Academic Journey at TUM
Currently pursuing a Bachelor of Science in Informatics at the Technical University of Munich (TUM), one of Germany's leading technical universities. My studies focus on building a solid foundation in computer science fundamentals while preparing for specialization in artificial intelligence.
Now entering my 5th semester in October 2025, I'm ahead of the typical schedule with more credits than planned completed and maintaining exceptional academic performance throughout my studies.
Studying at TUM means being part of a university recognized worldwide: ranked 22nd globally by QS and the best university in the EU, #1 in innovation and entrepreneurship (THE Impact Ranking), and consistently producing more start-up founders than any other German university. This environment combines cutting-edge research, industry collaboration, and strong entrepreneurial culture, providing an unmatched foundation for future innovators.
Academic Excellence
Throughout my academic journey, I have demonstrated a dedication to mastering complex computer science concepts, consistently achieving high standards in my coursework and projects.
1.6 GPA Achievement
Maintaining an excellent 1.6 GPA (German scale), demonstrating consistent high performance across all modules
134 Credits Completed
Ahead of schedule with 134 credits earned (while the standard schedule foresees 120), progressing efficiently through the comprehensive curriculum
Top 8% Performer
Recognized for academic excellence, ranking in the top 8% of my cohort at TUM
Core Competencies
My education has been built on the essential pillars of computer science, providing me with a comprehensive understanding of both foundational and advanced topics.
Software Engineering
Achieved a perfect 1.0 grade in Software Engineering and IT Security, mastering design patterns, software architecture, and modern development methodologies while ensuring robust and secure solutions.
System Foundations
In-depth study of computer architecture, programming languages, and databases (1.0) as well as operating systems (1.0) form the core of my system knowledge.
Theoretical Computer Science
Extensive coursework covering algorithms (1.0) and mathematical concepts underpins my analytical skills.
Specialization Path
I specialize in Machine Learning at the intersection of Software Engineering and AI systems.
I plan to pursue a Master's degree with focus on AI, where I can deepen my understanding of machine learning algorithms, neural networks, and their practical applications in software systems.
Practical Application
Beyond theoretical knowledge, my studies emphasize hands-on experience through practical courses, laboratory work, and project-based learning that bridges academic concepts with real-world applications.
Real-World Projects
Built projects that apply theoretical knowledge to real-world challenges and measurable outcomes.
Collaborative Delivery
Partnered with cross-functional teams to design and implement production-ready solutions.
Scalable & Secure Systems
Architected resilient databases and embedded cybersecurity best practices into every deliverable.
Want to see more?
Check out the projects and resources I've built along the way.