Belaynesh Mossie Kndie · Jyväskylä, Finland
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AI + Software Engineer | Brain & Data Science (MSc)

Building practical AI and software solutions especially for health & neuroscience.

Software Engineering BSc · Erasmus Mundus MSc in Brain & Data Science (University of Jyväskylä & Bar-Ilan University). Interested in applied ML, neural data analysis, BCI and building reliable systems.

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About

I combine software development with data/ML. I’ve worked as a web developer for a charity organization and as an assistant lecturer in Bahirdar University, and recently I graduated with MSc in Brain and Data sciencewith a thesis titled ML-based mental stress state classification using brain signal(MEG) and physiological(ECG) data.

JavaScript Docker Azure M/EEG Brain Imaging Backend SQL REST API PyTorch TensorFlow/Keras MNE-Python

Projects

ML based mental stress state classification (MEG + ECG)
MNE-Python · preprocessing · feature extraction
ML pipeline on noisy time-series data; focus on robust validation and error analysis.
Website development & Maintenance
php · mySQL
Developed and maintained an organizational website for a non profit organization
Eye health referral linkeage system
Node.js · Express · Vue.js · PostgreSQL
Built a patient referral tracking system to record, monitor, and manage eye health referrals and follow ups. Implemented backend API endpoints and a frontend workflow for entering and reviewing referral data.
Yegna Gebeya Online Shopping Platform
C# · ASP.NET Core · Web application · MySQl
Developed an online shopping platform implementing product management, user interaction, and backend business logic using ASP.NET Core.
AI-Powered CV Analysis Assistant
Developed an AI-powered application for CV analysis and personalized feedback integrating Hugging Face inference APIs and prompt-based workflows for intelligent document evaluation.
Predicting Reading Time from Textual Representations
Python · NLP · scikit-learn · Transformers · Eye-tracking Analysis
Investigated whether sentence-level reading time can be predicted from text using the ZuCo eye-tracking corpus. Compared structural linguistic features, TF-IDF representations, and BERT embeddings using Ridge regression and cross-validation to study the relationship between linguistic structure and human reading behavior.

Skills

  • Python, C++, Java, JavaScript, SQL
  • ML, Deep Learning, NLP, MLoPs
  • Frameworks and tools: scikit-learn, TensorFlow/PyTorch, MNE-Python, Docker, Azure, Linux, Git
  • APIs & Backend fundamentals

What I’m looking for

  • AI, Data Science and Software Development roles
  • Research oriented roles related to AI and neuroscience
  • Applied ML, Health-tech, and data-driven projects

Contact

Email: tslatebely@gmail.com
Mobile: +358466347802
Location: Jyväskylä, Finland
Languages: English (professional working proficiency), Amharic (native), Hebrew(lower Intermediate), Finnish (basic)