Hi, I am Pietro Mazzaglia and I am a Senior Machine Learning Researcher at Qualcomm Research
Netherlands, in Amsterdam.
The long-term goal of my research is to build embodied AI agents that discover and learn how to
behave in the environment by interacting with it.
About
Personal background
- I grew up in Catania, a sunny city next to a volcano in the east coast of Sicily, Italy.
- During my bachelor, I lived and studied at the superior graduate institute Scuola Superiore di Catania, where I was a scholar while attending the BSc Computer Engineering course at the University of Catania.
- For my master degree, I moved to Manchester, UK, where I studied Artificial Intelligence at The University of Manchester.
- I did my PhD at Ghent University, Belgium, supervised by Prof. Bart Dhoedt and Dr. Tim Verbelen. During my PhD, I also interned at Qualcomm Research (Amsterdam, Netherlands), Dyson Robot Learning Lab (London, UK) and ServiceNow Research (Montreal, Canada).
Research spotlight
My main research interests are:
- Embodied AI
- Robotics
- World models
- Deep reinforcement learning
GenRL: Multimodal-foundation world models for generalization in embodied agents
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron Courville, Sai Rajeswar
NeurIPS 2024
MFM-EAI workshop @ ICML 2024
Information-driven Affordance Discovery for Efficient Robotic Manipulation
Pietro Mazzaglia, Taco Cohen, Daniel Dijkman
ICRA 2024
GMPL workshop @ RSS 2023
Redundancy-aware Action Spaces for Robot Learning
Pietro Mazzaglia,* Nicholas Backshall,* Xiao Ma, Stephen James
Robotics and Automation Letters (RA-L) 2024
FOCUS: Object-Centric World Models for Robotics Manipulation
Stefano Ferraro*, Pietro Mazzaglia*, Tim Verbelen, Bart Dhoedt
Robot Representations workshop @ RSS 2023 (best paper)
GMPL workshop @ RSS 2023
Choreographer: Learning and Adapting Skills in Imagination
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar
ICLR 2023 (top-25%, spotlight)
Offline RL workshop @ ICML 2022 (oral)
Deep RL workshop @ ICML 2022
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
Sai Rajeswar*, Pietro Mazzaglia*, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron Courville, Alexandre Lacoste
ICML 2023 (oral)
DARL workshop @ ICML 2022
Curiosity-Driven Exploration via Latent Bayesian Surprise
Pietro Mazzaglia, Ozan Çatal, Tim Verbelen, Bart Dhoedt
AAAI 2022 (oral)
SSL-RL workshop @ ICLR 2021
Contrastive Active Inference
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt
NeurIPS 2021
The Free Energy Principle for Perception and Action: A Deep Learning Perspective
Pietro Mazzaglia, Tim Verbelen, Ozan Çatal, Bart Dhoedt
Entropy 2022 (best paper award)