Gido Van De Ven is an Assistant Professor and interdisciplinary researcher with nine years of experience at the intersection of machine learning, computational neuroscience, and cognitive science. He holds a PhD in Neuroscience from Oxford and advanced training in statistics and econometrics, which he leverages to develop principled, reproducible ML methods inspired by brain computation. His work spans postdoctoral and visiting roles at institutions including Baylor College of Medicine, Cambridge, KU Leuven and Delft, culminating in a faculty position in Groningen. An active open-source contributor, he implemented and improved continual learning techniques in PyTorch—adding replay mechanisms, iCaRL exemplars, A-GEM and XdG—demonstrating both theoretical and practical fluency in lifelong learning. Colleagues value his talent for bridging rigorous experimental neuroscience with scalable ML implementations that address real-world forgetting and transfer problems.
9 years of coding experience
6 years of employment as a software developer
Master's degree, Statistics, Master's degree, Statistics at University of California, Berkeley
Doctor of Philosophy - PhD, Neuroscience, Doctor of Philosophy - PhD, Neuroscience at University of Oxford
Bachelor's degree, Econometrics and Quantitative Economics, Bachelor's degree, Econometrics and Quantitative Economics at Erasmus Universiteit Rotterdam
A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).
Contributions:10 commits, 1 PR, 8 pushes in 11 months
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Gido Van De Ven - Assistant Professor at University of Groningen