| CARVIEW |
Select Language
HTTP/2 200
server: GitHub.com
content-type: text/html; charset=utf-8
last-modified: Sun, 14 Dec 2025 19:00:36 GMT
access-control-allow-origin: *
strict-transport-security: max-age=31556952
etag: W/"693f0954-5680"
expires: Sun, 28 Dec 2025 21:17:11 GMT
cache-control: max-age=600
content-encoding: gzip
x-proxy-cache: MISS
x-github-request-id: DEF1:2D64E0:7F1BFF:8EBCAF:69519BFD
accept-ranges: bytes
age: 0
date: Sun, 28 Dec 2025 21:07:11 GMT
via: 1.1 varnish
x-served-by: cache-bom-vanm7210051-BOM
x-cache: MISS
x-cache-hits: 0
x-timer: S1766956031.260500,VS0,VE221
vary: Accept-Encoding
x-fastly-request-id: 01306b4ba094c10fe7d3869964ee07e1a348eeaa
content-length: 3573
Pietro Mazzaglia
Pietro Mazzaglia
Hi, I am Pietro Mazzaglia and I am a Senior AI Researcher at Qualcomm AI Research, Amsterdam.
The long-term goal of my research is to build embodied AI agents that discover and learn how to behave in the environment from interactions data.
About
- 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 AI Research (Amsterdam, Netherlands), Dyson Robot Learning Lab (London, UK) and ServiceNow Research (Montreal, Canada).
Research interests
Embodied AI
World Models
Multimodal Agents
Reinforcement Learning
Robotics
Active Inference
Selected publications
Here's a selection of my research contributions. For an exhaustive list, see my Google Scholar profile.
Hybrid Training for Vision-Language-Action Models
Pietro Mazzaglia, Cansu Sancaktar, Markus Peschl, Daniel Dijkman
Preprint
Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action Models
Rokas Bendikas*, Daniel Dijkman*, Markus Peschl, Sanjay Haresh, Pietro Mazzaglia
CoRL 2025
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