About Jing Deng

“New technologies like Artificial Intelligence are developing rapidly—how can we leverage them in our field?” asks Jing Deng. As a hydrologist and data scientist (AI/ML) at Deltares, she applies cutting-edge machine learning to improve hydrological modeling and forecasting, helping decision-makers navigate challenges like droughts and floods.

Contributions to 'Enabling Delta Life':
She develops AI-driven forecasting tools, including:

• Low-flow forecasting with LSTMs – Enhancing accuracy in operational discharge forecasting.
• XAI for machine learning hydrological models - Making data-driven models more transparent and explainable.
• Review on AI in water management – Exploring new AI applications in the field.
• LLMs-based tool/agentic workflow - Leveraging LLMs for data mining and automatic report generation.

Beyond project work, she works on the centralization of LLM-based tool development at Deltares and coordinates the DS/AI community, driving internal collaboration and innovation.

Impact & Skills:

• Bridging AI and hydrology to tackle water challenges.
• Advancing trustworthy AI for decision support.