Johannes Ackermann
Doctoral Student at The University of Tokyo
Chiyoda, Japan
Summary
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Senior🎓
Top SchoolJohannes Ackermann is a Ph.D. student at the University of Tokyo specializing in reinforcement learning and broader machine learning, with nine years of research and industry experience across Europe and Asia. He has contributed to high-impact applied ML projects—ranging from optical DSP research and physical-layer ML at Huawei to high-resolution image editing with diffusion models during a Preferred Networks internship. His academic work on multi-task reinforcement learning at ETH Zürich led to a publication at ECML-PKDD, reflecting strong foundations in both theory and systems. Johannes blends deep research rigor with practical engineering, having moved ideas from thesis to patents and production-focused internships. Based in Chiyoda, Tokyo, he thrives at the intersection of scalable algorithms and real-world applications, often tackling problems that require both signal-processing expertise and modern generative or RL techniques.
9 years of coding experience
University of TokyoM.Sc Electrical Engineering and Information Technology, M.Sc Electrical Engineering and Information Technology at Technical University Munich
German, English, Japanese
Github Skills (129)
python10
stylegan10
deep-learning10
autoencoder10
tensorflow10
arxiv10
machine-learning10
responsive10
generative-adversarial-network10
jekyll10
image-quality10
jekyll-theme10
markdown9
ml9
neural-network9
Programming languages (8)
Github contributions (5)
JohannesAck/MATD3implementation
Dec 2019 - Nov 2020
Contributions:3 commits, 2 pushes, 1 branch in 1 year
JohannesAck/tf2multiagentrl
Nov 2020 - Mar 2021
Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x
Contributions:17 commits, 3 PRs, 11 pushes in 3 months
autoencodermeta-learningagent2-xreinforcement-learning
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