Astrophysicist | Computer Science Student | Aspiring ML Engineer
BSc in Astrophysics graduate pursuing Computer Science with a passion for applying machine learning to solve complex problems. Currently building expertise in ML/DL while working on hands-on projects to bridge theoretical knowledge with practical applications.
Just published my Medical Insurance Regression project! 📈 Predicting insurance charges with Ridge, Lasso & ElasticNet. Also completed the Supervised Machine Learning: Regression on course. Open to collaborations and opportunities in ML/AI!
Stand: 2026-02-22
- 🧠 Doing: IBM Machine Learning Professional Certificate
- 📚 Next up: Creating some ML projects
- 🛠️ Creating production-style ML & DL projects to showcase my skills and real-world problem-solving abilities.
- 💼 Open to collaborations and opportunities in ML/AI
- Merit Scholarship (Leistungsstipendium) | Computer Science, University of Vienna | 2024/25
Awarded for outstanding academic performance in first year
Computer Science (B.Sc., ongoing) | University of Vienna | 2024-present
- Interests: Machine Learning, Deep Learning, Artificial Intelligence
Astrophysics (B.Sc.) | University of Vienna | 2020-2024
- Bachelor Thesis: "Solar Rotation" - Implementation available in portfolio projects
CAD Designer | Steel Production & Casting | 2019-2020
- CAD design and construction for steel production and casting processes
- Technical drawings and 3D modeling for industrial applications
| Course / Specialization | Provider | Status | Credential |
|---|---|---|---|
| IBM Machine Learning Professional Certificate | IBM / Coursera | 🔄 In Progress | - |
| ↳ Exploratory Data Analysis for Machine Learning | IBM / Coursera | ✅ Completed | View Certificate |
| ↳ Supervised Machine Learning: Regression | IBM / Coursera | ✅ Completed | View Certificate |
| Machine Learning Specialization | DeepLearning.AI / Coursera | ✅ Completed | View Certificate |
| IBM Deep Learning with PyTorch, Keras and Tensorflow Professional Certificate | IBM / Coursera | 💭 Maybe | - |
| Coursera | 🚫 Dropped | Focus on IBM AI Engineering |
Currently learning: PyTorch, Advanced Deep Learning techniques
Bachelor Thesis Project | Astrophysics
A Python-based computer vision tool for tracking sunspots and analyzing the Sun's differential rotation using HMI continuum images from NASA's Solar Dynamics Observatory.
Key Features:
- Automated sunspot detection using adaptive thresholding and OpenCV
- Real-time tracking with interactive visualization
- Coordinate transformation from pixel to heliographic coordinates
- Differential rotation curve fitting and analysis
Tech Stack: Python OpenCV SunPy Astropy NumPy SciPy Matplotlib
🌍🧗🏼♀️ Exoplanet Explorer Database
Database Systems Project | Computer Science
A comprehensive relational database system for managing and analyzing exoplanet data from NASA's Exoplanet Archive, implementing the complete database design lifecycle.
Key Features:
- Complete ER modeling with inheritance and recursive relationships
- Normalized schema (3NF) with constraints, triggers, and views
- Automated data pipeline ingesting ~1,248 confirmed exoplanets from NASA API
- Advanced SQL techniques: composite keys, cascade rules, business logic triggers
Tech Stack: Oracle SQL Python oracledb Pandas NASA Exoplanet Archive API
| Category | Project | Description | Tech Stack | |
|---|---|---|---|---|
| AI / Intelligent Systems | 🎮 Wumpus World Agent | Knowledge-based logical agent using BFS pathfinding and inference rules to navigate a dangerous cave environment | Python AI Logic Search Algorithms |
✅ |
| ML | 📊 Student Performance EDA | Exploratory data analysis of student performance data, investigating factors affecting academic outcomes through statistical analysis and visualization | Python Pandas Matplotlib Seaborn |
✅ |
| ML | 📈 Medical Insurance Regression | Predicting medical insurance charges using multiple regression models (Linear, Ridge, Lasso, ElasticNet) with GridSearchCV hyperparameter tuning on the Kaggle Medical Cost dataset | Python Scikit-learn Pandas Seaborn |
✅ |
| ML | Image Compression using K-Means Clustering | Implemented image compression by reducing color space using k-means clustering on pixel values, demonstrating unsupervised learning for efficient image representation | Python NumPy Unsupervised Learning |
📅 |
| ML | Unsupervised Learning – Patient Data Clustering | Implementing k-means clustering to identify anomalies in patient datasets using data from the mala-lab repository | Python Unsupervised Learning |
📅 |
| 📅 Planned 🚧 In Development ✅ Finished |
More projects coming soon as I build my ML/AI portfolio!
📧 Feel free to reach out for collaborations or just to connect!
"From studying the cosmos to teaching machines to learn" ✨