Rodrigo Dattari
Postdoctoral Researcher at KTH Royal Institute of Technology
Stockholm, Stockholm County, Netherlands
Summary
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Senior🎓
Top SchoolRodrigo Dattari is a postdoctoral researcher specializing in robot learning and control with roughly a decade of experience developing adaptive, safe robotic systems for unstructured environments. Trained as an electrical engineer at Universidad de Chile and holding a Ph.D. from TU Delft, he has advanced imitation-learning methods using control-theoretic priors and scaled task planning with graph-based knowledge and large language models. His applied work includes proof-of-concept deployments in greenhouse and poultry processing settings, highlighting a focus on real-world impact and human-friendly interactive learning. Rodrigo’s background in RoboCup robot soccer and hands-on hardware/software development gives him a pragmatic edge in turning research into deployable systems. Based in Stockholm, he now combines academic rigor with practical engineering to help non-experts program and safely operate robots in complex environments.
8 years of coding experience
6 years of employment as a software developer
Master of Science in Electrical Engineering, Robot Learning, Master of Science in Electrical Engineering, Robot Learning at Universidad de Chile
English, Spanish
Github Skills (30)
generalization9
q-learning8
gymnasium8
policies8
openai-gym7
reinforcement-learning7
ieee6
deep-learning6
machine-learning6
temporal6
python5
robotics5
robot4
deep-neural-networks3
openai3
Programming languages (2)
Github contributions (5)
rperezdattari/COACH-gym
May 2018 - Mar 2019
A python implementation of the COACH algorithm for the Cartpole problem in OpenAI gym.
Contributions:21 commits, 1 PR, 19 pushes in 9 months
pythonpython-implementationreinforcement-learningcartpole-problemopenai
rperezdattari/Interactive-Learning-with-Corrective-Feedback-for-Policies-based-on-Deep-Neural-Networks
Oct 2018 - Dec 2018
Code of the paper "Interactive Learning with Corrective Feedback for Policies based on Deep Neural Networks" ISER 2018.
Contributions:48 commits, 5 pushes in 1 month
generalizationdeep-learninginteractive-learningneural-networkspolicies
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