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