. Co-sponsored by: Fairleigh Dickinson University Speaker(s): Dr. Scott Acton Agenda: Registration for the event and refreshments/dinner are complimentary. Venue: Fairleigh Dickinson University 1000 River Road, Building: Muscarelle Center, Room Number: 105 Teaneck, New Jersey, United States 07666 For additional information about the venue and parking, please contact Dr. Hong Zhao [email protected] Virtual: https://events.vtools.ieee.org/m/462787

Robotics Seminar: Foster progress and sustainability in multiple sectors via robotics February 12th, 2025 | CELS 120 | 2:00 PM – 3:30 PM Speaker: Christelle Keefer ABB Inc. Robotics Education Director [] Room: 120, Bldg: CELS, 1 Normal Ave, Montclair, New Jersey, United States, 07043

On-site Registration/Breakfast 7:30 a.m. - 8:30 a.m. Workshop: 8:30 a.m. - 5:00 p.m. On-site Networking Reception: 5:30 p.m. - 7:30 p.m. Both on-site & virtual Complimentary registration is available - on-site - registration deadline 11 February 2025 - includes free breakfast, lunch, & reception! - virtual - registration deadline 14 February 2025 5G is not just the next evolution of 4G technology; it’s a paradigm shift. Not only is 5G evolutionary (providing higher bandwidth and lower latency than current-generation technology), more importantly, 5G is revolutionary—because it is expected to enable fundamentally new applications with much more stringent requirements in latency and bandwidth. 5G should help solve the last-mile problem and provide broadband access to the next billion users globally at much lower cost because of its use of new spectrum and its improvements in spectral efficiency. Today, several standards organizations and forums, namely IEEE, 3GPP, and ITU, are working on defining the architecture and standardizing various aspects of 5G technologies. However, little has been studied to explore how 5G technologies can be useful to tactical and first responder networks. It is important to investigate how tactical and first responder communities can take advantage of 5G technologies to support massive bandwidth, massive sensing, and massive control type applications. IEEE is hosting the workshop in collaboration with the JHU Applied Physics Lab. The workshop's focus is to discuss the applicability of 5G technologies for tactical and first responder networks and related opportunities and challenges. The workshop will provide a platform to bring together 5G experts from industry, academia, and the standards, regulator, and defense communities to discuss various 5G-specific use cases and requirements. The one-day event has invited speakers from DARPA, DHS, FCC, NIST, NSF, Columbia University, NYU, Intel, National Instruments, Nokia, AT&T, CERDEC, IEEE, and 3GPP. This workshop will be a catalyst to develop relevant use cases, drive standards, and investigate deployment suitable for tactical and first responder networks. Full details and the agenda can be found at: https://futurenetworks.ieee.org/conferences/2025-first-responder-and-tactical-networks-workshop For more information, please contact Ashutosh Dutta, IEEE WFRTN Chair, Johns Hopkins University. Email: [email protected] or [email protected] Tel: 908-642-8593 Details on Sponsorship and Exhibit Opportunities can be found at: https://futurenetworks.ieee.org/images/files/IEEE-WFRTN-Sponsor-Brochure_2025_v2.pdf Co-sponsored by: IEEE Future Networks TC, Washington DC & Baltimore Sections Room: Kossiakoff Conference Center, The Johns Hopkins University Applied Physics Laboratory, 11100 Johns Hopkins Road, Laurel, Maryland, United States, 20723, Virtual: https://events.vtools.ieee.org/m/460733

[] Dr Chin is currently a Research Scientist at Discovery Partners Institute, part of the University of Illinois System. He is working on research in mobile social networking, IoT, responsible AI, human-centered AI, and data science. His research interests are in data science, machine learning, IoT, big data, social networking, HCI, ubiquitous computing, web and AI. Speaker(s): Dr. Alvin Chin, PhD Virtual: https://events.vtools.ieee.org/m/456323

SEMINAR OUTLINE: • Fundamentals of dry type transformers • Using transformers for current limitation • Live demonstration of Power Quality solution • Linear vs. non-linear loads • Harmonics • VFD operation • Single phase harmonic solutions • Three phase harmonic solutions • VFD load side filtering • Emerging markets and applications Hammond Power Solutions c/o the IEEE is proud to offer the informative presentation and live demonstration of power quality solutions for variable frequency drives (VFDs). VFDs provide fine motor control and energy savings but they also produce harmonic content on the system. High harmonic content can lead to issues such as: equipment overheating, communication issues, nuisance OCPD trips and possible utility fines. We will present the various transformer filtering technologies and demonstrate how they work. In addition, participants will learn more about dry type transformer ratings, such as K factor, temperature degree rise, etc. for the proper development of engineer’s specifications, as well as transformer applications in commercial/industrial/datacenter projects. Speaker(s): Dave, Chris, Dr. Razak Agenda: PLEASE NOTE THE CHANGE IN TIME FOR THIS PARTICULAR SEMINAR. WE WILL BEGIN AT 8AM AND WRAP UP BY NOON. The seminar fee includes lunch, refreshments and handouts. Non-members joining IEEE within 30 days of the seminar will be rebated 50% of the IEEE registration charge. Four hours of instruction will be provided. If desired, IEEE Continuing Education Units (0.4 CEUs) will be offered for this course - a small fee of $55 will be required for processing. Please pay attention to the “Registration Fee” and choose the appropriate choice either with or without CEUs. CEU Evaluation Form can be found at: (https://innovationatwork.ieee.org/ieee-pes-northjersey-certificates/) Room: Auditorium, Bldg: PSE&G - Hadley Road Facility, 4000 Hadley Road, South Plainfield, New Jersey, United States, 07080

Special Presentation by Dr. Mahdi Boloursaz Mashhadi (U. of Surrey, UK) Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Date/Time: Thursday, 20 February 2025 @ 12:00 UTC Topic: Goal-Oriented Generative Semantic Communications with Multimodal LLMs Abstract: The integration of Generative Artificial Intelligence (GenAI) models with wireless networks provides ample opportunities to develop innovative technologies with transformative potential. One such technologies is Generative Semantic Communications (Gen SemCom), which leverages the capabilities of state-of-the-art GenAI models to develop ultra-low bitrate semantic communication systems aiming to transmit only the semantic message of interest with high fidelity. GenAI models such as Diffusion, Flow-based, and GAN models, can learn the general distribution of natural signals through training and generate new samples at the inference time. This generative process can be guided or conditioned to synthesize outputs with a desired semantic content. In Gen SemCom, the semantics of interest are extracted at the transmitter, communicated over the channel, and then used at the receiver to guide a generative model to locally synthesize a semantically consistent signal. The emerging generative foundation AI models and Multi-modal Large Language Models (MLLMs) can be leveraged in the SemCom framework to convey the most important semantics of the source signal to the receiver through textual prompts in a super compact form. These models possess a vast general knowledge through intensive pre-training on huge amount of data. This alleviates the need for a shared knowledge base/graph between the semantic transmitter and receiver, obviating the need for corresponding knowledge sharing overheads imposed in current SemCom frameworks. Despite the above benefits, deployment of such large models in the SemCom framework is challenging due to their high computational complexity, energy consumption, and latency. This talk focuses on novel generative approaches to semantic communications, the fundamental bounds on Gen SemCom, and its emerging applications in wireless networks. It investigates the challenges and opportunities of deploying Gen SemCom at various layers in future wireless networks and provides the corresponding future research directions. Speaker: [] Dr. Mahdi Boloursaz Mashhadi (Senior Member, IEEE) is a Lecturer at the 5G/6G Innovation Centre (5G/6GIC) at the Institute for Communication Systems (ICS), University of Surrey (UoS), and a Surrey AI fellow. His research is focused at the intersection of AI/ML with wireless communication, learning and communication co-design, generative AI for telecommunications, and collaborative machine learning. He received B.S., M.S., and Ph.D. degrees in mobile telecommunications from the Sharif University of Technology (SUT), Tehran, Iran. He has more than 40 peer reviewed publications and patents in the areas of wireless communications, machine learning, and signal processing. He is a PI/Co-PI for various government and industry funded projects including the UKTIN/DSIT 12M£ national project TUDOR. He received the Best Paper Award from the IEEE EWDTS conference, and the Exemplary Reviewer Award from the IEEE ComSoc in 2021 and 2022. He served as a panel judge for the International Telecommunication Union (ITU) on the “AI/ML in 5G” challenge 2021- 2022. He is an editor for the Springer Nature Wireless Personal Communications Journal. Co-sponsored by: Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Virtual: https://events.vtools.ieee.org/m/463737

The Internet of Vehicles (IoV) is a network that connects vehicles, infrastructure, and devices to enable seamless communication and data sharing. Vehicular VLC communication is fast emerging due to the widespread deployment of LED lights. Aerial terrestrial networks (ATNs) with the widespread deployment of unmanned aerial vehicles (UAVs) will also play a vital role in the IoV. Free-space optical (FSO) communication links can be effectively deployed between aerial bodies and vehicles. However, outdoor FSO and VLC links suffer from pointing error, fast varying channel conditions, sunlight and atmospheric impairments. This talk will cover various research topics in this area. Co-sponsored by: Fairleigh Dickinson University Speaker(s): Dr. Xavier Fernando Agenda: Registration for the event and refreshments/dinner are complimentary. Venue: Fairleigh Dickinson University 1000 River Road, Building: Muscarelle Center, Room Number: 105 Teaneck, New Jersey, United States 07666 Virtual: https://events.vtools.ieee.org/m/467003

[] Dr Kootsookos, IEEE Connecticut Section Chair. Dr Kootsookos will describe his career preparation. He will conduct a deep dive of his field as an expert in patent arbitration providing source code reviews. He is a teacher of telecommunications, signal & image processing, circuit analysis, digital hardware, and various software engineering courses at the University of New Haven, Fairfield University, Central Connecticut State University, and CT State Community College, Middlesex in the US and the Australian National University and University of Queensland in Australia. He is a Researcher: Signal processing research: more than 40 papers in conferences and international journals in signal, video, and image processing; Full life-cycle systems engineering: requirements, analysis, design, verification, validation, delivery; Quality processes worked with: IS09001-2000, CMMI, ACE (UTC’s Achieving Competitive Excellence). Speaker(s): Dr. Peter James Kootsookos, PhD Virtual: https://events.vtools.ieee.org/m/456326