Reposted by David LeeftinkNico Bohlinger @nicobohlinger.bsky.social · 01/10/2026⚡ One policy, millions of embodiments, over 200 robot models. Can we add yours? We're building γ₀, a generalist RL policy for motion control trained across millions of randomized embodiments derived from a growing collection of more than 200 robot models. 192
Reposted by David LeeftinkMax Hinne @maxhinne.bsky.social · 29/09/2026Bayesian analyses are great, but making the right model is very challenging. Come work with me on implementing efficient Bayesian multiverses, where we help researchers across empirical domains to improve their models! More information on the Radboud University website: www.ru.nl/en/working-a...ru.nlResearch Assistant at the Donders Centre for Cognition: Computational Modelling and Scientific Software | Radboud UniversityDo you want to work as a Research Assistant at the Donders Centre for Cognition: Computational Modelling and Scientific Software? Check our vacancy! 074
Reposted by David LeeftinkKai Ploeger @kaiploeger.bsky.social · 24/06/2026Learning five-ball juggling on the second attempt, with two Barrett WAMs. Most humans take years of practice. Paper and videos: kai-ploeger.com/residual-juggling #robotics #juggling 145
Reposted by David Leeftinkmarcelvangerven.bsky.social @marcelvangerven.bsky.social · 08/05/2026Proud to share a new pre-print by @davidleeftink.bsky.social and with @maxhinne.bsky.social. We make a formal connection between the Pontryagin minimum principle and deep recurrent reinforcement learning, improving performance on challenging control tasks! arxiv.org/pdf/2605.05373 041
David Leeftink @davidleeftink.bsky.social · 31/03/2026#BayesianOptimization #SemiconductorManufacturing #ProcessOptimization #MachineLearning #IndustrialAutomation 000
David Leeftink @davidleeftink.bsky.social · 31/03/2026Evaluated on industrial-quality wafers, BOLD autonomously discovers high-quality production-ready process configurations under limited measurements. The configurations yield expert-level mechanical die strength and improve production throughput by up to 34% via human-in-the-loop refinement. 100
David Leeftink @davidleeftink.bsky.social · 31/03/2026We developed 𝗕𝗢𝗟𝗗 (Bayesian Optimization for Laser Dicing), the first scalable automation method for laser processes, which bridges complex physical manufacturing with probabilistic machine learning. 110
David Leeftink @davidleeftink.bsky.social · 31/03/2026Adapting multi-pass laser dicing to new, multi-layered semiconductor wafers is a notoriously challenging problem. No scalable automation methods exist today, so parameter optimization relies on human experts, typically requiring weeks of costly manual tuning. 100
David Leeftink @davidleeftink.bsky.social · 31/03/2026Our latest paper, just accepted in the IFAC journal Control Engineering Practice (Special Issue on Bayesian Optimization), explores exactly this: 📄 Full paper (open access): www.sciencedirect.com/science/arti...lnkd.inLinkedInThis link will take you to a page that’s not on LinkedIn 110
David Leeftink @davidleeftink.bsky.social · 31/03/2026How can Bayesian optimization enable the discovery of complex laser processes in semiconductor manufacturing? 100
Reposted by David LeeftinkClément Canonne @ccanonne.github.io · 06/03/2026Leibniz, looking at the universe: "Why is there something instead of nothing?" Me, looking at my Outlook calendar: same 210117
Reposted by David LeeftinkChristian Wolf @chriswolfvision.bsky.social · 05/03/2026It's time for this picture again ... #ECCV2026 2343
Reposted by David LeeftinkMax Hinne @maxhinne.bsky.social · 01/12/2025Proud to share a new pre-print by @davidleeftink.bsky.social and with @marcelvangerven.bsky.social on Bayesian optimization for automatic laser dicing in semiconductor manufacturing! arxiv.org/abs/2511.23141 012
Reposted by David LeeftinkMatti Vuorre @matti.vuorre.com · 14/10/2025Against Publishing: universonline.nl/nieuws/2025/... Preprints are read, shared, and cited, yet still dismissed as incomplete until blessed by a publisher. I argue that the true measure of scholarship lies in open exchange, not in the industry’s gatekeeping of what counts as published. 612046
David Leeftink @davidleeftink.bsky.social · 03/10/2025I'd say yes! It allows new ideas to distribute faster, while remaining clear that it is not a reviewed article 020
David Leeftink @davidleeftink.bsky.social · 03/09/2025📄 Read the full paper: arxiv.org/abs/2504.02543 💻 Code available on GitHub: github.com/DavidLeeftin... A huge thank you to everyone who contributed to this work! #CDC2025 #ReinforcementLearning #OptimalControl #MachineLearningarxiv.orgOptimal Control of Probabilistic Dynamics Models via Mean Hamiltonian MinimizationWithout exact knowledge of the true system dynamics, optimal control of non-linear continuous-time systems requires careful treatment under epistemic uncertainty. In this work, we translate a probabil... 030
David Leeftink @davidleeftink.bsky.social · 03/09/2025Our recent paper “Optimal Control of Probabilistic Dynamics Models via Mean Hamiltonian Minimization,” has been accepted to CDC 2025! We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty. 181