MrThien (Peter) Tran

As a passionate technology enthusiast focused on Industry 4.0/5.0 and Society 5.0, Peter is currently a graduate researcher at Deakin University, advancing an early-stage hybrid Cloud–Edge–Robotics (CER) architectural framework for Next-Generation Industrial Cyber-Physical Systems (NG-ICPS) alongside AI/SI breakthroughs. His work is grounded in the Cloud–Fog Automation (CFA) paradigm and 4C co-design principles (Cognition, Control, Computing, and Communication) to enable time-critical, scalable, and resilient networked autonomy across fleets of robots, so any machine can move and cooperate safely with humans by unifying IT-OT-CT domains.

To bring Physical/Embodied AI into the world, deterministic connectivity (TSN, 5G/6G, AI-native Network) is the first core, and distributed intelligence and computing in gigantic AI/SI infrastructure (federated/split learning, on-device inference), is the second core, alongside massive energy requirements. He studied QoS-aware control, adaptive/dynamic task offloading, and sim-to-real deployment in multi-robot collaboration and telerobotics settings, extending to MAS.

Why now?

Industry is shifting from isolated cells to distributed, AI-enabled factories and field robots. Scaling physical AI demands deterministic networks, accountable edge intelligence, and standards-based orchestration across cloud tiers, edge nodes, and machines. Peter's research addresses core bottlenecks, latency, reliability, energy, and safety, and delivers a reusable CER reference architecture and open testbed that researchers and stakeholders can adopt to shorten integration time, cut energy use, and improve safety in real deployments, ready for the AI application era.

With a technical degree in Robotics & Mechatronics Engineering from RMIT University, hands-on experience at ABB Robotics, and lived experience, Peter's core values integrate rigorous academia with practical industrial automation know-how and tech passion. His research team develops a CER architecture and testbed spanning cloud, edge, and robotics tiers (ROS2, K8s, AI accelerators, etc.) to evaluate latency, reliability, safety, and energy efficiency under real-world constraints, then orchestrates these systems with AI-driven QoS-aware control entities, aligning with the following Sustainable Development Goals (SDGs): Core SDGs: #9 - #4 - #12 - #17 | Indirect SDGs: #7 - #8 - #11

Latest update: October 2026 | © Thien (Peter) TRAN - All rights reserved.