I'm Lorenzo Magnino, a researcher at University of Cambridge, supervised by Amanda Prorok.
My work now explores the intersection of Multi-Agent Robotics and Collective Intelligence. During my time at NYUShanghai I worked on Mean Field Games and Reinforcement Learning supervised by Mathieu Lauriere. I also interned at InstaDeep, working on GNNs for Multi-Agent Reinforcement Learning.
I love science, building things, playing music, and sports.
Feel free to write me on LinkedIn or connect directly by email.
Collaborated with: University of Cambridge, NYU, UCLA, Earth Science Projects, KTH Royal Institute of Technology, Georgia Institute of Technology.
Snapshots from recent Symposium on "Future of Intelligent Robotics" in Cambridge.
News
- Jan 2026: Starting as TA for Robot Mobile Systems, course taught by Amanda Prorok, Cambridge University
- Jan 2026: ProbAI Winter School. Diffusion Models and Optimal Transport
- Dec 2025: Poster presentation at NeurIPS 2025 in San Diego
- Nov 2025: Talk at Symposium "Future of Intelligent Robotics" in Cambridge
- Oct 2025: Starting as a Research Assistant at the University of Cambridge, ProrokLab
- Jul 2025: Poster presentation at ICML 2025 in Vancouver
- Mar 2025: Intern at InstaDeep (MARL and GNN for routing and scheduling in a real world challenge)
- Sep 2024: Continue as Research Assistant at NYU Shanghai w. Mathieu Lauriere
- Mar 2024: Head to NYU Shanghai as a visiting student
Featured Publications
Talks
- Prob_AI Winter School: Mathematical Foundations of Probabilistic AI Warwick University, Jan 2026
- NeurIPS 25: poster presentation San Diego, Dec 2025
- Cambridge CST Symposium: Foundation models in robotics Madingley Hall, Cambridge UK, Nov 2025
- Insta Deep AI week - Workshop: Graph Neural Network for Multi-Agent Routing Problem Berlin, Jul 2025
- ICML 25: poster presentation Vancouver, Jul 2025
- Seminar: “Latest advances in Dynamic Programming in Wasserstein spaces” with Professor M. Fischer Padova, Aug. 2023
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Research internship with Professor M. Formentin Padova, Apr. 2022 – Jul 2022
High-dimensional Probability for Statistical Learning (using Dudley's inequality and covering numbers to derive an upper bound for the excess risk in machine learning theory)
Projects
RoboML Research Template
A lightweight, opinionated template for running machine learning and robotics research projects. It provides a standardized structure for experiments, data handling, logging, and evaluation, with ready-to-use configs and scripts for reproducible workflows.
ML/Robotics Community
★ Star and clone the repo!
Protein Design RL
A toy protein design environment where agents learn to build protein sequences with target motifs and charge neutrality. Developed as personal project during my time at InstaDeep upon the paper on model-based reinforcement learning for protein backbone design.
Reinforcement Learning / Protein Design
NanoImage
A Neural Network implemented from scratch in pure Python for image classification, with no deep learning frameworks.
Neural Networks / Image Classification
GitLife
Commit to a better version of yourself.
COMING SOON....
...some interesing readings
- The Creative Act: A Way of being by Rick Rubin
- The art of doing Science and Engineering by R. Hamming
- What the Tortoise Said to Achilles by L. Carroll
- Why Greatness cannot be Planned by K. Stanley and J. Lehman