Academic · Education

BSc in Computer Science Engineering

Period
Sep 2018 – Jan 2022 · 3 yrs 5 mos
Organisation
Budapest University of Technology and Economics (BME)
Location
BME Faculty of Electrical Engineering and Informatics (buildings Q and I)Magyar tudósok körútja 2, 1117 Budapest, Hungary
Posted

Bachelor's degree in computer engineering with a specialisation in System Design. GPA 4.85/5.00, cum laude. Graduated at the Department of Automation and Applied Informatics with a thesis on deep-learning-based text mining of Hungarian-language sales contracts.

  • GPA 4.85 / 5.00, cum laude
  • Specialisation: System Design
  • Integrated BSc–MSc (IMSc) talent programme

I studied computer engineering ("Mérnökinformatikus") at BME, Hungary's leading technical university, specialising in System Design: the engineering of complete hardware–software systems, from requirements and modelling to implementation and testing. I graduated at the Department of Automation and Applied Informatics (AUT) of the Faculty of Electrical Engineering and Informatics (VIK).

The curriculum was broad and hands-on: programming in C, C++, Java and C#, databases, software engineering and modelling (UML), embedded systems, and the mathematics and theory underneath. I was part of the faculty's Integrated BSc–MSc (IMSc) talent programme, which gives selected students extra research and coursework opportunities across both degrees.

From May 2021 I combined the last semesters with a part-time position as an embedded software developer at iData.

Thesis

My thesis, Deep learning based text mining for the analysis of sales contracts in Hungarian, supervised by Dr. Gyula Max, was a client–server application that reads sales contracts and extracts their key entities with a transformer-based named-entity recognition model (project page).

Outcome

Graduated in January 2022 with a GPA of 4.85/5.00, cum laude.

References

  1. D. Frey. 2022. Deep learning based text mining for the analysis of sales contracts in Hungarian. BSc thesis, Budapest University of Technology and Economics. Supervisor: Dr. Gyula Max. diplomaterv.vik.bme.hu/en/theses/deep-learning-alapu-text-mining-magyar-nyelvu