Dr. László Budai
Department of International Trade and Logistics
Associate professor
PhD
Contacts
- Office:1165 Budapest, Diósy Lajos utca 22-24.
- Building:Building E, 2nd Floor, Room 16
- Phone:+36 1 467-7936
- Internal extension:936
- Email:budai.laszlo@uni-bge.hu
Introduction
I graduated in 2008 as a teacher of mathematics and computer science. Between 2009 and 2011, I earned a master’s degree (MA) in both majors. Between 2011 and 2016, I carried out my PhD research, which aimed to assess the impact of the involvement and efficiency of IT tools in mathematics education. In 2017, I obtained a PhD. Doctoral degree from the Doctoral School of Mathematics and Computer Science of the University of Debrecen. Since 2013, I am a lecturer of Budapest Business School.
Office Hours
| Location | E.II.16. |
|---|---|
| Hours | e-mailben történő előzetes egyeztetés alapján / prior consultation by email is required |
| Comment |
Subject(s) taught
- Data Mining and Massive Data Management (Hungarian)
- Introduction to Digital Business Models (Hungarian)
- Information Management (Hungarian)
- Information Technology and the World (Hungarian)
- Informatics 2 (Hungarian)
- IT Skills Development (Hungarian)
- Professional and Financial Information Processing Skills (Hungarian)
- Internship (Hungarian)
- Business Information Systems B (Hungarian)
- Business Information Services (Hungarian)
- Business Intelligence in Practice (Hungarian)
- Business Intelligence, Decision Support Systems (Hungarian)
- ERP Systems (SAP) (Hungarian)
Professional career
- 2004 - 2008teacher of mathematics and informatics
- 2009 - 2011Diploma in Mathematics - Informatics Teacher (MA)
- 2017Obtaining a PhD degree in Mathematics and Computer Science
- 2017-member of public body of the Hungarian Academy of Sciences
- 2018-GM FOSZK Digital Business Services specialization in charge
- 2019-Chairman of the Faculty Study Committee
- 2019-leader of BOSCH Smart Shop Floor Logistics Laboratory
Research areas
- data models
- data analysis
- data visualization
- data-driven BI self-service systems
- Areas of application of ML / DL algorithms