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Resume (English only)
Academic Achievements
Developed MOMAland, an open-source multi-objective multi-agent reinforcement learning Python library; will be giving a tutorial on multi-objective (multi-agent) decision-making at AAMAS 2024; published work on 'Emergent Cooperation under Uncertain Incentive Alignment'.
Research Experience
She has extensive experience in developing multi-agent decision systems, particularly where each agent is driven by different objectives and goals.
Education
Previously, she was a FWO Postdoctoral fellow at the Artificial Intelligence Lab, Vrije Universiteit Brussel, Belgium.
Background
Currently an Assistant Professor in AI and Data Science at the Department of Information and Computing Sciences, Utrecht University. Her research focuses on the development of multi-agent decision-making systems under the paradigm of multi-objective multi-agent reinforcement learning.
Miscellany
Offers several tutorials and lectures on multi-objective decision-making, including both single and multi-agent settings.