Hello, I'm Gabriele Giudici, a robotics researcher passionate about pushing the boundaries of human-robot interaction. Born during a vibrant Italian summer in the 1990s in Rimini (IT), I grew up captivated by art, philosophy, and the essence of life itself. Over time, I came to realize that the greatest artists and philosophers were, in fact, scientists themselves.—pioneers who blend creativity with logic to explore the unknown.
This led me to Politecnico di Milano, where I pursued Computer Engineering (BSc) and Automation Control Engineering (MSc). It was there, studying in Piazza Leonardo da Vinci, that I found my true calling: developing the next generation of humanoid robots - the modern Vitruvian Man.
My research journey began at the Scuola Superiore Sant'Anna in Pisa, where I applied human-inspired control techniques to humanoid robots. It then led me to Queen Mary University of London, where I advanced teleoperation systems through exoskeletons and haptic sensors. My work there focused on exploring the dynamics of haptic data and pushing the boundaries of learning from human demonstrations.
Driven by curiosity and a love for challenges, my motto reflects my curiosity for exploration and research as a life purpose.: "There's a secret mission in uncharted space. Let's go!"
Triviality and routine drain me, but the pursuit of the seemingly impossible ignites my passion. If you're looking for a collaborator who combines technical expertise with creative vision—someone ready for the next big adventure—you can count on me.
Reasearch Workshop Organizer [ACTIVE]
IROS 2025 : Robot Learning From Human Teleoperation: Prospects and Challenges
Lead organizer of a IROS 2025 workshop connecting top researchers and industry leaders (Google DeepMind, Unitree Robotics, Shadow Robot Company, University of Texas at Austin, KIT, IIT) to advance imitation learning and teleoperation in robotics, featuring keynotes and interactive sessions on data collection, standardization, and tactile sensing.
https://sites.google.com/view/lfht-iros25-workshop-proposal/home
ICRA 2026 : Robot Learning from Human Teleoperation: Scaling Demonstrations and Leveraging Foundation Models
Co-Lead organizer of a ICRA 2026 workshop connecting experts from top universities and companies (Stanford, KIT, DLR, Czech Technical University, mimic robotics AG) to advance robot learning from teleoperation and video demonstrations, featuring keynotes and interactive sessions on large model adaptation, multimodal sensing, and dataset design. [Work In Progress: Submitted ICRA 26]
https://sites.google.com/view/lfht-icra26-workshop/home
UCL - University College of London [ACTIVE]
Senior Research Fellow in Robotics and AI | March 2025 - Ongoing:
MagTecSkin Project: Develop an innovative robotic skin that gives robots a sense of touch using magnetic technology. It can detect contact forces at multiple points while remaining flexible enough to bend and stretch. This breakthrough will enable to fully cover articulated and soft robots with the skin, to give them an enhanced sense of touch which enables higher dexterity in tasks within manufacturing, logistics, agri-food, and healthcare.
AI for Dexterous Manipulation and Control: Imitation learning, learning from human demonstrations, teleoperations, VLMs and tactile sensing.
MSc and PhD students supervision
Queen Mary University of London
Research Assistant | October 2024- April 2025:
Anastomosis Project : Study, evaluation and design of robotics solutions for minimally invasive surgery.
PhD Candidate, Computer Science | July 2021 - January 2025
Developed haptic telerobotics setup
Segmentation, Classification and Imitation Learning for Long-Horizon Tasks
Autonomous Control via Machine Learning and AI
Designed 3D-printed soft magnetic tactile sensors for a robotic hand
Published papers and presented at international conferences.
Teaching Lab Demonstrator | July 2021 - January 2025
Advanced Robotics
Cognitive Robotics
Computer Programming C,
Computer Programming python
Electronic Sensing
Mechatronics
Digital Electronics and Computer Systems
The BioRobotics Institute, Scuola Superiore Sant’Anna
Research Assistant, Pontedera (PI) | April 2019 - July 2021
Collaborated on the 'Human Brain Project' to simulate the human brain using supercomputers (SNN).
Developed neuro controllers (NARX, LSTM) for humanoid robots including iCub's arm and musculo-skeletal models.
Servotecnica S.p.A.
Internship, Milano (MI) | September 2018 - March 2019
Developed a controller for a linear tubular motor and PI driver autotuning logic.
LibraWay S.p.A.
Tech Advisor, Milano (MI) | August 2017 - June 2018
Developed business strategies, SWOT analysis, and financial strategies for LibraWay Mobile App https://libraway.com/
Degrees:
PhD in Computer Science, Robotics and AI - ARQ: (Advanced Robotics @ Queen Mary University of London), 2025
M.Sc in Automation and Control Engineering - Politecnico di Milano, 2020
B.Sc in Engineering of Computer Systems - Politecnico di Milano, 2017
Certificates:
Probability & Statistics for Machine Learning & Data Science - DeepLearning.AI, Stanford Online, 2024
Machine Learning Specialization - DeepLearning.AI, Stanford Online, 2024
Supervised Machine Learning: Regression and Classification
Unsupervised Learning, Recommenders, Reinforcement Learning
Advanced Learning Algorithms
Applied Machine Learning - LinkedIn Learning 2023
Machine Learning with Python: Foundations - LinkedIn Learning 2023
AI Software: Cursor, Gemini AI Studio, Perplexity, Midjourney
Programming Languages: Python, C, C++, Java, ROS, YARP, Assembler, SFC, Ladder Diagram, Html5, CSS3
Database Management : SQL, MySQL
Computing Environments: Matlab, Simulink, OpenModelica, Maxima, Scilab.
Simulators: Gazebo, CATIA V5, SOFA
Operating Systems: Linux, Windows, macOS,
Other Tools: Microsoft Office, Adobe Photoshop, Inkscape, Autodesk Fusion 360, Cura
Hardware: Microelectronic soldering, 3D printing and chemical material processing (silicone)
App Development: Google Sites, Google Script
Humanoid Robots
Telerobotics Manipulation
Autonomous Systems
AI & Bio-Inspired Control
Neural Networks
Machine Learning
FinTech
Football Performance Algorithmic Analysis
Business Strategy and Startup
BioTech, MedTech and FoodTech
Created a personal optimization tool for fantasy football, automating player selection and lineup decisions using custom algorithms for improved team performance. Designed for practical use and fun, the project applies advanced optimization methods tailored to the rules and scoring of the fantasy football game.
Currently developing features for scraping and analyzing the last 5 years of Serie A player performances, with planned simulation of 10,000 possible next-season outcomes for more reliable, data-driven predictions.
https://script.google.com/macros/s/AKfycbxbHynJEcs674WmRV0QegPBgSFKOg7Ql0jbaJCFgr3-Xl69opjYmCAOhBajTuU6O0br/exec
TRY IT
Usr: gabriele_giudici
Psw: fanta25