Shared labs, real-world data and common validation standards, starting from two decades of human-robot interaction research in Sydney.
National Facility for Human-Robot Interaction Research, UNSW Sydney
High-quality, real-world data with spatial and behavioural ground truth, plus shared instrumentation, robots, sensors and simulation. Go from idea to market-ready product without building a lab first.
Standard environments, benchmarks and protocols for safety, reliability and human interaction, repeatable across labs and markets.
Open design, open infrastructure and open data where appropriate, so universities, startups and communities can take part.
In person and through its digital counterpart.
Two linked sites; partners engage at either.
Shared data, standards and validation.
One instrument, one team, one offer to partners.
Physical AI needs large volumes of real-world data and repeated cycles of hardware integration, simulation and testing. Building that alone takes time and money.
Systems that work alongside people must be proven for safety, reliability, interoperability, security and human interaction, not only technical performance.
Infrastructure is fragmented and held by a few institutions able to build multimillion-dollar proprietary labs.
Instrumentation, robotics platforms, sensors, simulation environments, test scenarios and reusable datasets, without building the lab yourself.
idea → data → development → testing → deployment
Common environments, methodologies, benchmarks and protocols for testing safety, reliability and human interaction.
Open infrastructure, open data where appropriate, and reusable designs, reference architectures and educational resources for universities, startups, students and underserved communities.
National Facility for Human-Robot Interaction Research, UNSW Sydney
Spatial and behavioural ground truth, captured unobtrusively; reference datasets and packaged scenarios.
A state-of-the-art, reconfigurable space where new systems are tested against real human behaviour before deployment.
Industry partners work with the Sydney Facility from day one, in person and through its digital counterpart, as the US facility is developed.
Two decades of multidisciplinary practice
Human-machine interfaces, from concept to evaluated prototype.
Creation and evaluation of new robotic systems, with people.
Advisory and design research on what comes next in physical AI.
Industry access from day one; data, testing and validation begin immediately.
Two linked sites; partners engage remotely at both.
Evidence before embodiment. Encounter before deployment.
As the network grows, a system built in one lab can be tested across different labs, operating environments, applications and markets before broad deployment.
Proven in Sydney on 20+ years of HRI practice.
A replicable framework that local organizations operate.
Shared standards and validation, everywhere.
SynCorpo Labs grows out of the National Facility for Human-Robot Interaction Research (NFHRI) UNSW Sydney in Australia: a purpose-designed environment for studying how people, robots and objects interact.
SynCorpo Labs extends the NFHRI concept for the Physical AI economy: accessible infrastructure for research, commercialization, validation, education and innovation.
Professor of Social Robotics at UNSW; founder and director of NFHRI and the Creative Robotics Lab. Two decades of HRI study design, experimental environments and industry research.
Founder and CEO of AI 2030. Responsible AI, enterprise partnerships, venture building and market development — connecting industry, government, research and capital.
Former IBM VP, Quantum Services and Quantum+AI. Helped put IBM's first quantum computer online as a web service — frontier infrastructure turned into a product external users can access.
The trusted intelligence and evidence layer for machines entering the physical world.
A global coalition that lets the people and institutions affected by Physical AI help design, test, govern and deploy it, while helping companies reach trusted adoption faster and with better evidence.
Instrumented environments, robotics platforms, real-world data and standardized validation.
Workers, users, communities, researchers, buyers, regulators and insurers, with shared methods and independent governance.
Affected users, operators and communities shape needs and limits before product decisions lock in.
Systems are observed and improved through direct interaction with people and real workflows.
Common methods and reporting make safety and readiness comparable.
Independent experts and affected communities have defined roles in oversight.
Feedback, re-testing and incident review continue after deployment.
A federated network of Open Physical AI Labs, with the people, methods and evidence to deploy Physical AI responsibly worldwide.
The National Facility for Human-Robot Interaction Research at UNSW Sydney. More than 20 years of purpose-designed research into how people, robots and objects interact, with real-time measurement and ground-truth data.
One of Australia’s leading research universities and home to NFHRI, connecting robotics, science and industry research.
A global movement mobilizing leaders and institutions to harness AI for people, planet and prosperity, and to build open and responsible AI infrastructure.
Velonaki co-authored the peer-reviewed research on ScentDia. The paper credits her with conceiving ScentDia and directing its design and development, exploring scent as a new dimension of social robotics.
The official program identifies Zhang as Executive Director of AI 2030 and features him in opening remarks on Chicago as a Responsible AI hub, discussions on AI and quantum, Chicago's AI identity, and the closing physical-AI panel.
IULM announced that the project developed by Luisa Damiano with Mari Velonaki and Manos Gerakinis was selected as a finalist at the International Conference on Social Robotics 2026 in London.
The AACS selected Zhang for an opening keynote, “From Wall Street to the Operating Room: Responsible AI Lessons Cosmetic Surgery Can’t Afford to Miss,” focused on safety, compliance and trust in AI-enabled healthcare.
IBM featured Faro, VP of Quantum and AI at IBM Research, discussing the shift from AI as a tool toward AI as a “teammate” and his concept of an Agentic Operating System for orchestrating agents, safety, compliance and resources.
IBM interviewed Faro about how increasingly capable AI agents could reshape the traditional application and operating-system model.
SynCorpo Labs is building the Open Physical AI Lab Network: shared, open environments where companies, researchers, startups and communities can build, test, validate and improve Physical AI systems.
Industry partners, startups, universities, researchers and public bodies. Partners can work with the Sydney Facility from day one, in person and through its digital counterpart.
High-quality physical AI data, technology testing and validation, and virtual and physical access, plus team expertise in interface design, robot design and future systems.
Labs share standardized environments, methodologies, benchmarks and protocols, so a system developed in one location can be validated across multiple real-world environments before broad deployment.
Yes. Once the lab model is established, local organizations will be able to operate labs connected through shared standards, knowledge, infrastructure and community. Get in touch through Partner / Join.
For companies and funders: become a design partner, access the Sydney Facility from day one, or back the 18-month seed plan.
For institutions and governments: host a locally operated lab connected to shared data, standards and validation.
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