IEEE North Jersey Section

Passivity theory is one of the cornerstones of control theory providing a systematic way to study the stability of interconnected systems. In practice, many systems are not passive, and must be passivized in order to be included in the framework of passivity theory. Input-output (loop) transformations are the most general tool for passivizing systems. In this paper, we propose a characterization of all possible input-output transformations that map a system with given shortage of passivity to a system with prescribed excess of passivity. We do so by using the connection between passivity theory and cones for SISO systems, and using the S-lemma for MIMO systems. We also present several possible applications of our results, including simultaneous passivation of multiple systems or with respect to multiple equilibria, as well as optimization problems such as $\mathcal{L}_2$-gain minimization. Speaker(s): Daniel Zelazo Agenda: - Talk by Daniel Zelazo at 11:00 am - Lunch box after the talk at 12:00 pm - You don't have to be an IEEE member to attend this meeting. Room: 202, Bldg: ECE, 141 Warren St, New Jersey Institute of Technology, Newark, New Jersey, United States, 07103

In this webinar, we will discuss the newly released ISO standard, ISO/IEC 42001: Artificial Intelligence Management System and its impact on the governance of AI. We will go over the context of the standard, it’s objectives, and the new framework it sets to help organizations build a responsible AI practice, develop an ethical practice, and build a long-term AI strategy. We will also address implications of the EU AI Act on U.S technology companies, and the impact of the EU Act on the issue of conformity assessment and standardization. Finally, we will discuss linkages between 42001 and the NIST Risk Management Framework, and go over the state of federal and local government AI regulations in the U.S Co-sponsored by: Ali Daneshmand Speaker(s): Sid Ahmed, Agenda: Virtual: https://events.vtools.ieee.org/m/428548

The IEEE North Jersey Section's Executive Committee (EXCOM) monthly meeting will be held hybridly. The EXCOM meeting starts at 6:30 pm EST and typically ends at 8:30 pm. The meeting is meant to discuss and coordinate the activities of the Section and its Chapters and Groups, as well as new initiatives. Everyone is welcome to attend this meeting. Please register in advance for this meeting using vTools (Please make a note if you join the meeting remotely) You can change/cancel the registration if your plans change. For more information, please contact our IEEE North Jersey Section Chair Hong Zhao ([email protected]) , or Secretary, Adriaan van Wijngaarden, ([email protected]). Location: New Jersey Institute of Technology To join remotely by the following Zoom link: https://fdu.zoom.us/j/99736508515 Meeting ID: 997 3650 8515 Note: If you are unable to join the meeting, please send your chapter activity report to the section chair at [email protected] Agenda: 06:30 pm - 06:45 pm Networking 06:45 pm - 08:30 pm IEEE North Jersey Section Executive Committee Meeting The meeting agenda typically includes news related to the IEEE and the IEEE North Jersey Section, Secretary and Treasurer reports, Chapter and Affinity Group reports, Committee reports, and reports by various Chairs and Representatives, Committee Chairs, and planning, and new initiatives. Room: ECE 202, Bldg: Electrical and Computer Engineering (ECE) Building, University Heights, Newark, New Jersey, United States, 07102, Virtual: https://events.vtools.ieee.org/m/441739

Distinguished Lecture (Virtual) - Civilized Collaboration: Ethical architectures for enforcing legal requirements and mediating social norms in Human-robot Interaction Prof. Ronald C. Arkin, Georgia Tech, IEEE Fellow Abstract: The ways in which we treat each other, typically underpinned by an ethical theory, serve as a foundation for civilized activity. Bounds and requirements are established for normal and acceptable interactions between humans. If we are to create robotic systems to reside among us, they must also adhere to a set of related values that humans operate under. This talk first describes the importance of such conventions in human-robot interaction, then outlines a way forward including the difficult research questions remaining to be confronted in ethical human robot interaction (HRI). In particular, examples involving architectures using ethical governors, moral emotions, responsibility advisors and theories of mind are described in two quite different contexts: warfare and the maintenance of human dignity in healthcare. Even the role of deception must be considered as an important adjunct to HRI, as it may yield more effective intentional and autonomous social robots if properly deployed. Finally, we can consider how robots may eventually be able to engineer more socially just human beings via nudging and the ethical questions associated with using such devices. Prof. Ronald C. Arkin is Professor Emeritus with the College of Computing at Georgia TechProf. Arkin was named a Distinguished Lecturer for the IEEE Society on Social Implications of Technology in 2012 and a Distinguished Visitor for the IEEE Computer Society in 2023. He was elected a Fellow of the IEEE in 2003. Co-sponsored by: New York Section and Region 1 & Region 2 Computer Society Speaker(s): Prof. Arkin , Agenda: - Event Agenda - Event Agenda: 6:00 PM Welcome Remark – IEEE NY Section 6:10 ~7:10 PM (Presentation- Prof. Ronald C. Arkin, Georgia Tech, IEEE Fellow, Civilized Collaboration) 7:10 PM Q/A The event is free to attend. ALL ARE WELCOME Virtual: https://events.vtools.ieee.org/m/434465

Friday, November 15, 2024, Life Member Luncheon at Casa Bella, 300 US-46, Denville, NJ 07834 with Presentation on Artificial Intelligence: What is AI, How does it work, Can it replace us, AI and the Arts, Industry, Music, and the future. AI in the wrong hands, etc. Fill out registration, send a check of $10 per person to Michael Miller, 5 Cliff Road, Apt. D1, Woodland Park, NJ 07424. Your check will be returned to you at the door. Questions: Phone 732-494-1196 or email: [email protected] Please Complete registration by November 1 Questions: Phone 732-494-1196 or email [email protected] Co-sponsored by: Kenneth Oexle Bldg: Restaurant - 1st level, Casa Bella, 300 US-46, Denville, New Jersey, United States, 07834

Special Presentation by Dr. Farhad Rezazadeh (CTTC, Spain) Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Date/Time: Thursday, November 21st, 2024 @ 12:00 UTC Topic: Toward Trustworthy AI/ML in 6G Networks through Explainable Reasoning Abstract: This talk emphasizes the importance of trustworthy Artificial Intelligence (AI) in 6G networks in response to growing global attention on AI governance. Notable initiatives such as the White House's Executive Order on the Safe, Secure, and Trustworthy Development and Use of AI, DARPA's Assured Neuro-Symbolic Learning and Reasoning and eXplainable AI (XAI) programs, and the European Union's AI Act, highlight the increasing regulatory focus on AI transparency and responsibility. As 6G networks transition from AI-native to automation-native, the need for explainability and trustworthiness becomes critical, especially in mission-critical and high-stakes applications. Traditional post-hoc explainability methods, which aim to explain AI decisions after they are made, are no longer adequate in complex network environments. Instead, in-hoc explainability or explanation-guided techniques – where explanations guide the learning process itself – is emerging as a crucial approach for establishing trust in AI systems from the ground up. Indeed, integrating explanatory mechanisms directly within AI learning models enables transparent decisions and enhances learning. Furthermore, incorporating neuro-symbolic approaches, which combine neural networks with symbolic reasoning, provides a robust framework to tackle the increasing complexity of 6G networks. By integrating these approaches, AI systems can make more explainable, contextually guided decisions, boosting trust and performance while mitigating risks associated with black-box AI models. Speaker: Farhad Rezazadeh received his Ph.D. degree (Excellent Cum Laude) in Signal Theory and Communications from the Technical University of Catalonia (UPC), Barcelona, Spain. He is currently a researcher (Sr. Applied AI Engineer) at the Telecommunications Technological Center of Catalonia (CTTC), Barcelona, Spain. He participated in 8 European and National 5G/B5G/6G R&D projects with leading and technical tasks in the areas of Applied AI. His AI innovation in B5G/6G resource allocation was recognized as a great EU-funded Innovation by the European Commission's Innovation Radar. He was awarded the first patent connected to the H2020 5G-SOLUTIONS project. He was a secondee at NEC Lab Europe and had scientific missions at TUM, Germany, TUHH, Germany, and UdG, Spain. He is a Marie Sklodowska-Curie Ph.D. grantee, winning five different IEEE/IEEE ComSoc grants, two European Cooperation in Science and Technology grants, and a Catalan Government Ph.D. Grant. He is an active member of ACM Professional, IEEE Young Professionals, and IEEE Spain - Technical Activities and Standards, with more than 29 top-tier journals/conferences and book chapters. He actively serves as Organizing, Chair, Reviewer, and TPC member in IEEE and Guest Editor for Elsevier. He has over 140 verified reviews for peer-reviewed publications. He coordinates the IEEE Trustworthy Internet of Things (TRUST-IoT) working group within the IEEE IoT Community. Co-sponsored by: Toward Trustworthy AI/ML in 6G Networks through Explainable Reasoning Virtual: https://events.vtools.ieee.org/m/443359