Personal information

Artificial Intelligence, Reinforcement learning, Evolution algorithms, Quality Diversity, Model Based Reinforcement Learning, Neural Networks, Robotics

Activities

Employment (5)

Huawei Technologies (France): Boulogne-Billancourt, FR

2021-12 to present | Senior Research Scientist (Noah's Ark)
Employment
Source: Self-asserted source
Giuseppe Paolo

SoftBank Robotics (France): Paris, FR

2018-10 to 2021-11 | PhD Student (Innovation)
Employment
Source: Self-asserted source
Giuseppe Paolo

IBM Research: Zurich, CH

2018-02 to 2018-08 | Research Intern
Employment
Source: Self-asserted source
Giuseppe Paolo

City University of Hong Kong: Kowloon, HK

2016-10 to 2017-01 | Research Assistant
Employment
Source: Self-asserted source
Giuseppe Paolo

Telecom Italia: Torino, IT

2015-03 to 2015-06 | Intern
Employment
Source: Self-asserted source
Giuseppe Paolo

Education and qualifications (3)

Sorbonne University: Paris, FR

2018-10 to 2021-11 | PhD (ISIR)
Education
Source: Self-asserted source
Giuseppe Paolo

ETH Zurich: Zurich, CH

2015-09 to 2017-12 | MSc. in Robotics, Systems and Control (MAVT)
Education
Source: Self-asserted source
Giuseppe Paolo

Politecnico di Torino: Torino, IT

2012-09 to 2015-07 | Bachelor degree in electronic engineering (Electronic department)
Education
Source: Self-asserted source
Giuseppe Paolo

Professional activities (2)

SIGEVO - Special Interest Group on Genetic and Evolutionary Computation: ---, FR

2021-05-01 to present
Membership
Source: Self-asserted source
Giuseppe Paolo

GECCO 2021: Lille, FR

2021-07-10 | Nominated for best paper award
Distinction
Source: Self-asserted source
Giuseppe Paolo

Works (6)

Sparse Reward Exploration via Novelty Search and Emitters

Genetic and Evolutionary Computation Conference (GECCO 21)
2021-07-05 | Conference paper
Source: Self-asserted source
Giuseppe Paolo

Novelty Search makes Evolvability Inevitable

2020-07-08 | Conference paper
Contributors: Stephane Doncieux; Giuseppe Paolo; Alban Laflaquière; Alexandre Coninx
Source: Self-asserted source
Giuseppe Paolo via HAL

Unsupervised Learning and Exploration of Reachable Outcome Space

IEEE International Conference on Robotics and Automation (ICRA)
2020-05 | Conference paper
Contributors: Giuseppe Paolo; Alban Laflaquière; Alexandre Coninx; Stephane Doncieux
Source: Self-asserted source
Giuseppe Paolo via HAL

Unsupervised Learning and Exploration of Reachable Outcome Space

2019-09-12 | Preprint
Source: Self-asserted source
Giuseppe Paolo

A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments

ICRA 2018
2017-09-25 | Conference paper
EID:

2-s2.0-85063161339

Part of ISBN:

10504729

Source: Self-asserted source
Giuseppe Paolo
grade
Preferred source (of 2)‎

Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigation

IROS 2017
2017-03-01 | Conference paper
EID:

2-s2.0-85041946430

Part of ISBN:

21530866 21530858

Source: Self-asserted source
Giuseppe Paolo
grade
Preferred source (of 2)‎