Hi, I'm Miklos Sipos. 👋 I'm a full-stack developer, university lecturer, and researcher working at the intersection of software engineering, education, and applied research. I'm currently pursuing my PhD studies in blockchain technologies and serve as the specialization lead for Software Design and Development specialization.
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Fullstack Development
End-to-end web application development covering client-side foundations using vanilla JS and modern frontend practices, combined with REST API backend architecture. -
Frontend Development
Modern client-side development from core web technologies to framework-driven architectures, with a strong focus on Angular and TypeScript, complemented by styling ecosystems and component-based design. -
Thesis
Supervision of BSc and MSc theses, including topic definition, research guidance, and support for designing and implementing complete software solutions. I have supervised more than 100 thesis projects to successful completion. -
Advanced Development Techniques
Advanced C# and .NET development, covering delegates, LINQ, concurrency (tasks, threads), reflection, layered architectures, and testing practices in real-world applications. -
Software Design and Development II.
Object-oriented design and core data structures, including inheritance, polymorphism, interfaces, delegates and events, generics, and fundamental structures such as trees, graphs, and hash-based collections.
Tip
Course materials and additional resources are available both on my academic site and GitHub profile, check my repositories below at the pinned section.
- Optimal Gas Consumption in Ethereum Smart Contracts: A Targeted Review of Empirical Results, Design Patterns and Formal Methods
- Blockchain Transaction Graph Analysis Using Image Processing Techniques
- Analyzing Follower Data on Social Platforms Using Big Data Tools
- Blockchain-based Voting DApp with MetaMask Integration
- Analyzing Training Exercises with Mathematical Algorithms and Convolutional Neural Network
- Enhancing huBERT Model with Additional Convolutional and BiLSTM Layers for Hungarian Sentiment Analysis
You can find all publications here with full papers.