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 interests
My main research interests are:
- Embodied AI
- Robotics
- World models
- Deep reinforcement learning
Research spotlight
Here's a selection of my research contributions.
For an exhaustive list, please check my Google Scholar profile.
For an exhaustive list, please check my Google Scholar profile.
Multimodal foundation world models for generalist embodied agents
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron Courville, Sai Rajeswar
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 Dhoert
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 )