100 + INNOVATIONS
CRUISE Lab- Human- Centric and Robust Machine-Learning Model Research
Pioneering human-centric, trustworthy AI with multimodal spatiotemporal intelligence
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Research Project
Prototype developed
Challenge
Today’ s complex, noisy and irregular data limits effective decision-making. Traditional AI struggles with multimodal, spatiotemporal and sensor-driven data, creating challenges in extracting insights, powering future cities with reliable modelling and forecasting across sectors, and developing data-efficient models to harness health and wearable sensor data for improved outcomes.
Solution
The CRUISE Lab develops data and model-efficient AI methods to interpret complex, noisy and heterogeneous data, ensuring reliable and sustainable operation in real-world settings. Their solutions include foundation models and LLMs for multimodal time-series and geospatial data. They work on spatio-temporal modelling for applications like traffic, energy and health, and use continual learning techniques for LLMs and VLMs. They also develop agentic and embodied AI for simulations and advanced models for climate and weather forecasting. These innovations enable scalable, trustworthy AI for dynamic environments across various sectors.
Target customers / end-users
• urban stakeholders: smart cities, transport, mobility, energy and buildings
• government, Defence and security agencies
• industry partners: property, retail, infrastructure, asset managers and sustainability sectors.
Progress
• > AU $ 20m research funding with global industry and government partnerships
• deployed predictive analytics improving urban infrastructure management
• pioneered natural language processing( NLP)/ LLMs for timeseries analysis
• real-world deployment and adoption of predictive and recommendation systems software
TRL 3
Sustainable transition
Intelligent Systems, Quantum & Space
CRUISE Lab is at the forefront of research in human-centric and robust machine-learning models, large language models( LLMs), vision language models( VLMs), multimodal foundation models( MFMs) and AI systems. It focuses on foundation models and reasoning techniques for multimodal data and sensors, with applications in healthcare, mobility, infrastructure and Defence.
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