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Gabriele Tiboni

PostDoc & Research Scientist working on Physical AI
(Robotics, Reinforcement Learning, Computer Vision, 3D Learning).
Currently building new things.

News

May 2026 In stealth, building new things in the space of Physical AI, starting with intelligent industrial automation.
Apr 2026 MaskPlanner has been accepted at IEEE Transactions on Robotics (T-RO)! With this, we introduce an important milestone to study "Object-Centric Motion Generation" and hope to pave the way for future applications in industry and beyond.
Mar 2026 I launched Paperedge.ai, a free and collaborative reference manager for researchers. Already used by researchers from 50+ institutions worldwide!
Feb 2026 I joined Neuracore as a Research Scientist to help build the infrastructure layer for Physical AI.
Sep 2025 Our RemembeRL Workshop @ CoRL 2025 was an absolute success! Check out the uploaded recordings at rememberl-corl25.github.io in case you missed it.
Sep 2025 I successfully defended my PhD thesis! Huge thanks to all those who were part of my PhD journey throughout the years. My Thesis on "Scalable and Generalizable Robot Learning" is available here.
Jun 2025 Our RemembeRL Workshop @ CoRL 2025 has been accepted. We're looking forward to investigating the intersection of in-context learning and transductive inference for applications in robotics.
Nov 2024 I moved to Germany! I joined the LiteRL and Pearl labs as a Post Doctoral researcher, supervised by Prof. Carlo D'Eramo and Prof. Georgia Chalvatzaki.
Jan 2024 Our paper "Domain Randomization via Entropy Maximization" (DORAEMON) has been accepted at ICLR 2024! We recommend you give it a read if you're interested in sim-to-real transfer of RL policies.
Oct 2023 I presented two works as a first author at this year's IROS 2023! Check out (1) paper #1 on Robotic Spray Painting and (2) paper #2 on Domain Randomization for Soft Robots.
Jun 2023 I attended the Reinforcement Learning Summer School (RLSS 2023) in Barcellona, and won the social beach volley tournament event!
May 2023 Our paper "DROPO: Sim-to-Real Transfer with Offline Domain Randomization" has been accepted in Robotics and Autonomous Systems Journal.
Feb 2023 Ellis PhD visiting at TU-Darmstadt for 9 months, under the co-supervision of Prof. Jan Peters, Prof. Georgia Chalvatzaki and Prof. Carlo d'Eramo.
Nov 2022 I attended the National PhD-AI Fall School, discussing topics such as Federated Learning, Domain Adaptation, and Kernel Methods by Prof. Lorenzo Rosasco.
Sep 2022 Our paper "Online vs. Offline Adaptive Domain Randomization Benchmark" will be published in the Springer Proceedings in Advanced Robotics 2023.
Jul 2022 I attended the International Computer Vision Summer School (ICVSS 2022) and won the Reading Group Competition led by Prof. Stefano Soatto.

About

Hi there! My name is Gabriele.

Currently building new things
In stealth to build physical AI solutions, starting with intelligent industrial automation.
Launched Paperedge.ai
March 2026
Free, collaborative reference manager for researchers, an AI-powered alternative to Zotero. Researchers from 50+ institutions worldwide.
Research Scientist — Neuracore
London, United Kingdom  ·  Jan–Apr 2026
Building the infrastructure layer for Physical AI.
PostDoc
JMU Würzburg  ·  TU Darmstadt  ·  Nov 2024–Dec 2025
Supervised by Prof. Carlo D'Eramo and Prof. Georgia Chalvatzaki.
PhD
Politecnico di Torino  ·  TU Darmstadt  ·  Nov 2021–Oct 2024
B.Eng + M.Sc — Polytechnic of Turin & Aalto University
Turin, Italy  ·  Espoo, Finland

Publications

new MaskPlanner: a Framework for 3D Learning-Based Object-Centric Motion Generation and Applications to Robotic Spray Painting Gabriele Tiboni, Raffaello Camoriano, Tatiana Tommasi IEEE Transactions on Robotics (T-RO), 2026 Paper/ Code/ Website new Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning Rickmer Krohn, Vignesh Prasad, Gabriele Tiboni, Georgia Chalvatzaki IEEE Robotics and Automation Letters 11 (6), 6799-6806 Paper/ Website K-Level Policy Gradients for Multi-Agent Reinforcement Learning Aryaman Reddi, Gabriele Tiboni, Jan Peters, Carlo D'Eramo Preprint Paper Shaping Laser Pulses with Reinforcement Learning Francesco Capuano, Davorin Peceli, Gabriele Tiboni Reinforcement Learning Conference (RLC) Paper FoldPath: End-to-End Object-Centric Motion Generation via Modulated Implicit Paths Paolo Rabino, Gabriele Tiboni, Tatiana Tommasi 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Domain Randomization via Entropy Maximization Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki International Conference on Learning Representations (ICLR) Paper/ Code/ Website DROPO: Sim-to-Real Transfer with Offline Domain Randomization Gabriele Tiboni, Karol Arndt, Ville Kyrki Robotics and Autonomous Systems, 104432 Paper/ Code/ Website Domain Randomization for Robust, Affordable and Effective Closed-loop Control of Soft Robots Gabriele Tiboni, Andrea Protopapa, Tatiana Tommasi, Giuseppe Averta 2023 IEEE/RSJ international conference on intelligent robots and systems (IROS) Paper/ Code/ Website PaintNet: Unstructured Multi-Path Learning from 3D Point Clouds for Robotic Spray Painting Gabriele Tiboni, Raffaello Camoriano, Tatiana Tommasi 2023 IEEE/RSJ international conference on intelligent robots and systems (IROS) Paper/ Code/ Website Online vs. Offline Adaptive Domain Randomization Benchmark Gabriele Tiboni, Karol Arndt, Giuseppe Averta, Ville Kyrki, Tatiana Tommasi Springer Proceedings in Advanced Robotics (SPAR), 2023 Paper/ Code/ Website Towards Safe and Efficient Transfer of Robot Policies from Simulation to Real World Gabriele Tiboni, Karol Arndt, Ville Kyrki, Barbara Caputo M.Sc. Thesis, 2021 Thesis

Recordings

RL course project presentation

March 11th, 2024 ・ 11 mins

Presentation of the RL project to the students of the course of "Machine Learning and Deep Learning" at Politecnico di Torino.

Intro to RL for Supervised Learners (Seminar)

July 27th, 2023 ・ 38 mins

A high-level introduction to Reinforcement Learning concepts tailored to an audience familiar with supervised learning. Recording of weekly seminar at Polytechnic of Turin.

Practical session on Policy Gradient (Reinforcement Learning course @ TU Darmstadt)

June 22, 2023 ・ 1 hour 13 mins

Recording of practical session on Policy Gradient (PG) for students of the Reinforcement Learning course @ TU Darmstadt. Derivations of the policy gradient and the optimal baseline are shown, together with practical examples for running PG algorithms with Mushroom RL library.

Ellis PhD Student Gabriele Tiboni

November 2021 ・ 1 min

Introduction to the Ellis PhD & Postdoc program during my PhD.