Curriculum Vitae

Simone Parisi

For the complete list of publications, please see here.

Current Position
2014 - 2019Ph.D. Candidate in Computer Science
 Technische Universität Darmstadt, Germany
 Thesis: Reinforcement Learning with Sparse and Multiple Rewards
 Supervisor: Jan Peters
Professional Experience
2017Research Intern
 RIKEN AIP, Tokyo, Japan
 Supervisors: Masashi Sugiyama, Emtiyaz Khan
Educational Background
2015Machine Learning Summer School
 Max Planck Institute for Intelligent Systems, Tübingen, Germany
2011 - 2014Master of Science in Computer Science and Engineering
 Politecnico di Milano, Italy
 Thesis: Study and Analysis of Policy Gradient Approaches for Multi-Objective Decision Problems
 Supervisors: Marcello Restelli, Matteo Pirotta
2012Exchange Student
 University of Queensland, Brisbane, Australia
2008 - 2011Bachelor of Science in Computer Science and Engineering
 Politecnico di Milano, Italy
Invited Talks
30 Aug 2019University of Texas, Learning Agents Research Group (LARG), Austin, United States
 Host: Peter Stone
28 Aug 2019Brown University, Dept. of Computer Science, Providence, United States
 Host: Michael Littman
26 Aug 2019Facebook Artificial Intelligence Research (FAIR), Pittsburgh, United States
 Host: Abhinav Gupta
24 May 2019Max Planck Institute (MPI), Dept. of Empirical Inference, Tübingen, Germany
 Host: Bernhard Schölkopf
6 May 2019Delft University of Technology, Dept. of Cognitive Robotics (CoR), Delft, Netherlands
 Host: Jens Kober
3 May 2019University of Amsterdam, Machine Learning Lab (AMLab), Amsterdam, Netherlands
 Hosts: Herke van Hoof, Max Welling
14 Dec 2017Advanced Telecommunications Research Institute (ATR), Kyoto, Japan
 Host: Jun Morimoto
2 Oct 2017RIKEN Center for Advanced Intelligence Project (AIP), Tokyo, Japan
 Host: Emtiyaz Khan, Masashi Sugiyama
Teaching
2019Reinforcement LearningTeaching AssistantTechnische Universität Darmstadt
2017Statistical Machine LearningTeaching AssistantTechnische Universität Darmstadt
2016Robot LearningTeaching AssistantTechnische Universität Darmstadt
2016Statistical Machine LearningTeaching AssistantTechnische Universität Darmstadt
Reviewing
2020International Conference on Automated Planning and Scheduling (ICAPS)
2020International Conference on Robotics and Automation (ICRA), Workshop Proposal
2019Workshop on Robot Learning, Conference on Neural Information Processing Systems (NIPS)
2019International Conference on Learning Representations (ICLR)
2018Workshop on Reinforcement Learning under Partial Observability, Conference on Neural Information Processing Systems (NIPS)
2018Workshop on Prediction and Generative Modeling in Reinforcement Learning, Conference on Flexible Automation and Intelligent Manufacturing (FAIM)
2018Conference on Robot Learning (CoRL)
2018Program Committee, European Workshop on Reinforcement Learning (EWRL)
2018Program Committee, AAAI Conference on Artificial Intelligence (AAAI)
2017Neurocomputing
2017International Conference on Intelligent Robots and Systems (IROS)
2017International Conference on Robotics and Automation (ICRA)
2017Program Committee, AAAI Conference on Artificial Intelligence (AAAI)
2016Neurocomputing
2016International Journal of Advanced Robotic Systems (IJARS)
2016Journal of Machine Learning Research (JMLR)
2016Robotics: Science and Systems (R:SS)
2016International Joint Conference on Artificial Intelligence (IJCAI)
2016Neurocomputing: Special Issue on Multi-objective Reinforcement Learning
2015Program Committee, European Workshop on Reinforcement Learning (EWRL)
2015International Conference on Intelligent Robots and Systems (IROS)
2015International Conference on Automation Science and Engineering (CASE)
Supervision
Mentzendorff, E. (2020). Bridging the Gap Between Multi-objective and Multi-task Deep Reinforcement Learning, Master Thesis.
Cui, K. (2019). A Study on TD-regularized Actor-critic Methods, Master Thesis.
Zhang, S. (2019). Integration of Self-imitation and Model-based Learning to Actor-critic Algorithms, Master Thesis.
Hubecker, S. (2019). Curiosity-driven Reinforcement Learning for Autonomous Driving, Master Thesis.
Keller, L. (2019). Application of Reinforcement Learning Algorithms to Robotics Simulators, Bachelor Thesis.
Zhang, S.; Wan, L. (2018). Enhancing Exploration through Curiosity for Robotics, Integrated Project.   Download Article [PDF]   BibTeX Reference [BibTex]
Ramstedt, S. (2017). Bayesian Deep Reinforcement Learning: Tools and Methods, Integrated Project.   Download Article [PDF]   BibTeX Reference [BibTex]
Ramstedt, S. (2016). Deep Reinforcement Learning with Continuous Actions, Bachelor Thesis.   Download Article [PDF]   BibTeX Reference [BibTex]
Klie J. C., Li X. (2015 - 2016). Feature Selection for Tetherball Robot Games, Integrated Project.
Blank A., Viernickel T. (2014 - 2015). Multi-objective Reinforcement Learning for Tetherball Robot Games, Integrated Project.

  

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