Event Details - Date: 8 April 2026 - Time: 11:00 AM – 11:59 AM - Duration: 1 hour - Mode: Hybrid (In-person + Online) Venue Details - Physical Location: IISRI, NS Building Deakin University, Waurn Ponds Campus - Online Platform: Deakin University IEEE Student Branch is inviting you to a scheduled Zoom meeting. Join Zoom Meeting https://deakin.zoom.us/j/6813570312?pwd=RCtTSWVYNkg0V0ZmbDlaSUpJS0pTQT09&omn=83101851691 Meeting ID: 681 357 0312 Password: 44944359 Event Description The Annual General Meeting (AGM) 2026 of the IEEE Student Branch at Deakin University is an official gathering of all members to review the branch’s activities, achievements, and progress over the past year. The meeting will also provide an opportunity to discuss future plans, gather member feedback, and conduct the election or confirmation of the executive committee for the upcoming term. All IEEE members and interested students are encouraged to attend and contribute to shaping the future direction of the student branch. Target Audience - IEEE Student Members - Deakin University Students - IEEE Volunteers and Faculty Members Agenda: - Opening remarks and welcome - Confirmation of quorum - Review of previous AGM minutes - Annual report presentation (2025–2026) - Discussion on achievements and challenges - Election/confirmation of executive committee - Future plans and upcoming events - Open discussion / Q&A - Closing remarks Bldg: NS IISRI, 75 Pigdons Road, Waurn Ponds, Geelong, VIC 3216, Geelong, Victoria, Australia, 3216, Virtual: https://events.vtools.ieee.org/m/550623
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The Bridgestone World Solar Challenge highlights how modern vehicles are increasingly defined by electrical and electronic systems rather than purely mechanical design. With Matt’s experience on the Deakin University’s solar car projects as context, this talk explores the key challenges that rely on electrical engineering knowledge. These include efficient solar energy harvesting, battery management and protection, motor control strategies, and real-time energy optimisation over long distances. The presentation frames these as interconnected system-level problems: how to generate, store, convert, and use energy as efficiently as possible under real-world constraints. The aim is to illustrate how electrical engineering underpins performance, reliability, and sustainability in modern automotive applications, and why these challenges are central to the future of mobility. Co-sponsored by: Deakin University IEEE Student Branch Speaker(s): Matt Jennings Bldg: School of Engineering, KA3.411, 75 Pigdons Rd,, Geelong, Victoria, Australia, 3216, Virtual: https://events.vtools.ieee.org/m/557228
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Abstract: This presentation revisits how we introduce the fundamentals of electromagnetic radiation to students of RF physics and engineering. At present the dominant approach focuses on Maxwell’s equations. The problem is that the complexity of Maxwell’s equations makes an understanding of electromagnetic radiation inaccessible to learners without university-level mathematics. As a result, high-school students of physics and others, such as amateur radio operators, are typically given simplistic analogies, such as comparing radio waves with light, and assertions that light and radio signals are waves, without further justification. Even for those studying university-level physics or engineering who do have the mathematics to solve Maxwell’s equations, Maxwell’s equations are arguably at the wrong level of detail to provide an intuitive understanding of how electromagnetic radiation is formed. This talk presents a different possibility: the late 19th-century approach of Joseph Larmor. Larmor’s analysis examines just a single charged particle and how accelerating the charged particle generates a transverse disturbance in the electric field. This framework simplifies the mathematics, making it possible to gain a quantitative understanding of electromagnetic radiation with only high-school algebra and trigonometry. The aim is not to replace Maxwell’s equations, but to develop a pedagogy accessible to anyone with high-school mathematics studying RF physics and engineering. By examining electromagnetic radiation from this perspective, the presentation highlights how simplifying frameworks can deepen understanding. It also raises a broader challenge for both engineering and education: how do we balance rigor, intuition, and accessibility when teaching the physics at the heart of RF engineering? By examining electromagnetic radiation from this perspective, the presentation highlights how simplifying frameworks can deepen understanding. It also raises a broader challenge for both engineering and education: how do we balance rigor, intuition, and accessibility when teaching the physics at the heart of RF engineering? Speaker(s): Dr George Galanis, Virtual: https://events.vtools.ieee.org/m/552008 |
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Abstract: Backpropagation has powered the modern era of computational intelligence, enabling breakthroughs in perception, language, control, and autonomous systems. Yet as intelligent systems move into dynamic, real-world environments, new demands emerge: continual adaptation, robustness under uncertainty, energy efficiency, and scalable autonomy. These challenges invite a deeper question — are our learning algorithms fundamentally aligned with how intelligence itself operates? This lecture explores predictive coding as a compelling, brain-inspired alternative for credit assignment in deep systems. Rather than relying on staged forward and backward passes with global error transport, predictive coding formulates learning as the continuous minimization of hierarchical prediction errors through local, parallel, and bidirectional interactions. Recent theoretical advances demonstrate that such dynamics can approximate gradient-based optimization, offering a principled bridge between neuroscience and modern machine learning. This perspective reframes learning as an energy-minimizing dynamical process, opening new directions in distributed credit assignment, continual learning, robust inference, and neuromorphic implementation. By revisiting the principles of biological intelligence, this lecture argues that the next generation of computational intelligence systems may emerge not from scaling existing algorithms, but from rethinking the foundations of learning itself. Co-sponsored by: IEEE VIC CIS Chapter; IEEE VIC Section Speaker(s): Narayan Srinivasa, Virtual: https://events.vtools.ieee.org/m/554620 |
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The IEEE Student Branch at The University of Melbourne is organising an academic seminar titled “From Intelligent Systems to Intelligent Learning: Bridging AI Research & Engineering Education.” This event will feature Dr. Lili Chen, Associate Lecturer (Education Specialist) at The University of Melbourne, who will present her research and teaching work at the intersection of artificial intelligence, wireless communication systems, and engineering education. The seminar will cover two main themes. The first part will introduce AI-driven resource allocation in wireless communication networks, with a focus on graph neural network (GNN)-based approaches for modelling interference relationships and enabling efficient, scalable decision-making. The second part will explore the use of GenAI-assisted, criterion-referenced grading frameworks in engineering education to improve feedback quality, consistency, and efficiency in large-cohort teaching contexts. This event is intended for students, researchers, and early career engineers who are interested in emerging AI applications in both technical research and engineering learning environments. The seminar aims to promote academic exchange, technical awareness, and interdisciplinary discussion within the IEEE student community. Refreshments will be provided after the seminar. Speaker(s): Dr. Lili Chen Agenda: 2:00 PM – 2:05 PM: Welcome and introduction 2:05 PM – 2:45 PM: Seminar presentation by Dr. Lili Chen 2:45 PM – 2:55 PM: Q&A session 2:55 PM – 3:00 PM: Closing remarks 3:00 PM onwards: Refreshments and informal networking Room: Newton Room, Level 2, Bldg: EEE Building, University of Melbourne, Parkville Campus, Melbourne, Victoria, Australia, 3010 |
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The IEEE IAS Student Branch Chapter at RMIT University is pleased to host the IEEE IAS Mini Industry Networking Event on the theme “Challenges and Opportunities for Future Low-Carbon Power Grids.” This event brings together industry professionals, academics, students, and early-career engineers for technical discussion and networking. The program will include expert talks, academic and industry perspectives, a panel discussion, a Q&A session, and a networking session with refreshments. The event is supported through the IEEE Industry Applications Society MINE initiative and aims to strengthen engagement between industry and academia in the area of future low-carbon power systems. Co-sponsored by: IEEE Industry Applications Society, SmartGRID Technologies & Power Quality Solutions Pty Ltd Speaker(s): Lasantha Meegahapola, Nuwantha Fernando, Shuo Yan, Roozbeh Kabiri, Andrea Fakos, Chalitha Liyanage, Manoj Angus Agenda: 3:00 PM – Registration and welcome 3:10 PM – Opening remarks 3:20 PM – Technical talks and industry perspectives 4:10 PM – Panel discussion 4:35 PM – Q&A session 4:50 PM – Closing speach 5:00 PM – Networking and refreshments Room: 012.05.002, Bldg: 12, 124 La Trobe Street, Melbourne, Victoria, Australia, 3001
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Data-Driven Cyber-Physical Systems: Edge AI in Modern Engineering - Background Engineering industries are undergoing rapid transformation driven by advances in digital technologies, automation, and data-driven systems. Concepts such as Edge AI and distributed intelligence are increasingly shaping how engineers design, manufacture, and maintain complex infrastructure and production systems. These technologies allow organizations to process data closer to physical assets, optimize operational performance, and improve decision‑making through real-time analytics and low-latency computation. As engineering organizations adopt these tools, the expectations placed on graduate engineers are evolving rapidly. While universities provide strong theoretical foundations, many employers report that graduate engineers often lack several practical competencies required for modern engineering workplaces. These include systems thinking, familiarity with embedded and edge computing platforms, data literacy, and the ability to work effectively in multidisciplinary teams. To help bridge the gap between academic training and industry expectations, IEEE student branch of Swinburne proposes organizing a tech‑talk style event focused on Edge AI and the professional skills required for the future engineering workforce. 2. Event Overview This event will feature a keynote presentation by Prof. Prem Prakash Jayaraman, Director of the Factory of the Future at Swinburne University of Technology and a leading researcher in distributed systems, IoT, and Edge AI. The event will provide post-graduate students, graduate engineers and final‑year engineering students with insight into Edge AI technologies, industry trends, and the practical skills required to remain competitive in the evolving engineering industry. In addition to the keynote presentation, attendees will participate in a guided visit to the Swinburne Factory of the Future. This visit will showcase ongoing research and industry collaboration projects involving Edge AI, smart sensing systems, robotics, and real-time data processing at the edge. By combining a live demonstration of advanced engineering technologies with an expert academic perspective, the event aims to provide both practical exposure and career guidance for early‑career engineers and researchers. 3. Keynote Content and Technical Focus The keynote presentation will provide a deep technical perspective on Edge AI and its role in modern engineering systems. The speaker will introduce the concept of Edge AI, highlighting how machine learning models are deployed on embedded systems, sensors, and edge devices to enable real-time decision-making without reliance on cloud infrastructure. The presentation will explore system architecture for Edge AI, including edge-cloud collaboration, distributed intelligence, and resource-constrained model deployment. Practical examples will demonstrate how Edge AI improves efficiency, reduces latency, enhances data privacy, and enables autonomous operation in applications such as smart manufacturing, robotics, and industrial automation. The talk will also discuss challenges associated with Edge AI, including computational constraints, model optimization, energy efficiency, and system integration. Emphasis will be placed on how engineers can design robust and scalable edge systems. The session will connect these technologies to real-world industry applications and outline how they are influencing the skills and competencies required of modern engineers. Attendees will gain insight into how Edge AI is being adopted in practice and how they can prepare to work effectively in increasingly distributed and intelligent engineering environments. 4. Objectives The key objectives of the event are: • Introduce students to Edge AI technologies transforming modern engineering industries. • Demonstrate real-world applications through a guided tour of the Factory of the Future. • Highlight the practical skills and competencies employers expect from graduate engineers. • Provide career insights and professional advice for students and early‑career engineers. • Encourage engagement between students, researchers, and industry professionals. Registrations: https://www.eventbrite.com.au/e/data-driven-cyber-physical-systems-edge-ai-in-modern-engineering-tickets-1986395765206?aff=oddtdtcreator Co-sponsored by: IEEE VIC Section Speaker(s): Prem, Agenda: Event Program Date: Friday, 8th May 2026 Start Time: 3:30 PM 3:30 PM – 4:00 PM | Guided Visit – Swinburne Factory of the Future Attendees will participate in a 15–30 minute guided tour of the Swinburne Factory of the Future. The tour will demonstrate existing projects involving smart manufacturing systems, digital engineering platforms, robotics, and automation. The visit will provide participants with direct exposure to advanced manufacturing technologies currently being developed and applied in industry collaboration projects. 4:00 PM – 4:05 PM | Transition to EN102 Lecture Hall Attendees will be guided from the Factory of the Future to the EN102 Lecture Hall for the keynote presentation. 4:05 PM – 4:10 PM | Opening Remarks The event organizers will provide a short introduction outlining the purpose of the event and introducing the keynote speaker 4:10 PM – 4:40 PM | Keynote Presentation – Prof. Prem Prakash Jayaraman The keynote will focus on Edge AI systems, distributed intelligence, and real-time decision-making in engineering applications. The talk will also highlight industry expectations and required technical skills. 4:40 PM – 5:00 PM | Q&A Session Attendees will have the opportunity to ask questions related to technological trends, career development, and the evolving expectations of engineering professionals. 5:00 PM – 5:30 PM | Refreshments and Networking The event will conclude with an informal networking session accompanied by refreshments. This will provide an opportunity for attendees to interact with the speaker, discuss career pathways, and connect with fellow engineering students and professionals. Room: EN 102, Bldg: Engineering Building, Swinburne University of Technology, John Street, Hawthorne, Melbourne, Victoria, Australia, 3122 |
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Engage with cutting-edge innovation and research from Deakin University, presented through a special collaboration between GREG and the Deakin IEEE Student Branch. Co-sponsored by: Deakin University IEEE Student Branch Speaker(s): Igor, Abdur, Room: Haptic Lab, Bldg: NS, Deakin University - Institute for Intelligent Systems Research and Innovation (IISRI), 75 Pigdons Rd, Waurn Ponds, Geelong, Victoria, Australia, 3216 |
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