Events

We all have ideas about careers in big corporations, careers in academia or being an entreprenur, but how about a career in the world of startups? Do you know what signs to look for in a healthy startup? When to join and when to exit? What skill sets are needed? Is it a rewarding career after all?In this panel, you will learn from two extremely successful engineers who have developed their careers in the startup world, in very different fields. First, we will have Erik Selin. Erik is a relatively recent and very successful UOttawa alumnus, who is currently the data lead at LayerZero Labs. He was previously involved with Shopify, Twitch and Doximity in their early phases. Next, we have Dr. Fatemeh Soltani, who is curruntly the technical lead at RANOVUS Inc. Dr. Fatemeh has 10+ years experience at various companies including Ciena and Lumentum, as well as Alphawave Semi, Milkshake and <a href="http://Credo.This" target="_blank" title="Credo.This">Credo.This panel discussion is the perfect way to end this term with fresh ideas and a widened vision! Join us for the panel, and stay for the lunch and networking following the <a href="http://event.Agenda:" target="_blank" title="event.Agenda:">event.Agenda: - Short presentations- Panel discussion- Lunch and networkingRoom: STM117, Bldg: STM Building, University of Ottawa, 150 Louis-Pasteur Private, Ottawa, Ontario, Canada, K1N 9A7

The IEEE Women in Engineering (WIE) Affinity Group – Hamilton Section meets on the last Thursday of each month. We are pleased to invite you to our next monthly meeting, to be held on April 30, 2026. We warmly look forward to your participation and hope you can join <a href="http://us.Agenda:" target="_blank" title="us.Agenda:">us.Agenda: - Opening and welcome- Update on the drawing competition- Update on collaboration with the student branch- Discussion on WIE Day event and activities- Volunteer recruitment: sources and strategies- Update on the drawing competition- Planning upcoming activities- Closing RemarksVirtual: https://events.vtools.ieee.org/m/551067

Abstract:This lecture summarizes “Survival Skills for Scientists”, a graduate course designed to offer basic advice and mentorship. The central theme of this presentation is that succeeding in science requires skills (‘soft professional skills’) beyond those needed for <a href="http://science.The" target="_blank" title="science.The">science.The lecture aims at giving basic guidance to young scientists, focusing on:- The job market for science and engineering graduates- Funding your research- Publish or perish- Presenting your work- The laws of ‘scientific survival’- Ethics in science- Alternative careersCo-sponsored by: ETS Optica Student ChapterSpeaker(s): Federico RoseiAgenda: 11:15 am - 11:30 am: Welcome & introduction11:30 am-12:30 pm: Tech Talk (on-site)12:30 pm-1:30 pm: Networking lunchRoom: A-1300, Bldg: Pavillon A, Ecole de Technologie Supérieure , 1100, rue Notre-Dame Ouest, Montreal, Quebec, Canada, H3C 1K3

Title: Generative AI and Deep Learning for Resource Allocation in 6G Wireless NetworksAbstract:This talk provides an in-depth exploration of resource management in 6G wireless networks, focusing on the vision, key performance indicators (KPIs), key enabling techniques (KETs), and the diverse array of services characteristic of these advanced networks. The distinct challenges inherent in 6G resource management call for a pivotal shift toward artificial intelligence (AI) and machine learning (ML)–driven solutions, requiring a departure from traditional optimization-centric <a href="http://approaches.The" target="_blank" title="approaches.The">approaches.The talk sheds light on generative AI and unsupervised ML strategies tailored to effectively address convex and non-convex resource management optimization problems. A key focus is placed on deep unsupervised learning techniques for network resource allocation under nonlinear and non-convex constraints. Deep implicit layers and differentiable projection methods are explored as mechanisms to ensure zero constraint violations in applications such as beamforming, phase-shift optimization, and power <a href="http://allocation.Furthermore" target="_blank" title="allocation.Furthermore">allocation.Furthermore, the potential of generative AI models, including large language models (LLMs), to enable proactive network resource allocation is examined, highlighting their role in optimizing performance and reducing reliance on traditional heuristics. The session concludes by identifying key research gaps and future directions, paving the way for next-generation AI-driven wireless <a href="http://networks.Co-sponsored" target="_blank" title="networks.Co-sponsored">networks.Co-sponsored by: Hong-chuan Yang***CANCELED***Room: 660, Bldg: Engineering/Computer Science Building (ECS), 3800 Finnerty Road, Victoria, British Columbia, Canada, V8P 5C2

Abstract: The next generation of wireless networks will no longer be confined to moving bits — they will sense, communicate, and learn simultaneously. This convergence is anticipated to enable distributed intelligence across devices, unlocking new capabilities for real-time perception and decision-making in dynamic environments. In this talk, two complementary advances in federated signal processing will be presented. First, an over-the-air federated edge learning (OTA-FEEL) framework with integrated radar sensing will be discussed. By leveraging echoes from the environment, rather than treating them solely as interference, robust model aggregation will be maintained while ensuring high-quality sensing and communication performance. A joint scheduling and beamforming design will be presented, supported by low-complexity optimization techniques, to preserve aggregation accuracy under realistic wireless conditions. Second, FedTrack, a novel federated learning–inspired algorithm for distributed target tracking, will be presented. By treating local log-likelihood functions as loss functions in a distributed optimization framework, FedTrack enables devices to collaboratively estimate a moving target’s position and velocity. This communication-efficient method closely approximates centralized maximum likelihood estimation, achieving accuracy near the Cramér–Rao bound while reducing reliance on a central coordinator. Together, these developments illustrate how federated intelligence over the air can transform 6G networks into systems that not only communicate but also sense and learn collaboratively. Implications for autonomous systems, smart cities, and beyond will be discussed, with emphasis on the central role of signal processing innovations in realizing this <a href="http://vision.Room:" target="_blank" title="vision.Room:">vision.Room: MCLD 3038, Bldg: Hector J. MacLeod Building - MCLD, 2356 Main Mall, Vancouver, BC V6T 1Z4, Vancouver, British Columbia, Canada, Virtual: https://events.vtools.ieee.org/m/552228

CREATE TRAVERSAL, SITE-CAV and Lunch&Learn series of IEEE Young Professionals Ottawa is taking it to the sky! Join us as Prof. Cicek Cavdar from KTH Sweden, a leading expert in the field, presents state-of-the art research and the upcoming challenges in satellite communications and 6G.Come for the learning and stay for the community! We will serve lunch, Turkish coffee and other treats following the <a href="http://presentation.6G" target="_blank" title="presentation.6G">presentation.6G for Connected Sky: From LEO Mega-Constellations to Airspace CommunicationsAbstract: Future 6G systems will extend across terrestrial, aerial, and non-terrestrial platforms to support seamless, resilient, and intelligent connectivity for users in the sky, on the ground, and in remote areas. In this talk, I will present our recent work toward this vision of 6G for Connected Sky, covering three main research directions: (i) design and resource allocation in LEO mega-constellations, including handover management, Open RAN architectures, interference, and hybrid terrestrial-satellite networking; (ii) satellite-assisted IoT and edge intelligence, where learning-based methods support data collection and task offloading in highly dynamic environments; and (iii)airspace communications, including UAV connectivity, reliability, sensing, and spectrum/regulatory challenges in integrated 3D networks. Together, these works highlight how future connectivity must be designed jointly across communication architecture, mobility, compute, and intelligence to enable reliable and scalable 6G services for the connected <a href="http://sky.Bio:" target="_blank" title="sky.Bio:">sky.Bio: Cicek Cavdar is a Full Professor at KTH Royal Institute of Technology, Sweden, where she serves as Vice Head of the Department of Communication Systems and Founding Director of SMART-6GSAT, Sweden’s first national 6G satellite communications center. She leads the Intelligent Network Systems research group and works on AI-native and cloud-native network design and orchestration, with a focus on cell-free massive MIMO, integrated sensing and communications, drone communications, and the convergence of terrestrial and non-terrestrial networks. Her research addresses the trade-off between resiliency and energy efficiency through an end-to-end perspective spanning cloud, transport, and radio access networks. She has led major EU academia–industry initiatives, including 6G-SKY and RAI-6Green, and previously coordinated AI4Green, which received the 2024 EUREKA Innovation Award and Celtic Excellence Award. Her team received the Scientific Excellence Best Paper Award at ASMS/SPSC 2025 for work on disaggregated RAN in space and handover management in LEO mega-constellations. Professor Cavdar has authored more than 160 publications, holds several patents, and serves on the editorial boards of IEEE Transactions on Wireless Communications and IEEE Transactions on Green Communications and Networking. She is also an active organizer, editor, and keynote speaker in the areas of 6G, AI-native networks, green communications, and non-terrestrial <a href="http://networks.Co-sponsored" target="_blank" title="networks.Co-sponsored">networks.Co-sponsored by: Smart Connected Vehicles Innovation Centre (SCVIC) and the Next Generation Communications and Computing Networks Lab (NEXTCON)Speaker(s): Cicek, Agenda: - Introductions- Talk by Prof. Cicek Cavdar- Lunch and networkingBldg: Hub 350, 350 Legget Dr, Smart Connected Vehicles Innovation Centre, Ottawa, Ontario, Canada, K2K 3N1

Title: Generative AI and Deep Learning for Resource Allocation in 6G Wireless NetworksAbstract:This talk provides an in-depth exploration of resource management in 6G wireless networks, focusing on the vision, key performance indicators (KPIs), key enabling techniques (KETs), and the diverse array of services characteristic of these advanced networks. The distinct challenges inherent in 6G resource management call for a pivotal shift toward artificial intelligence (AI) and machine learning (ML)–driven solutions, requiring a departure from traditional optimization-centric <a href="http://approaches.The" target="_blank" title="approaches.The">approaches.The talk sheds light on generative AI and unsupervised ML strategies tailored to effectively address convex and non-convex resource management optimization problems. A key focus is placed on deep unsupervised learning techniques for network resource allocation under nonlinear and non-convex constraints. Deep implicit layers and differentiable projection methods are explored as mechanisms to ensure zero constraint violations in applications such as beamforming, phase-shift optimization, and power <a href="http://allocation.Furthermore" target="_blank" title="allocation.Furthermore">allocation.Furthermore, the potential of generative AI models, including large language models (LLMs), to enable proactive network resource allocation is examined, highlighting their role in optimizing performance and reducing reliance on traditional heuristics. The session concludes by identifying key research gaps and future directions, paving the way for next-generation AI-driven wireless <a href="http://networks.Co-sponsored" target="_blank" title="networks.Co-sponsored">networks.Co-sponsored by: Hong-chuan YangRoom: 660, Bldg: Engineering/Computer Science Building (ECS), 3800 Finnerty Road, Victoria, British Columbia, Canada, V8P 5C2

IEEE North Saskatchewan Section Meeting - May, 202657 Campus Dr, Saskatoon, Saskatchewan, Canada, S7N 5A9, Virtual: https://events.vtools.ieee.org/m/544435

Future of communication and sensing network is being transformed with the advancement in next generations of wireless with Beyond-5G, beyond-WiFi-8, ICAS, NTN, VR/XR/Metaverse, Digital-Twin and other emerging applications. Higher quality of experiences for connected future with ubiquitous lowest latency and superhigh data rate connectivity services will require innovative wireless technologies and communication hardware combined with AI/ML. Mobile platform integrated RF systems with antenna front ends are common factor for most of the wireless applications. Emerging usage scenarios will need intelligent mobile platforms with ultra-small form-factor, requiring co-design and heterogeneous integration of dis-similar semiconductor device, circuit and antenna technologies, in order to satisfy the desired application-specific performance criteria for the evolving use <a href="http://cases.This" target="_blank" title="cases.This">cases.This presentation will present the emerging technology trends and will focus on the antenna-integrated RF to mm-wave/THz array integrated frontend opportunities and challenges demanding new technology, design, development and integration. Example architectures to enablemultifunction microsystem platform will be <a href="http://discussed.Speaker(s):" target="_blank" title="discussed.Speaker(s):">discussed.Speaker(s): Dr. Debabani Choudhury, Agenda: - 6:30 - 7:00 PM Networking- 7:00 - 8:00 PM Technical TalkBldg: Cal Lutheran Center for Entrepreneurship (Hub101), 31416 Agoura Rd, Westlake Village, California, United States, 91361, Virtual: https://events.vtools.ieee.org/m/494694

As the semester comes to a close, we will be holding our Annual General Meeting (AGM) on May 6th to elect the 2026–2027 Executive Team of the IEEE BCIT Student <a href="http://Branch.Room:" target="_blank" title="Branch.Room:">Branch.Room: TBD, Bldg: TBD, Burnaby, British Columbia, Canada

Abstract: The unprecedented scale, heterogeneity, and performance requirements of 6G networks fundamentally challenge traditional optimization-centric approaches to resource management, motivating a paradigm shift toward artificial intelligence (AI)–driven methodologies. This lecture examines how deep unsupervised learning and generative AI techniques can be leveraged to solve both convex and non-convex network resource allocation problems under complex, nonlinear constraints. Particular emphasis is placed on deep unsupervised learning frameworks, deep implicit layers, and differentiable projection methods that enforce strict constraint satisfaction in applications such as beamforming, phase-shift optimization, and power allocation. The emerging role of generative AI models, including large language models (LLMs), is further discussed in enabling adaptive and environment-aware resource allocation strategies that reduce dependence on frequent model redesign and retraining. The lecture concludes by identifying key research challenges and outlining a roadmap toward scalable, robust, and AI-native 6G wireless <a href="http://networks.Speaker" target="_blank" title="networks.Speaker">networks.Speaker Bio: Hina Tabassum (Senior Member, IEEE) received the Ph.D. degree from the King Abdullah University of Science and Technology. She is currently an Associate Professor with the Lassonde School of Engineering, York University, Canada, where she joined as an Assistant Professor in 2018. She is also appointed as a Visiting Faculty with the University of Toronto in 2024, and the York Research Chair of 5G/6G-enabled mobility and sensing applications in 2023, for five years. She is listed in Stanford’s list of the World’s Top Two-Percent Researchers from 2021 to 2025. She has been selected as the IEEE ComSoc Distinguished Lecturer for the term 2025–2026. She has co-authored over 120 refereed articles in well-reputed IEEE journals, magazines, and conferences. Her current research interests include multiband 6G wireless communications and sensing networks, connected and autonomous systems, and AI-enabled network mobility and resource management solutions. She has earned numerous distinctions, including the N2Women Star in Networking and Communications (2025), Early Career Lassonde Innovation Award (2023), N2Women Rising Star in Networking and Communications (2022), multiple Exemplary Editor awards from IEEE journals, and appointment to the NSERC Discovery Grant Evaluation Group (2025–2028). She served as an Associate Editor for IEEE Communications Letters from 2019 to 2023, IEEE Open Journal of the Communications Society from 2019 to 2023, and IEEE Transactions on Green Communications and Networking from 2020 to 2023. She is also currently serving as an Area Editor for IEEE Open Journal of the Communications Society and an Associate Editor for IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, IEEE Transactions on Wireless Communications, and IEEE Communications Surveys and <a href="http://Tutorials.Bldg:" target="_blank" title="Tutorials.Bldg:">Tutorials.Bldg: ICT 424C, University of Calgary, Calgary, Alberta, Canada

Seminar Abstract:Switch-mode power converters are ubiquitous in renewable energy applications, electric vehicles, and battery chargers. Closed-loop controllers are essential to guarantee the consistent behaviour of power converters under all operating conditions, and they become a decisive component when defining the converters’ dynamic performance. Digital controllers based on linearized small-signal models are the preferred choice by the power electronics industry as their low implementation requirements make them suitable for implementation in low-cost microcontrollers. However, given the small-signal nature of the controller design, large transients usually represent an interesting <a href="http://challenge.This" target="_blank" title="challenge.This">challenge.This seminar describes an alternative large-signal modelling and control framework for power electronics, based on state-space average analysis. Large-signal average models will be derived for fundamental topologies, and then extended to more complex power converters and applications. Various ways to leverage these state-plane-average models will be discussed, including controllers that can significantly improve the converter’s large-transient dynamic performance while maintaining simple implementation <a href="http://requirements.Biography:Dr">requirements.[]Biography:Dr. Ignacio Galiano Zurbriggen is an Assistant Professor with the School of Sustainable Energy Engineering at Simon Fraser University. His research interests include the study of power electronic converters as technology-enabling building blocks for applications in sustainable Energy and Transportation. His work includes numerous industry-academia collaboration projects and industrial R&D experience with companies including Tesla, Alpha-Enersys, and <a href="http://Computrol.He" target="_blank" title="Computrol.He">Computrol.He completed his MSc and PhD degrees in Electrical and Computer Engineering at the University of British Columbia in 2013 and 2020 respectively, and his bachelor’s degree in Electronics Engineering at the National University of Cordoba, Argentina in 2010.Dr. Galiano Zurbriggen currently serves as an Associate Editor for IEEE-OJPEL, he has delivered numerous IEEE technical presentations and seminars, and he contributes as a reviewer for several IEEE journals and <a href="http://conferences.Room:" target="_blank" title="conferences.Room:">conferences.Room: SF B560, Bldg: Sanford Fleming Building, University of Toronto, 10 King’s College Road, Toronto, Ontario, Canada, M5S 3G4