Rossella Arcucci

Information

Bio

Rossella Arcucci is a mathematician, machine learner, and societal engineer. She obtained her Master’s degree in Applied Mathematics in 2008 from the University of Naples Federico II and her PhD in Computational and Computer Science in 2012.

Professor Arcucci has been actively involved in operational research since her PhD, continuing through her first postdoctoral position at the Euro-Mediterranean Centre on Climate Change.

Her research addresses fundamental questions on how to effectively use big data, improve its reliability, and reduce uncertainty in predictive model development to extract meaningful features and actionable outcomes. She pioneered the integration of Data Assimilation with Machine Learning, creating the field of Data Learning. Her work spans diverse areas including weather prediction, wildfire modelling, flood nowcasting, healthcare, and epidemic control, all with a focus on saving human lives in crises.

Current Role

She is currently an Associate Professor in Data Learning and AI for Good at Imperial College London, where she also serves as Director of Research at the Imperial Data Science Institute and Director of the Ada Lovelace Academy. In 2018, she founded and now leads the Data Learning Group, a research team dedicated to advancing Data Assimilation and Machine Learning through interdisciplinary and international collaboration.

Areas of Expertise

Professor Arcucci’s expertise includes Data Assimilation, AI for Earth Observation, Computational Modelling, Physics-Informed Machine Learning (PIML), and Large Language Models (LLMs). She works with diverse data sources, from satellite imagery and sensor networks to social media and real-world observational datasets.

Her methods integrate heterogeneous data while respecting physical laws, enabling the development of interpretable, reliable, and scientifically grounded predictive systems. This capability supports the creation of multi-source AI pipelines and physics-aware models that can significantly benefit ESA Φ-lab projects, particularly in climate, environmental, and societal monitoring, and the development of next-generation trustworthy AI aligned with ESA’s mission.

Vision for the Future

Professor Arcucci envisions a future in which AI and Physics-Informed Machine Learning operate seamlessly with diverse data sources—from satellite systems to ground-based sensors and social information streams—to build trustworthy, interpretable, and high-impact digital twins of the Earth.

Her goal is to develop AI systems that do not simply analyse data but explain, predict, and assist decision-making across environmental and societal domains at multiple scales. By combining LLMs, multi-source data fusion, and physics-based intelligence, her work aims to support and accelerate innovation in Earth observation, climate monitoring, and sustainable development, advancing ESA Φ-lab’s mission through science-grounded and human-relevant AI.