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Field
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. Most of our research focuses on social dilemmas, i.e., situations where poor group outcomes arise from optimal individual choices. We use this framework to study: Multi-agent Systems and AI, Social
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machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety : Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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recommendations and learn from experience to improve wireless network energy efficiency. The research combines large language models, multi-agent systems, reinforcement learning and knowledge evolution
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multi-agent LLM systems Efficiency: Streamlining large-scale model experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers
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Agent-Based Models, hydrological and flood models. GEB can simulate the dynamics between multiple hazard risk, how these risk impact society, vulnerability of different sectors, and how society can
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under Uncertainty - Decision-making under uncertainty - Decentralized planning and coordination for multi-agent systems b. Mapping and Scene Representations - Dynamic Scene Graphs modelling uncertainty
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-agent systems, swarm robotics or distributed coordination of autonomous agents experience with multi-robot or mission planning, autonomous decision-making or self-adaptive systems experience with robot
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perception, planning, and control for robotic handling and assembly operations Collaborative humanoid robotics: Investigation of learning-based coordination strategies, including multi-agent
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effective adult and/or youth education programs. Provides expertise for disciplinary, multi-disciplinary, and/or interdisciplinary programming and projects of the agency. Applies an understanding of
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engineering, robotics, electrical engineering or a related field. Furthermore, you should have: experience with multi-agent systems, swarm robotics or distributed coordination of autonomous agents