Computer Science @ University of Vienna Β· AI / Quantum Computing / Software Engineering / Scientific Computing
Building toward a long-term goal: applying my skills in ML/AI, Quantum Computing, Scientific Computing, and Software Engineering to humanity's hardest problems - one project, one job, one paper at a time. Working through both academic research and entrepreneurial ventures, with the patience to build real depth before reaching for scale.
- π B.Sc. Computer Science student at the University of Vienna (ranked 1st in Austria, Top 100 globally - EduRank 2026)
- π§ Former GenAI Software Development Intern at IBM π built RAG evaluation frameworks & code analysis tools
- βοΈ Former Software Development Intern at Bosch π ML, data cleaning, tool migration
- βοΈ Quantum Computing Research Intern at QWorld π quantum image encoding (QPIE, FRQI), Quantum Harris Corner Detection
- π 3rd Place & Google DeepMind Special Recognition π AI Agent Olympics Hackathon, Milan AI Week 2026
- πΉπ· TEKNOFEST Top 20 β Turkish NLP Scenario Category
- π΄ What am I doing nowadays ?
- π exploring multi-agent AI systems,
- π investigating the potential of physical AI at the software layer,
- π evaluating the promisingness of Neurosymbolic AI
- π working on Scienticome
Languages
AI / ML / Quantum
Web & Tools
| Project | Description |
|---|---|
| OmniSynth π | Full-stack multi-agent AI research platform turning collections of papers into an interactive knowledge workspace (concept graphs, per-paper wikis, gap analysis, hypotheses). 3rd Place & Google DeepMind Special Recognition at AI Agent Olympics Hackathon, Milan AI Week 2026. |
| RAGnosis | A synthetic-data-powered testing & evaluation framework for RAG systems, built with Langfuse, WatsonX, Ragas, Streamlit, and FastAPI. Built during IBM internship. |
| Quantum Harris Corner Detection | Quantum realization of Harris/Sobel-based corner & edge detection using FRQI and QPIE image encoding in Qiskit, with classical post-processing. |
| Agentic Turkish LLM (TEKNOFEST) | Multi-agent sentiment analysis system combining a fine-tuned Mistral-7B classifier with a LLaMA 3.1 8B orchestrator, trained on TΓBΔ°TAK HPC resources. |
| Hello HPC | Beginner-friendly tutorial and toolkit bridging classical HPC and quantum workflows, using the Qiskit 2.3 C API, Slurm, and OpenMP. |
π More projects on my portfolio site
- Qiskit Global Summer School 2025 β Quantum Excellence
- IBM watsonx.ai Technical Essentials Β· 2025 IBMer watsonx Challenge
- MIT iQuHack 2025
- DeepLearning.AI TensorFlow Developer Specialization (4 courses)