DATA SCIENCE & AI LEAD | NEW ZEALAND INSTITUTE FOR PUBLIC HEALTH & FORENSIC SCIENCE
Dr Alvaro Orsi
Dr Alvaro Orsi is a Data Science & AI Lead with extensive experience leveraging AI and advanced analytics to transform insights-driven solutions across scientific and business domains. At the Institute for Environmental Science and Research (ESR), he spearheads AI-powered innovations, orchestrating cutting-edge solutions through technologies such as Generative AI, Digital Twins, Large Population Models, Geospatial data science, and Time series forecasting. Throughout his career, Dr Orsi has applied AI and advanced analytics to diverse sectors, including supply chain logistics in primary industries, remote sensing of vegetation, productivity forecasting, and delivering data-driven insights for government agencies. His expertise spans multiple fields, including astrophysics, machine learning, and remote sensing of vegetation. Before joining ESR, Dr Orsi was a Principal Research Scientist at PlantTech Research Institute, developing AI and machine learning solutions for New Zealand’s primary industry. His background in Computational Astrophysics includes work in Spain, the UK, and his native Chile, contributing to a global perspective that enriches his approach to data science. Dr Orsi holds a PhD in Computational Cosmology from Durham University, UK. He has published over 80 peer-reviewed papers across various disciplines, including astrophysics, machine learning, remote sensing, and epidemiological data science. Currently, he serves as a Board member for the AI Researchers Association of New Zealand. Committed to shaping the future of data science in New Zealand and beyond, Dr Orsi strives to foster a new era of AI-powered solutions that deliver positive impact for New Zealand’s economy, society, and environment.
Presentation: Revolutionising Decision-Making with AI-powered Digital Twins
In this presentation I will introduce ALMA (Aotearoa Large-Scale Multi-Agent Platform), ESR’s revolutionary digital twin technology that’s transforming how we approach complex system challenges. I’ll demonstrate how we’ve created a computational environment that simulates 5 million synthetic New Zealanders, each characterised by multiple attributes, enabling unprecedented fidelity in modelling population behaviour and infrastructure interaction. This platform features a powerful synthetic population generator with demographic, socioeconomic and behavioural attributes; an advanced routing model that simulates realistic movement through transportation networks; and sophisticated AI capabilities including multivariate time series forecasting, automated causal discovery and large-scale social dynamics modelling. I’ll discuss applications across industries, including how engineers can use ALMA for urban planning and infrastructure management, testing resilience against extreme events, optimising transportation networks, and evaluating the impacts of public policy on infrastructure. I’ll share real-world case studies including our successful COVID-19 hospitalisation forecasts and measles outbreak simulations that demonstrate ALMA’s predictive capabilities.