Transforming Water Quality Monitoring Using Artificial Intelligence

“I am incredibly grateful and excited to receive a Data Science Emerging Investigator Grant from the Novo Nordisk Foundation. This support will allow us to develop AI models that can extract far more information from complex chemical data, with the long-term goal of improving detection and identification of harmful chemicals in environmental water samples and predicting the health consequences on the societal level. I’m very much looking forward to starting this five-year project in 2026.”

Says Svetlana Kutuzova, P1 Faculty and Assistant Professor at the Department of Computer Science, University of Copenhagen.

Under the growing pressures of climate change and pollution, global water supplies are increasingly under threat, affecting billions of people worldwide. Despite the vast amount of water analyzed every day for pollutants, nutrients, and other chemicals, advanced laboratory techniques can only identify an estimated 10% of the compounds.

Addressing these limitations leaving the majority of compounds unidentified, Kutuzova aims to redefine how water quality can be safeguarded, using artificial intelligence to increase our ability to understand what is truly in our water.

The focus of the project is to develop chemical foundation models for small molecule detection and identification from environmental samples to enable faster and more accurate analysis, detection, and prediction of hidden chemical fingerprints in complex water samples, while reinforcing monitoring abilities and water resilience, and subsequently contributing to the long-term protection of water resources for future generations.

Starting in fall 2026, Kutuzova will lead the five-year project, working in collaboration with P1 Co-lead Mads Nielsen, Professor at the Department of Computer Science, University of Copenhagen, and Jan H Christensen's group at the Department of Plant and Environmental Sciences, University of Copenhagen.

Title of the project

Chemical foundation models for small molecule detection and identification from environmental samples

Type of grant

NNF Data Science Emerging Investigator

Amount

12 million DKK

About the Data Science Emerging Investigator Grant

The purpose of the Data Science Emerging Investigator Grant is to support highly promising starting group leaders with ambitious projects rooted in data science and computational science with immediate or potential future applications within areas of relevance to Novo Nordisk Foundations’s Strategy.

The intended impact is to strengthen the quality and size of the Danish academic environment for data science research and education, which in turn will allow for an increased and improved output of new candidates skilled in data science and computational science, to meet the strong demand for such competencies from all sectors of society.