👋 Hello! I’m Sándor, a Mathematics master’s student at the Technical University of Munich.
🎓 My academic journey is focused on Machine Learning, Deep Learning, and Mathematical Optimization.
Interests and Expertise
💻 I’m passionate about developing innovative software solutions and cutting-edge AI technologies, with interests in:
- Application development and scalable software architectures
- Large Language Models (LLMs)
- Efficient ML architectures
- Large-scale data analytics for data-driven decision making
Technical Skills
🛠️ Experienced with:
- Languages: Python, Java, SQL, R
- Frameworks/Libraries: PyTorch, Transformers, pandas
- Tools: Git, Docker, AWS, Databricks, Tableau
- Practices: Agile methodologies, CI/CD, Test-Driven Development
Professional Goals
- Develop robust, scalable software solutions for complex problems
- Bridge the gap between theoretical ML and practical applications
- Contribute to innovative projects that leverage both traditional software development and AI/ML technologies
Current Focus
🌱 Currently, I’m diving deep into:
- Developing and optimizing LLMs
- Exploring AI model compression and quantization techniques
- Implementing deep learning methods for applications in Spectrum Monitoring
- Microservices architecture and cloud-native applications
My Journey
📚 Education
- MSc Mathematics in Operations Research, Technical University of Munich
- Oct 2021 - Mar 2025
- BSc Mathematics, Eötvös Loránd University, Budapest
- Sep 2018 - Jun 2021
💼 Work Experience
- Master Thesis Student, Pruna AI & Technical University of Munich
- Sep 2024 - Present
- Working Student - Machine Learning Engineer, Rohde & Schwarz GmbH & Co. KG.
- Feb 2024 - Present
- Working Student - Data Science, Lidl Stiftung & Co. KG
- Oct 2022 - Mar 2023
- Intern - Data Science, Spryfox GmbH
- Apr 2022 - Sep 2022
Beyond Work
🌍 When not coding, I’m enjoying long-distance running, exploring new cultures, learning languages, or cooking good food.
Contact
Feel free to reach out through Email or connect with me on GitHub and LinkedIn.