I am a third year PhD Student (5 year PhD program) at Technical University Delft, where I’m part of the Interactive Intelligent Group at the Intelligent Systems Department of Faculty of Electrical Engineering, Mathematics and Computer Science. My PhD is part of Delft AI Labs and I belong to the HIPPO Lab, which aims to build AI-based decision support for addresing complex real-world problems such as climate change mitigation and adaptation.

My background and experience

I obtained MSc in Computer Science and Econometrics from the University of Warsaw (Poland) in 2020. Between my MSc studies and the current position at TU Delft, I worked at the European Space Agency (ESA) for 1.5 years as a Data Scientist Young Graduate Trainee (YGT) in the domain of socio-economic data in Oxford, United Kingdom.

Research

Climate change and other societal challenges demand decisions that balance multiple, often conflicting objectives across complex and uncertain environments. My research focuses on developing applied reinforcement learning methods to support such complex decision-making processes, particularly in domains like climate adaptation and sustainable resource management.

At the HIPPO Lab, we aim to build trustworthy, interpretable, and just AI-based decision-support systems for public policy design. These systems assist decision-makers in exploring the trade-offs inherent in policies for climate change mitigation and adaptation.

My PhD research focuses on Multi-Objective Reinforcement Learning (MORL) — a largely theoretical framework that enables learning across multiple, often conflicting objectives simultaneously. While MORL has significant potential for addressing complex real-world problems involving competing goals and uncertain environments, its application beyond simulation-based settings remains limited.

To bridge this gap, my work aims to make MORL applicable, interpretable, and explainable for decision-making in real-world contexts. I introduce practical, real-world problems where MORL can offer value, and develop methods and tools that help policymakers explore and understand the resulting trade-offs among learned policies. By combining algorithmic innovation with human-centered design, my research advances the use of reinforcement learning for complex, multi-objective decision-making, ensuring it becomes both usable and trustworthy for real-world applications.

For more information on specific projects within my PhD, please refer to the My PhD Projects tab.

Recent Highlights

• October 2025 Together with KWE, I am looking for an intern for our project on Urban Water Network Design via Multi-Objective Reinforcement Learning. Please contact me for more detials.

• August 2025 See the results of my work at Earth Systems Lab here. Our paper was accepted to Climate Change AI Neurips workshop!

• June 2025 I was accepted as a Fellowship Researcher in the Eearh Systems Lab to work on uncertainty quanitifcation and real-world deployment of Geospatial Foundation Models.

• April 29, 2025
  📄 My paper Exploring Equity of Climate Policies using Multi-Agent Multi-Objective Reinforcement Learning was accepted to IJCAI 2025, AI and Social Good Track.

• March 2025
  🚀 MORL4Water is now published on PyPI!
  📚 See documentation

• December 2024
  📝 Extended abstract Multi-Objective Reinforcement Learning for Water Management accepted to AAMAS 2025.

• October 2024
  🎤 Gave a Highlight Presentation at ECAI 2024, presenting my paper
  Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning

Research interests

My research interests lay in the areas of:

• Applied Reinforcement Learning
• Multi-Objective Reinforcement Learning
• Explainable AI
• AI-based decision-support
• Policy-Making
• AI application in the domain of public policies
• AI-based support for climate change mitigation and adaptation

Other activites & Teaching

• I am an active member of my faculty’s PhD Council, where we raise issues PhD face and try to address them.
• I also coordinate AI projects within Joint Interdisciplinary Project at TU Delft
• If you are interested in collaborating on a project with me or writing your master thesis, please refer to Open Calls Section of my website