Marco Bressan
About Marco Bressan
Marco Bressan is a Research Engineer with a strong academic background in psychology and cognitive science. He currently works at Aix-Marseille University and specializes in analyzing psychological and behavioral variables using advanced statistical models.
Work at Aix-Marseille University
Marco Bressan has been employed as a Research Engineer at Aix-Marseille University since 2020. In this role, he focuses on analyzing psychological and behavioral variables through advanced statistical models. His work contributes to various research initiatives within the university, emphasizing the transformation of data into actionable insights. Bressan's expertise in statistical modeling supports the academic community in understanding complex psychological phenomena.
Education and Expertise
Marco Bressan holds a diverse educational background. He achieved a Laurea in Psychology of Personality and Interpersonal Relations from Università degli Studi di Padova from 2008 to 2011. He earned a Master's Degree in Social, Work and Communication Psychology from the same university between 2011 and 2013. Bressan completed a PhD in Cognitive Science at Università degli Studi di Trento from 2014 to 2018. He also obtained a 1-year Master's in Management of Advanced Services from Bologna Business School in 2018. Additionally, he has been studying English at the University of Cambridge since 2005.
Background
Marco Bressan's professional journey includes various roles in research and management. He worked as a Postdoctoral Researcher at Università degli Studi di Trento for four months in 2018. Following this, he served as a Research Engineer at BOXXAPPS S.R.L. from 2018 to 2020. He also held a position as a Commercial Director Assistant at Comuni-Chiamo for four months in 2018. His background combines technical expertise in electronics and telecommunications with a strong foundation in psychology and cognitive science.
Achievements
Marco Bressan specializes in the analysis of psychological and behavioral variables using advanced statistical models. He engages in continuous personal development to enhance his skills and assist colleagues in experimental and field situations. Bressan prefers statistical modeling over machine learning in his research work, which reflects his commitment to applying rigorous scientific methods in his analyses. His guidance on data gathering emphasizes the importance of transforming raw data into useful information for research purposes.