Dr. Zoltán Lakner

Professor, Hungarian University of Agriculture & Life Sciences (MATE), Hungary, EU

Professional experience:

  • 1986 – 2000 University of Horticulture and Food Industry, assistant professor, 1991: associate professor
  • 2000 – 2002 Szent István University
  • 2002 – 2003 Budapest University of Economics and Public Administration
  • 2003 – 2017 Corvinus University of Budapest
  • 2018 – 2021 Szent István University
  • 2021 – Hungarian University of Agriculture and Life Sciences
  • Member and chairman of the Agricultural Economics Committee of the Hungarian Academy of Sciences
  • Member of the editorial board of Economics and Military Science journals

Education, qualification:

  •  1978-1983 preservation engineer (KE)
  •  1985 university doctor (doctor univ.)
  •  1985-1987 business economics engineer (KÉE)
  •  1987 chartered accountant (PM)
  •  1989-1991 innovation manager economist (BKÁE)
  •  2009 dr. habile (agricultural sciences) (BCE)

Field of research and activity:
econometrics, economic statistics, operations research, use of artificial intelligence in decision-making, system dynamic modeling

Awards and recognitions:

  • 1978 Leading soldier of the Regiment (Hungarian People’s Army)
  • 2002 Louis de Saint-Rat literature prize (Hungarian Food Industry Scientific Association)
  • 2018 Pro Alimentis Hungariae (Ministry of Agriculture)

Doctoral training information: https://doktori.hu/index.php?menuid=192&lang=HU&sz_ID=1425

Publication data: https://m2.mtmt.hu/gui2/?type=authors&mode=browse&sel=10000802

Taught subjects:

  • Food industry management
  • Food industry economics
  • Research methodology
  • Research methodology
  • Food economics
  • EU knowledge
  • R programming and artificial intelligence
  • Analysis of competitiveness of agrarian-industrial complex (Moscow Agricultural Academy)

Optional thesis topics:

  • Analysis of food economic time series with neural networks
  • Big data-based analyzes on bibliometric databases
  • Optimal control of bioeconomic systems
  • Application of text mining methods in the collection of strategic information
  • Food chain optimization in Africa