Available for Internships & Projects

Ultrich
Edima Edima.

Master's student in Computer Science at Humboldt-Universität Berlin — building at the intersection of education technology, applied AI, and thoughtful software engineering.

M.Sc
Computer Science — HU Berlin
1.7
Bachelor thesis grade
3+
Languages spoken
🇩🇪 🇫🇷 🇬🇧
Trilingual DE · FR · EN

Building with purpose,
learning without limits.

I'm a Master's student in Computer Science at the Institut für Informatik, Humboldt-Universität zu Berlin. My academic work covers software engineering, plugin development for education platforms, and data annotation research.

I've built tools that help students get automated feedback in digital workbooks, explored AI-powered SaaS products, and worked with multilingual text data — always with a focus on things that are actually useful for real people.

I grew up across Cameroon, France, and Germany — three countries, three languages, and a natural curiosity for the spaces between cultures and systems. That background shapes how I think about software: inclusive, pragmatic, and always asking who it's really for.

Currently

Degree M.Sc. Computer Science
University HU Berlin
Based in Berlin 🇩🇪
Open to Internships · Projects

Roots

🇨🇲 Cameroon Origin
🇫🇷 France Education
🇩🇪 Germany University & Life

Beyond Code

🏎️ Karting in Berlin
✈️ Travel & food
📚 Building SaaS ideas

Selected projects.

All repos on GitHub →
📘
Bachelor Thesis · 2024
Auto-Grading Plugin
A plugin for digital workbooks that automatically evaluates student submissions. Configurable grading logic integrated directly into LMS infrastructure, developed at HU Berlin.
Bachelor Thesis Java EdTech LMS HU Berlin
🍽️
SaaS Concept · 2024
MenuCraft
AI-powered multilingual menu generator for restaurants, with EU allergen compliance built in. Designed as a SaaS MVP for small European restaurants — three languages, zero extra work.
SaaS AI / LLM Multilingual GitHub Spark
🔬
Research · 2024
Ad Comment Annotator
Data annotation framework for evaluating Facebook ad comments across 7 quality criteria — informativeness, relevance, sentiment, civility, and more. Reached 84–87% accuracy.
NLP Python Data Annotation Research
Bachelor Thesis

Academic highlight.

B.Sc. Computer Science — Humboldt-Universität zu Berlin
Entwicklung eines Plugins zur automatischen Bewertung von Lernendenabgaben in digitalen Workbooks
University Humboldt-Universität zu Berlin — Institut für Informatik
Supervised by Dr. André Greubel · Prof. Dr. Lars Grunske
Topic area Education Technology · Plugin Systems · LMS

Developed a plugin architecture for digital workbooks enabling automated, configurable grading of student submissions. The work addresses the challenge of scaling individualized feedback in digital learning environments, integrating grading logic into existing LMS infrastructure without disrupting the educator workflow.

✦ Final Grade: 1.7  ·  Gut
Technical Stack

What I work with.

Languages

Python
Java
JavaScript
HTML / CSS
LaTeX

Tools & Frameworks

Git / GitHub
PyMuPDF · ReportLab
GitHub Spark
Vercel
VS Code

Areas of Interest

Education Technology
Plugin Development
NLP · Data Annotation
SaaS Prototyping
AI Fine-tuning

Languages Spoken

🇩🇪 Deutsch — Fließend
🇫🇷 Français — Langue maternelle
🇬🇧 English — Fluent

Let's build
something.

Whether you have a project idea, an internship offer, or just want to say hi — I'm happy to hear from you. Reach out in German, French, or English.