Bernhard Specht

Bernhard Specht

Research Engineer

I turn hard problems into shipped products. From brain-computer interfaces to privacy-preserving ML systems and beyond — I research, build, and deliver end-to-end.

Projects

University BCI Projects

Technical University of Munich

Brain-computer interface projects from my time as a teaching assistant and working student.

PrivateBoost

Ph.D. Research

A privacy-preserving federated learning system for cross-device medical data. Raw medical data never leaves patients' mobile devices — the system uses secret sharing to enable collaborative model training without exposing individual records.

Scavenger & Nogrod

Open Source — 2018

Energy-efficient cryptocurrency miner based on proof of capacity with GPU acceleration, adopted by multiple cryptocurrencies. Nogrod validates miners' proofs and distributes rewards based on estimated disk capacity.

Education

Industrial Ph.D. — Brain-Computer Interfaces for Remote Neurological Monitoring

Myelin-H, University of Luxembourg & Luxembourg Institute of Science and Technology (LIST)
Mar 2023 – Present · Luxembourg
  • Funded by the Luxembourg National Research Fund (FNR)
  • Built a hybrid brain-computer interface for remote neurological monitoring and rehabilitation using multi-modal sensor data
  • Developed a privacy-preserving federated learning system where raw medical data never leaves patients' mobile devices

B.Sc. & M.Sc. Electrical Engineering and Information Technology

Technical University of Munich
Oct 2013 – Oct 2020 · Munich, Germany
  • M.Sc. focused on Neural Engineering, machine learning, and brain-computer interfaces
  • Master thesis with exchange at Dalian Ligong University (Dalian, China): Joint Optimization of Haptic Communication and Resource Allocation

Chinese Language Studies and Exchange — HSK6

Tongji University (Shanghai) & Nanjing University (Confucius Institute Scholarship)
Sep 2012 – Oct 2013, Sep 2017 – Jun 2018 · China

Publications

Multiple Sclerosis in the Digital Health Age: Challenges and Opportunities — A Systematic Review
medRxiv, 2023 first author
medRxiv, 2026 · Journal submission in preparation first author
Predicting Depression and Anxiety Progression in Multiple Sclerosis from Longitudinal Clinical Data Using Machine Learning
In preparation first author

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