IEEE North Jersey Section

The role of Electromagnetic (EM) fields in our lives has been increasing. In areas where EM fields have critical importance are communication, remote sensing, integrated command/ control/surveillance systems, intelligent transportation systems, medicine, environment, education, marketing, and defense. We have witnessed the transformation from Engineering Electromagnetics to Electromagnetic Engineering for the last few decades after being surrounded by EM waves everywhere. Among many others, EM engineering deals with a broad range of problems from antenna design to EM scattering, indoor–outdoor radio wave propagation to wireless communication, radar systems to integrated surveillance, subsurface imaging to novel materials, EM compatibility to nano-systems, electroacoustic devices to electro-optical systems, etc. The range of the devices we use in our daily lives has extended from DC to Terahertz frequencies. We have had large-scale (kilometers-wide) and small-scale (nanometers) EM systems. Many of these systems are broadband and digital and must operate nearby, which results in severe EM interference problems. Engineers must take EM issues into account from the earliest possible design stages. This necessitates establishing an intelligent balance between a strong mathematical background (theory), engineering experience (practice), and modeling and numerical computations (simulation). This Distinguished/keynote lecture aims to look broadly at current complex EM problems and particular teaching/training challenges confronting wave-oriented EM engineering in the 21st century in a complex computer and technology-driven world with rapidly shifting societal and technical priorities. Co-sponsored by: IEEE AP-S Co-sponsor DL Talk by Dr. Levent Sevgi Speaker(s): Levent Sevgi Agenda: All Welcome! You do not have to be a member of the IEEE to attend. Time: 5:00 PM-6:00 PM, Monday, March 03, 2025. A complimentary buffet dinner will be available until 4:45 PM. Place: New Jersey Institute of Technology (NJIT), Room 202, ECE Center, Newark, NJ. Directions are available at (http://www.njit.edu/). Contact Persons: Dr. Ajay Poddar (akpoddar@ieee.org), Dr. Durga Misra (dmisra@njit.edu), Dr. Anisha Apte (anisha_apte@ieee.org), Dr. Edip Niver (edip.niver@njit.edu) Room: 202, Bldg: ECE Center, New Jersey Institute of Technology (NJIT), 154 Summit Street, Newark, NJ 07102, Newark, New Jersey, United States

Elizabeth Alves STEM Affiliate Leader at Learning Disabilities Association of America Elizabeth Alves will share her preparation for her mission and a deep dive of her endeavors, projects, programs, accomplishments and inspired goals as a passionate Humanitarian with over 20 years of experience in education, specializing in integrating STEM concepts for students of all abilities. Her expertise spans general and special education, with a focus on supporting neuro-diverse learners and the under resourced. Note: PDH / CEU is not being offered for the Spring 2025 sessions. Speaker(s): Elizabeth Alves Virtual: https://events.vtools.ieee.org/m/456329

Abstract: First-order methods (FOMs) are optimization algorithms that can be described and analyzed using the values and (sub)gradients of the functions to be minimized. FOMs are the main workhorses for modern large-scale optimization and machine learning due to their low iteration costs, minimal memory requirements, and dimension-independent convergence guarantees. As the data revolution continues to unfold, the pressing demand for faster FOMs has become the key problem in today’s big data era. To that goal, we present Branch-and-Bound Performance Estimation Programming (BnB-PEP), the first unified methodology for constructing optimal (provably fastest) FOMs for convex and nonconvex optimization. BnB-PEP poses the problem of finding the optimal FOM as a nonconvex but practically tractable quadratically constrained quadratic optimization problem and solves it to certifiable global optimality using a custom branch-and-bound algorithm. Our open-source custom branch-and-bound algorithm, through exploiting specific problem structures, outperforms the latest off-the-shelf software by orders of magnitude, accelerating the solution time to discover the optimal FOMs from hours to seconds and weeks to minutes. We apply BnB-PEP to several practically relevant convex and nonconvex setups and obtain FOMs with bounds that improve upon prior state-of-the-art results. Furthermore, we use the BnB-PEP methodology to find proofs with potential function structures, thereby systematically generating analytical convergence proofs. Recently, BnB-PEP has helped pave the way for some fundamental results in optimization: (i) novel momentum-free accelerated gradient descent methods that broke with decades of conventional wisdom (ii) the optimal FOM for constrained convex optimization that outperforms the celebrated FISTA algorithm by Beck and Teboulle, and (iii) the first non-asymptotic convergence theory for the widely used nonlinear conjugate gradient methods. (joint work with Bart Van Parys and Ernest K. Ryu) Paper link: https://arxiv.org/pdf/2203.07305 Speaker(s): Shuvomoy Das Gupta Agenda: - Talk by Shuvomoy Das Gupta at 4:00 pm - Dinner box after the talk at 5:00 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

Dear All, You are cordially invited to attend the March ExCom meeting at NJIT or on Zoom. For those attending in person, the parking will be at the deck at 154 Summit St, Newark, NJ 07102. Looking forward to seeing you all Best Regards Emad Room: 202 ECEC, 141 Warren St, The Lewis and Julia P. Kiernan Conference Room, Newark, New Jersey, United States, 07102, Virtual: https://events.vtools.ieee.org/m/469411

Prof Ali Hessami (Director of R&D and Innovation at Vega Systems) will present “Climate Change, from Fundamentals to Smart Solutions” at 6pm (UTC) / 1pm EST on 06 March 2025 (re-scheduled from 20 Feb). Click (https://www.timeanddate.com/worldclock/fixedtime.html?msg=SSIT+Lecture%3A+Climate+Change%2C+from+Fundamentals+to+Smart+Solutions&iso=20250306T18&p1=78&ah=1). IEEE UK and Ireland SSIT Chapter and SSIT IST-Africa SIGHT are cooperating with a number of IEEE OUs including North Jersey Section SSIT Chapter, Atlanta Section SSIT Chapter, Southeastern Michigan Section Computer Chapter, NJ Coast IM/Computer Joint Chapter, Northwest Florida Computer /Communications Joint Chapter, Lehigh Valley Computer Chapter and Northern Virginia/Baltimore/Washington SSIT Chapter to organise this SSIT Lecture as a joint Webinar on 06 March. Registration IEEE and SSIT Members as well as non-IEEE Members are invited to (https://events.vtools.ieee.org/m/462162) and participate. IEEE Members should include their IEEE Membership Number when registering. Access to online Meeting Registered participants will be provided with the link prior to the event. Guest Lecture Focus Prof. Ali Hessami will present the second foundational lecture focused on climate science building on the initial lecture in October 2024 that covered the natural Earth Cycle, Green House effect, Green House Gases, the post-industrial trends in temperature rise etc. This talk is intended to conclude on the scientific fundamentals of climate science and introduce a scientific climate simulator (En-ROADS). The online simulator enables informed users and stakeholders to explore the impact of CO2 and other GHGs emissions on the future global temperature rise through various policy options from variations in the composition of energy supply to transportation electrification, buildings and industry, impact of growth, carbon removal and other sources of greenhouse emissions. Link to Climate Change, the Fundamentals 30 October 2024 https://ieeetv.ieee.org/channels/ssit/climate-change-the-fundamentals Speaker(s): Prof. Ali Hessami, Agenda: 18:00 (UTC) / 13:00 (EST) Welcome and Introduction to Guest Speaker 18:05 Lecture 18:45 Questions and Discussions Virtual: https://events.vtools.ieee.org/m/462162

Special Presentation by Dr. Deepak Kataria (Ericsson, USA) Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Date/Time: Thursday, 6 March 2025 @ 6 PM EST Topic: Leveraging Intent-Driven rApps for Intelligent RAN Automation Abstract: The evolution of service management and orchestration (SMO) in O-RAN has unlocked new possibilities for automating RAN operations. Intent-driven rApps are at the forefront of this transformation, enabling service providers to seamlessly evolve, deploy, and optimize networks with unprecedented efficiency. By abstracting complexity and leveraging intent-based automation, these rApps empower service providers to align network operations with dynamic business demands, fostering agility and innovation. This keynote will explore the transformative potential of rApps in achieving autonomous RAN management, emphasizing SDKs and solution frameworks that drive developer success. Additionally, it will highlight strategies for resolving conflicts and ensuring seamless collaboration across independent automation processes, paving the way for the next era of intelligent network management. Speaker: [] Deepak Kataria has over 25 years’ experience in telco, data networking, and cloud computing domains with the unique distinction of working in technical leadership roles at AT&T Bell Labs, Lucent Technologies, Fujitsu, Agere Systems, and LSI. He co-founded IPJunction Inc in 2009 consulting telco clients on new solution opportunities, target markets, product management consulting and ecosystem partnerships. Currently, he serves as the Principal Solution Consultant for Ericsson working on AT&T’s cloud native network transformation, Cloud RAN and SMO projects. He served as Chair of IEEE Princeton Central Jersey Section from 2020-2022, General Chair of IEEE Sarnoff Symposium between 2015-2019 and co-leads the IEEE Future Network Initiative’s Working Group on AI/ML. He holds B.S. in Electronics and Communications Engineering, and pursued M.S. and Ph.D. degrees in Electrical Engineering from Rutgers University, New Jersey. He completed Harvard’s Emerging Leaders professional program on virtual leadership covering strategy, customer focus, corporate governance, and innovation. Co-sponsored by: Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Virtual: https://events.vtools.ieee.org/m/466498

A comprehensive update packed with new functions is on the way: Enhanced modal testing with SDOF and video export Upgrades to OXYGEN-NET and power analysis New orbit plot and polar plot capabilities Improved recorder functionality Additional SCPI commands Enhanced reporting features And much more! Co-sponsored by: CH01265 - North Jersey Section Chapter,EMC27/PSE43 Speaker(s): Christophe , Gabriella Agenda: A comprehensive update packed with new functions is on the way: Enhanced modal testing with SDOF and video export Upgrades to OXYGEN-NET and power analysis New orbit plot and polar plot capabilities Improved recorder functionality Additional SCPI commands Enhanced reporting features And much more! Virtual: https://events.vtools.ieee.org/m/470877

Abstract: This talk presents two geometric methods—based on normal vectors and differential geometry—for efficient stability analysis of future power systems characterized by high complexity and uncertainty. The first part of the talk focuses on using normal vectors to analytically describe the stability margin to Hopf and saddle-node bifurcations, addressing oscillatory instability and voltage collapse, respectively. We apply this theory to assess the parameter sensitivities of grid-forming and grid-following inverters and identify the most effective control parameters for enhancing stability margins. In particular, the impacts of line dynamics are investigated. It is observed that line dynamics introduce a uniform reduction in the stability margin to Hopf bifurcation across all parameters. However, the reduction is generally small. The second part introduces a novel differential geometry-based method to approximate the singular solution space boundary (SSB) of power systems under high renewable generation variability. By extracting geometric information from the power flow manifold, we approximate geodesics originating from an operating point in any interested directions corresponding to generation and load fluctuations. Using these geodesic curves, we predict voltage collapse points by solving a few univariate quadratic equations. Compared to conventional methods that rely on optimization or computationally expensive numerical continuation, this approach is efficient and well-suited for handling the high-dimensional variability introduced by large-scale renewable integration. Bio: Sijia Geng is an Assistant Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University. She is a Core Faculty with the Ralph O’Connor Sustainable Energy Institute (ROSEI) and co-PI of the NSF EPICS Global Center. Before joining JHU, she was a Postdoctoral Associate at the Laboratory for Information & Decision Systems (LIDS) at MIT. Dr. Geng received her Ph.D. in Electrical and Computer Engineering from the University of Michigan, Ann Arbor, where she also obtained two M.S. degrees in Mathematics and in ECE. Her research interests include dynamics, control and stability of inverter-based smart grids and optimization of electrified transportation systems. She is the recipient of a Best Paper Award at the MIT/Harvard Applied Energy Symposium in 2022 and was named a Barbour Scholar and Rising Star in EECS in 2021. Speaker(s): Sijia Geng Agenda: - Talk by Sijia Geng 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