Curriculum Vitae

Simone Parisi

For the complete list of publications, please see here.

Current Position
2014 - 2019	Ph.D. Candidate in Computer Science
	Technische Universität Darmstadt, Germany
	Thesis: Reinforcement Learning with Sparse and Multiple Rewards
	Supervisor: Jan Peters

Professional Experience
2017	Research Intern
	RIKEN AIP, Tokyo, Japan
	Supervisors: Masashi Sugiyama, Emtiyaz Khan

Educational Background
2015	Machine Learning Summer School
	Max Planck Institute for Intelligent Systems, Tübingen, Germany
2011 - 2014	Master 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
2012	Exchange Student
	University of Queensland, Brisbane, Australia
2008 - 2011	Bachelor of Science in Computer Science and Engineering
	Politecnico di Milano, Italy

Invited Talks
30 Aug 2019	University of Texas, Learning Agents Research Group (LARG), Austin, United States
	Host: Peter Stone
28 Aug 2019	Brown University, Dept. of Computer Science, Providence, United States
	Host: Michael Littman
26 Aug 2019	Facebook Artificial Intelligence Research (FAIR), Pittsburgh, United States
	Host: Abhinav Gupta
24 May 2019	Max Planck Institute (MPI), Dept. of Empirical Inference, Tübingen, Germany
	Host: Bernhard Schölkopf
6 May 2019	Delft University of Technology, Dept. of Cognitive Robotics (CoR), Delft, Netherlands
	Host: Jens Kober
3 May 2019	University of Amsterdam, Machine Learning Lab (AMLab), Amsterdam, Netherlands
	Hosts: Herke van Hoof, Max Welling
14 Dec 2017	Advanced Telecommunications Research Institute (ATR), Kyoto, Japan
	Host: Jun Morimoto
2 Oct 2017	RIKEN Center for Advanced Intelligence Project (AIP), Tokyo, Japan
	Host: Emtiyaz Khan, Masashi Sugiyama

Teaching
2019	Reinforcement Learning	Teaching Assistant	Technische Universität Darmstadt
2017	Statistical Machine Learning	Teaching Assistant	Technische Universität Darmstadt
2016	Robot Learning	Teaching Assistant	Technische Universität Darmstadt
2016	Statistical Machine Learning	Teaching Assistant	Technische Universität Darmstadt

Reviewing
2020	International Conference on Automated Planning and Scheduling (ICAPS)
2020	International Conference on Robotics and Automation (ICRA), Workshop Proposal
2019	Workshop on Robot Learning, Conference on Neural Information Processing Systems (NIPS)
2019	International Conference on Learning Representations (ICLR)
2018	Workshop on Reinforcement Learning under Partial Observability, Conference on Neural Information Processing Systems (NIPS)
2018	Workshop on Prediction and Generative Modeling in Reinforcement Learning, Conference on Flexible Automation and Intelligent Manufacturing (FAIM)
2018	Conference on Robot Learning (CoRL)
2018	Program Committee, European Workshop on Reinforcement Learning (EWRL)
2018	Program Committee, AAAI Conference on Artificial Intelligence (AAAI)
2017	Neurocomputing
2017	International Conference on Intelligent Robots and Systems (IROS)
2017	International Conference on Robotics and Automation (ICRA)
2017	Program Committee, AAAI Conference on Artificial Intelligence (AAAI)
2016	Neurocomputing
2016	International Journal of Advanced Robotic Systems (IJARS)
2016	Journal of Machine Learning Research (JMLR)
2016	Robotics: Science and Systems (R:SS)
2016	International Joint Conference on Artificial Intelligence (IJCAI)
2016	Neurocomputing: Special Issue on Multi-objective Reinforcement Learning
2015	Program Committee, European Workshop on Reinforcement Learning (EWRL)
2015	International Conference on Intelligent Robots and Systems (IROS)
2015	International 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.
Bib Zhang, S.; Wan, L. (2018). Enhancing Exploration through Curiosity for Robotics, Integrated Project.
Bib Ramstedt, S. (2017). Bayesian Deep Reinforcement Learning: Tools and Methods, Integrated Project.
Bib Ramstedt, S. (2016). Deep Reinforcement Learning with Continuous Actions, Bachelor Thesis.
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.