Curriculum vitae

Personal details

  • name: Andrzej Gajda
  • date of birth: 22.05.1987
  • e-mail:
    • andrzej.m.gajda [at] gmail.com
    • andrzej.gajda [at] amu.edu.pl

Education

  • 2013–2019 Institute of Psychology, Adam Mickiewicz University, Poznań
    PhD programme: Cognitive science
  • 2010–2013 Institute of Psychology, Adam Mickiewicz University, Poznań
    MA programme: Cognitive science
  • 2010–2011 Department of Mechanical Engineering and Transport, Poznań University of Technology, Poznań
    MSc programme: Mechanics and mechanical engineering, mechatronics
  • 2006–2010 Department of Mechanical Engineering and Transport, Poznań University of Technology, Poznań
    BSc programme: Mechanics and mechanical engineering, mechatronics

Degrees

  • 2019 PhD in Cognitive science
    Institute of Psychology, Adam Mickiewicz University, Poznań
    PhD thesis: Abductive hypotheses generation in neural-symbolic systems
  • 2013 MA in Cognitive science
    Institute of Psychology, Adam Mickiewicz University, Poznań
    MA thesis: Emocje a rozumowania
  • 2011 MSc in Mechatronics
    Department of Mechanical Engineering and Transport, Poznań University of Technology, Poznań
    MSc thesis: Opracowanie konstrukcji dżojstika sześcioosiowego
  • 2010 BSc in Mechanical engineering
    Department of Mechanical Engineering and Transport, Poznań University of Technology, Poznań
    BSc thesis: Projekt napędu i sterowania suportem urządzenia do obróbki mikrofinish walców

Grants

  • Modeling of Abductive Reasoning (PhD student; the project funded by National Science Centre, Poland, Sonata-Bis grant, DEC-2013/10/E/HS1/00172).

Courses

  • European Summer School in Logic, Language and Information, Bolzano, Italy, 2016
  • SMART Cognitive Science: the Amsterdam Conference, Amsterdam, Holland, 2015
  • European Summer School in Logic, Language and Information, Barcelona, Spain, 2015
  • European Summer School in Logic, Language and Information, Opole, Polska, 2012

Teaching experience

  • Introduction to logic
  • Basics of functional programming
  • Mathematics for cognitive science students
  • Artificial neural networks and neuro-symbolic integration
  • Artificial intelligence
  • Information technology