Dr. Gabriele Giudici

About Me

Professional Experience

Education

Areas of Expertise

Latest Publications:

Other Publications:

About Me

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.

Professional Experience

UCL - University College of London

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.

Queen Mary University of London

Research Assistant | October 2024- Ongoing:

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/

Education

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

Areas of Expertise

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
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)