Maximilian Beck
PHD Researcher at Johannes Kepler Universität Linz
Karlsruhe, Baden-Württemberg, Germany
Summary
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Rockstar🎓
Top SchoolMaximilian Beck is a PhD researcher and research associate at Johannes Kepler University Linz, supervised by Sepp Hochreiter, building RNN-inspired, sub-quadratic Large Language Models that rethink transformer efficiency. With five years of research experience spanning academic labs and industry internships at Meta, he has worked on long-context architectures, code world models, and neural debuggers—publishing and evaluating novel approaches to code execution prediction. His background in mechatronics and hands-on systems work (from PLC programming to C++ computational geometry) gives him uncommon practical rigor when designing scalable ML models. Based in Paris and active in the ELLIS community, he combines theoretical innovation with applied engineering to push NLP performance under tight computational budgets.
5 years of coding experience
3 years of employment as a software developer
San José State UniversityMaster of Science - MS, Mechatronics and Information Technology, Master of Science - MS, Mechatronics and Information Technology at Karlsruhe Institute of Technology (KIT)
Github Skills (13)
llm9
machine-learning9
nlp9
deep-learning9
adaptation3
system-identification2
gaussian-processes2
recurrent2
transfer-learning2
dynamical-systems2
recurrent-neural-networks2
fairness-ml1
ensemble-learning1
Programming languages (3)
Github contributions (5)
NX-AI/mlstm_kernels
Dec 2024 - Mar 2025
A library for fast and efficient mLSTM Kernels.
Contributions:3 reviews, 1 PR, 7 pushes in 3 months
maximilianmbeck/RWKV-LM
Mar 2023 - Apr 2023
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
Contributions:15 pushes, 1 branch in 13 days
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