ABOUT ME
I'm a machine learning researcher with a deep interest in neurotechnology. My work lies at the intersection of machine learning, signal processing, and computer vision. I’m currently pursuing an M.Sc. in Computer Science at TU Berlin, where I focus on developing real-time gait classification systems using multimodal biosignals to support adaptive deep brain stimulation in Parkinson’s Disease.
Over the past years, I’ve contributed to research on brain source imaging, neural signal analysis, and behavioral neuroscience—building tools that bridge data science with experimental neurotechnology. I have worked closely with the Quality in Artificial Intelligence Group at PTB and Charité, where I developed toolboxes for electrophysiological data analysis and contributed to many open-source projects.
As the founder of MathCodeLab, I also teach undergraduate courses in Computer Science and Mathematics, fostering an active learning community.
Feel free to check out my CV for more details.
TECHNICAL SKILLS
- Programming Languages: Python, R, Julia, MATLAB, Java, C/C++, Haskell, TypeScript
- ML Architectures & Models: DNN, CNN, RNN (LSTM); Transformers (LLMs); Generative: GANs, AEs; Reinforcement Learning
- ML Libraries & Frameworks: TensorFlow, Keras, PyTorch, scikit-learn, NumPy, pandas, SciPy, Numba, OpenCV, matplotlib, seaborn
- Applied ML Domains:NLP, Computer Vision, Time Series, Signal Processing
- Cloud & DevOps: Docker, AWS, Azure, CI/CD, RESTful APIs
- Data Engineering: SQL, ETL Pipelines, Apache Kafka, Apache Spark
- Software Development Tools: Git, GitHub, Bash, SSH, gdb, Unit Testing, API Design, Open-Source
- Markup & Scripting: LaTeX, HTML, CSS, Markdown
- Collaboration & Communication: Project Management, Scientific Writing, Teaching, Documentation