Physical AI Meetup Auckland

A big thanks to our university partner, UoADSC — University of Auckland Data Science Club, for partnering with us to bring the Physical AI Meetup to Auckland.

This Auckland edition is hosted by Avnet & AMD, together with UoADSC, bringing together engineers, researchers, students, founders, industry partners, suppliers, and innovators to explore how AI moves from software into the real physical world — across edge devices, embedded systems, sensors, AI hardware, FPGA platforms, local LLMs, and real-world intelligent products.

Pizza and drinks for this meetup are made possible by Avnet & AMD, supporting the growing Physical AI community across Australia and New Zealand.

Take the mic at our Community Open Mic.

Share a quick demo, prototype, research idea, startup project, hardware design, embedded AI project, robotics work, or collaboration announcement — whether it is AI, hardware, sensors, robotics, edge computing, FPGA, local LLMs, or something you are building. All welcome.

Please have your Eventbrite ticket ready at check-in — then enjoy pizza, drinks, and time to connect with other attendees.

Hear a short welcome from the organisers and an introduction to the Physical AI Meetup community across Australia and New Zealand.

We will also briefly introduce the mission of the community: building a bridge between academia, industry, suppliers, engineers, founders, and students to help turn ideas into real products.

Overview:
AI is moving from the cloud into the physical world — onto phones, wearables, sensors, and embedded devices. This talk explores the evolution from TinyML and mobile sensing to emerging on-device small language models and LLM-powered edge AI systems.

The session will discuss how we can build efficient, personalised, and trustworthy AI systems under real-world constraints such as limited compute, energy, noisy data, privacy, and reliability.

Speaker: Dr. Hong Jia
Lecturer, University of Auckland | Honorary Senior Fellow, University of Melbourne

Dr. Hong Jia is a Lecturer at the University of Auckland and an Honorary Senior Fellow at the University of Melbourne. He previously worked as a Research Associate at the University of Cambridge and received his Ph.D. in Computer Science from UNSW in 2021.

His research focuses on AI and machine learning systems for edge devices, with applications in digital health, personalised monitoring, self-improving on-device and small language models, and uncertainty-aware AI. His work has been recognised with several awards, including the ACM MobiSys Rising Star Award 2023, Best Paper Runner-Up at ACM IPSN 2024, and Best Poster Runner-Up at ACM MobiCom 2022.

Overview:
AI has already transformed software development — and FPGA design may be next.

In this talk, Joe Peng will introduce how Agentic AI can help engineers move beyond traditional manual RTL, Tcl scripting, log analysis, and repeated Vivado iterations toward more automated, closed-loop FPGA design workflows.

The session will explore how the AMD Vivado MCP Server and structured agent skills can support real FPGA engineering tasks such as documentation search, Tcl execution, design analysis, timing closure, congestion analysis, CDC review, hardware debug, and implementation flow automation.

Joe will also discuss why raw LLMs alone are not enough for hardware design, where hallucinated Tcl commands, weak multi-step reasoning, and stale tool knowledge can break real builds. Instead, he will share how prompt engineering, context engineering, and harness engineering can work together to make AI-driven FPGA workflows more reliable, measurable, and grounded in real Vivado execution.

Speaker: Joe Peng, PhD, MBA
Sr. Regional Sales Manager, Australia & New Zealand, AMD / Xilinx

Joe Peng is the Senior Regional Sales Manager for Australia and New Zealand at AMD, with extensive experience across embedded systems, X86, AI, and FPGA technologies.

Joe has held senior industry leadership roles, including Vice President and CTO at a Texas Instruments joint venture , where he led teams to develop and commercialise multiple product lines from concept to profitability. He later joined STMicroelectronics, serving as an FAE Manager for STM32 and IoT/AI specialist, helping grow the ANZ business through a consultative technology engagement approach.

In addition to his industry role, Joe is also a Guest Professor at the University of Sydney. He is passionate about new technology, innovation, and sharing practical industry insights with engineering and academic communities.

Overview:
dataengine will delve into current AI trends in the market and present a live demo of an LLM Wiki powered by a Local LLM.

This session will explore how organisations can apply generative AI, local language models, and modern AI delivery frameworks to improve knowledge management, internal search, privacy, and real business outcomes.

Speaker: Sijie Wang
AI Practice Lead, dataengine

Sijie Wang is the AI Practice Lead at dataengine. With a master’s degree from the University of Auckland, Sijie specialises in end-to-end AI solutions across machine learning, generative AI, and MLOps.

He leverages modern platforms to deliver practical insights and impactful data-driven outcomes for organisations across diverse business environments globally.

About dataengine
dataengine partners with organisations to turn data into a strategic asset. The company designs and delivers modern cloud data platforms, advanced analytics, and AI solutions that accelerate insights and unlock measurable business value.

With deep expertise across industries, dataengine applies modern delivery frameworks such as DataOps and AIOps to improve agility, streamline decision-making, and enable innovation at scale.

Overview:
Turning AI concepts into real products requires more than algorithms. It requires hardware, software, system integration, engineering discipline, deployment experience, and a clear path from prototype to production.

This talk will share practical perspectives on AI-enabled systems, embedded platforms, edge computing, hardware/software integration, FPGA acceleration, and how design services can help organisations move from concept to real-world deployment.

Speaker: James Lau
Senior Director, Avnet Design Services

James Lau is a senior technology leader at Avnet Design Services, with deep experience in AI, embedded systems, FPGA acceleration, and engineering innovation across the Asia-Pacific region.

He works with organisations to bridge the gap between emerging technologies and deployable solutions, with a strong focus on AI-enabled systems, edge computing, hardware/software integration, and scalable product development.

Short informal shares — demo, prototype, research idea, startup project, hiring announcement, collaboration opportunity, project update, or community announcement.

Each share will be around 1–2 minutes.

All topics around AI, hardware, robotics, sensors, FPGA, edge computing, embedded systems, local LLMs, and physical intelligence are welcome.

Any further Q&As, discussions, and chats will happen here.

Connect with students, researchers, engineers, founders, sponsors, suppliers, and industry partners — and explore how we can work together to turn ideas into real products.

Launched in Sydney and now growing across Melbourne, Perth, Auckland, and beyond, the Physical AI Meetup is a hands-on community where engineers, founders, academics, students, suppliers, and industry partners come together to explore AI and hardware in real-world systems.

We focus on the bridge between academia, industry, and suppliers — helping ideas move from research, prototypes, and demos into practical systems and real products.

Join the Meetup group to stay in the loop on upcoming events across Australia and New Zealand.

Event Venue & Nearby Stays

201 342/10 Symonds Street, 10 Symonds Street, Auckland, New Zealand

Concerts, fests, parties, meetups - all the happenings, one place.

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