Jenia Jitsev is a computational neuroscientist and deep learning leader with 10+ years of experience translating brain-inspired plasticity and continual learning principles into large-scale AI systems. As co-founder of LAION e.V. and Ontocord.AI and head of the SLAMPAI lab at Jülich Supercomputing Center, he focuses on open foundation models, data-centric scaling laws, synthetic-data generation, and multi-modal continual learning. His career bridges rigorous neuroscience research—spanning cortico-basal ganglia plasticity and hierarchical recurrent networks—with practical engineering of distributed training on thousands of GPUs. Known for pursuing self-regulated, energy-efficient learning and meta-learning approaches, he blends basic science with open-source datasets and pretraining initiatives to accelerate reproducible AI. Based in the Cologne–Bonn region, he pairs deep academic roots (PhD in computational neuroscience) with entrepreneurial impact in the open-AI ecosystem.
11 years of coding experience
10 years of employment as a software developer
Dr. phil. nat. (PhD) Informatik (Computational Neuroscience, Dr. phil. nat. (PhD) Informatik (Computational Neuroscience at Goethe University Frankfurt
Diplom Informatik (Nebenfach Psychologie), Diplom Informatik (Nebenfach Psychologie) at The University of Bonn
Code for reproducing the experiments on large-scale pre-training and transfer learning for the paper "Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images" (https://arxiv.org/abs/2106.00116)
Contributions:3 commits, 2 pushes, 1 branch in 11 months
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