Aidan Scannell

Postdoctoral researcher | Machine learning | Sequential decision making | Robotics


Hello, my name is Aidan Scannell and I am a postdoctoral researcher with interests at the intersection of machine learning, sequential decision making and robotics. My research aims at enabling autonomous agents to learn behaviours, such that they can learn to solve any task. I am particularly interested in controlling agents with natural language instructions and the challenges associated with developing a robotic foundation model which can generalise across tasks, objects and embodiments.


I am a Finnish Center for Artificial Intelligence postdoctoral researcher at Aalto University in Joni Pajarinen’s Robot Learning Lab and Arno Solin’s Machine Learning Research Group. I obtained my PhD from the University of Bristol under the supervision of Arthur Richards and Carl Henrik Ek. During my PhD I developed methods for controlling quadcopters in uncertain environments by synergising methods from probabilistic machine learning, stochastic differential geometry and reinforcement learning.

  • Reinforcement learning
  • Embodied AI
  • Representation learning
  • World models
  • Robotics
  • PhD Robotics and Autonomous Systems, 2022

    University of Bristol, UK

  • MEng Mechanical Engineering, 2016

    University of Bristol, UK

Recent Publications

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(2024). iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning. arXiv.

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(2024). Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning. 4th Annual Conference on Learning for Dynamics and Control (L4DC).

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(2024). Function-space Prameterization of Neural Networks for Sequential Learning. The Twelth International Conference on Learning Representations (ICLR).

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(2023). Sparse Function-space Representation of Neural Networks. ICML 2023 Workshop on Duality Principles for Modern Machine Learning.

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(2023). Mode-constrained Model-based Reinforcement Learning via Gaussian Processes. 26th International Conference on Artificial Intelligence and Statistics (AISTATS).

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