The Letten Prize Day will be on September 4th, 2025.
The day will consist of the following events:
10-16:00: The Letten seminar in honor of the 2023 Letten Prize laureate, professor Paula Moraga.
18-19:00: The Letten Prize award ceremony for the 2025 Letten Prize laureate, professor Danielle Wood. The award ceremony will be followed by a celebratory dinner (Dinner by invitation only).
You can follow the livestream on our Youtube
The Letten Seminar:
The Letten Prize Seminar is in honor of the 2023 Letten Prize Winner Paula Moraga.
Time: September 4th, 2025, 10:00- 16:00 (CET)
Place: The Norwegian Academy of Science and Letters,
Drammensveien 78, 0271 Oslo
Reception: There will be a reception immediately after the Letten Seminar. Everyone attending the seminar is welcome.
The seminar will open with welcoming and introductory remarks from representatives of the Letten Foundation and the Young Academy of Norway, setting the stage for a day of scientific exchange and dialogue. Professor Arnoldo Frigessi, chair of the programme committee, will provide an academic framing, introducing the thematic focus of the event.
The first keynote will be delivered by Professor Paula Moraga, the 2023 Letten Prize laureate, who will present her work on Geospatial Statistics and Health Surveillance. Following this, Professor Peter Diggle will speak on Geospatial Statistical Methods to Support the Control and Elimination of Neglected Tropical Diseases. Professor Geir-Kjetil Sandve will then explore the intersection of AI and biomedical data, before the seminar pauses for lunch.
The afternoon session will feature four short research talks, each highlighting different intersections of data science, AI, and societal applications. Sigrunn Holbek Sørbye will discuss the application of advanced statistical methods to real-world problems, followed by Filippo Maria Bianchi with an introduction to Spatiotemporal Graph Neural Networks. Pedro Lind will then trace a path from classical physics to innovations in health and technology through AI, and Arnt-Børre Salberg will conclude the session with a presentation on Earth observation foundation models for climate and society.
Later, Professor Kristin Braa will deliver a keynote on Digital health and development, before the day transitions into a panel discussion bringing together the 2023 Letten Prize laureate and keynote speakers to reflect on the seminar’s themes. The event will conclude with a reception, providing an opportunity for informal networking and continued discussion.
Detailed program:
| Time | Name | Subject | |
| Welcome | 10:00 | Letten Foundation and the Young Academy of Norway | Welcoming and introductory remarks |
| Scientific framing | 10:10 | Professor Arnoldo Frigessi, program committee leader | Introduction to the academic focus of the seminar |
| Keynote: | 10:16 | Professor Paula Moraga | The 2023 Letten Prize laureate keynote on Geospatial Statistics and Health Surveillance |
| Break | |||
| Keynote: | 11:28 | Professor Peter Diggle | Geospatial Statistical Methods to Support the Control and Elimination of Neglected Tropical Diseases |
| Keynote: | 12:11-12:28 | Professor Geir-Kjetil Sandve | From piloting to routine operation: a platform for local ownership of spatiotemporal modelling |
| Lunch 12:30 | |||
| Short research talks | 13:30-13:45 | Sigrunn Holbek Sørbye | Bringing advanced statistical tools to real-world applications |
| 13:45-14:00 | Filippo Maria Bianchi | A primer on Spatiotemporal Graph Neural Networks | |
| 14:00-14:15 | Pedro Lind | From classical physics to health and technology, through the path of AI | |
| 14:15-14:30 | Arnt-Børre Salberg | Earth observation foundation models for climate and society | |
| Keynote | 14:30-14:50 | Professor Kristin Braa | Digital health and development |
| Break | |||
| Panel discussion and closing | 15:00 | The 2023 Letten Prize laureate and the keynote speakers reflects on the seminar. | |
| Reception | 16:00-17:00 | ||
Paula Moraga was awarded the Letten Prize 2023 for her pioneering research aimed at the early detection of epidemics and the design of control strategies worldwide. Her work focuses on developing innovative and cost-efficient disease surveillance systems with finer spatial and temporal resolution than those currently available. Dr. Moraga’s research has provided national health organizations with comprehensive tools to make better use of their data and improve public health outcomes.
Dr. Moraga will open the seminar by speaking about her research and how the Letten Prize funding has supported her work.
Other speakers
The seminar in Paula Moraga’s honor is being developed by a committee led by Arnoldo Frigessi, professor of statistics at the Department of Biostatistics, University of Oslo. Several young Norwegian academics specializing in fields related to Paula Moraga’s research will speak at the seminar. A range of other speakers has also been confirmed:
- Professor Emeritus Peter Diggle, Lancaster University, conducts research on the development and application of statistical methods relevant to the biomedical and health sciences. He is currently involved in several public health projects in low-resource settings, where statistical modelling of spatial and temporal variation in disease risk can help compensate for the lack of comprehensive registry data.
- Professor Kristin Braa is the director of the HISP Centre at University of Oslo, which is the home to the DHIS2 project. DHIS2 is developed as a free and open-source global public good. DHIS2 is used for national-scale deployments in 75 low and middle-income countries. It covers 3.2 billion people and is recognized as a global public good by the World Health Organization. HISP is a global action research network of 24 in-country and regional organizations that collaborates on developing global resources, as well as providing direct support to ministries.
The platform is now the primary tool for health data collection and analysis for governments in 75 countries. It covers 3.2 billion people and is recognized as a global public good by the World Health Organization.
Strengthen the climate resilience of national health systems focusing on how countries in the Global South can leverage open-source tools to integrate and harmonize climate and health data to support risk analysis and leverage machine learning to predict future trends and forecast disease outbreaks.
- Professor Geir Kjetil Ferkingstad Sandve, Scientific Computing and Machine Learning Group (SCML), Department of Informatics (IFI), University of Oslo, develops machine learning methodology inspired by major open challenges in the real world, mostly within life science. His current research is mainly focused on two challenges: 1) deciphering how immune cells recognise and mounts a response to foreign threats, and 2) learn models of how climate impacts disease incidence and use these models to provide early warnings of disease outbreaks.
- From a methodological standpoint, the research particularly emphasizes the generalization ability of machine learning models, the incorporation of mechanistic and causal knowledge into modelling, the development of domain-adapted machine learning software platforms, and methods for multiple-instance learning. The climate-sensitive disease challenge is about learning multi-variable, spatiotemporal models of disease incidence, where the focus is currently on how to develop integrated platforms that allow rigorous side-by-side method benchmarking, promotes method reuse, streamlines the transition from pilot models to routinely operating early warning systems, and most importantly allows local ownership and control of this entire process.
In addition to the keynotes, four researchers are invited to hold stort talks on their fields relating to Paula Moraga’s research:
- Filippo Maria Bianchi, Associate Professor at the Department of Mathematics and Statistics at UiT the Arctic University of Norway and a senior researcher at NORCE the Norwegian Research Centre. His research interests lie at the intersection between machine learning, dynamical systems, and complex networks. He developed several machine learning approaches for time series, graphs, and spatio-temporal data and applied them mostly to energy analytics, remote sensing, and health data.
- Arnt-Børre Salberg, chief research scientist at the Norwegian Computing Center (NR), specializing in Earth observation and AI research. At NR he develops methods for automatic analysis of remote sensing data for various applications, including land cover and hazard mapping. Salberg has managed and conducted several AI projects for European Space Agency, businesses and public organizations.
- Sigrunn Holbek Sørbye, professor in statistics at UiT The Arctic University of Norway. Her primary research focuses on Bayesian statistical modelling, with an emphasis on the analysis of time series and spatially structured data. Her work spans both methodological development and interdisciplinary applications, with particular interest in climate research, environmental science, and health.
- Pedro Lind, professor of scientific computing at Kristiania University of Applied Sciences and at Oslo Metropolitan University. His main scientific activities intersect the topics of data modelling and data analysis, with development of statistical and mathematical methods and open source numerical routines, as well as applications to health, geophysics and renewable energies.