 Senior Machine Learning Researcher PROWLER.io Cambridge, UK Contact me at felix.leibfried@gmail.com and download my CV here. About I am a senior machine learning researcher at PROWLER.io where I work on autonomous decision-making in high-dimensional environments. Specifically, my research focuses on reinforcement learning and lately on probabilistic modeling in the context of scalable Bayesian inference with deep learning. While my work is mostly centered around basic research, some of it has a more applied context, e.g. leading to a model-based reinforcement learning agent for autonomous trading in FinTec and a patent for tuneable artificial intelligence in computer games. Prior to my role at PROWLER.io, I interned at Microsoft Research in Cambridge, UK, working on model-based learning for image sequence and reward prediction in arcade games like Atari. I completed my PhD in artificial intelligence at the Max Planck Institutes for Intelligent Systems and Biological Cybernetics in Tuebingen, Germany. My educational background is computer science with focus on artificial intelligence (BSc+MSc) but I also obtained a degree in biology with focus on neuroscience (BSc+MSc). Publications → Google Scholar 2020 Pearce T, Leibfried F, Brintrup A, Zaki M and Neely A Proceedings of the Conference on Artificial Intelligence and Statistics (AISTATS) 2019 Leibfried F, Pascual-Diaz S and Grau-Moya J Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) 2019 Leibfried F and Grau-Moya J Proceedings of the Conference on Robot Learning (CoRL) 2019 Grau-Moya J, Leibfried F and Vrancx P Proceedings of the International Conference on Learning Representations (ICLR) 2018 Leibfried F and Vrancx P Workshop on Deep Reinforcement Learning at the Conference on Neural Information Processing Systems (NeurIPS Workshop) 2018 Leibfried F, Grau-Moya J and Bou-Ammar H Workshop on Deep Reinforcement Learning at the Conference on Neural Information Processing Systems (NeurIPS Workshop) 2018 Grau-Moya J, Leibfried F and Bou-Ammar H Balancing two-player stochastic games with soft Q-learning Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI) 2017 Leibfried F, Kushman N and Hofmann K Workshop on Principled Approaches to Deep Learning at the International Conference on Machine Learning (ICML Workshop) 2017 Peng Z, Genewein T, Leibfried F and Braun DA Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016 Grau-Moya J, Leibfried F, Genewein T and Braun DA Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2016 Leibfried F and Braun DA Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 2015 Genewein T, Leibfried F, Grau-Moya J and Braun DA Bounded rationality, abstraction, and hierarchical decision-making: An information-theoretic optimality principle Frontiers in Robotics and AI 2015 Leibfried F and Braun DA A reward-maximizing spiking neuron as a bounded rational decision maker Neural Computation 2015 Leibfried F, Grau-Moya J and Braun DA Signaling equilibria in sensorimotor interactions Cognition Patents 2017 Kim D, Nicholson T, Ferguson N, ..., Hensman J, Leibfried F, Grau-Moya J, John ST, Bou-Ammar H and Tukiainen A 2017 Grau-Moya J, Leibfried F and Bou-Ammar H |