Arbeitsgruppen I

Thematischer Austausch zur Podiumsdiskussion

Termin
Ende
Referent*innen

Dr. Gábor Kismihók

ReMO Action Chair

Since I obtained my summa cum laude PhD in management sciences (information management) in 2012, I have been concentrating my research efforts on the multi-disciplinary area of matching processes between education, labor market, and individuals. Previously, I founded the Center of Job Knowledge Research at the Amsterdam Business School, University of Amsterdam (UvA). Since then I have supervised doctoral research at the intersection of the following fields: Knowledge Management, Learning Analytics, Data Science and Organizational Behavior. I published my research in various peer-reviewed international journals and book chapters, mostly in the fields of knowledge management and education (e.g.: Organizational Research Methods, Journal of Learning Analytics (JLA), Journal of Vocational Behavior, and British Educational Research Journal). I regularly review manuscripts for academic journals and conferences in the scientific community I am engaged with (e.g. Computers in Human Behavior, JLA, LAK).

As the coordinator of the FP7 MSCA ITN Eduworks project, I developed a multi-disciplinary training programme for graduate students. This included the development of a transversal (e.g. writing and communication skills) and a personalized, research specific training programme covering methodological (advanced statistical methods, research design) and technical (data science, basic coding skills) courses for social scientists. Utilizing the above-mentioned training, I organized a number of summer and winter schools. Further, I worked out a complex quality management system to monitor the training progress of a multi-disciplinary group of graduate students

Dr. Stefan Mol

ReMO Action project, Working Group 2 Chair

Stefan T. Mol is assistant professor in Organizational Behavior and Research Methods at the Amsterdam Business School of the University of Amsterdam and co-founder and board member of the Scilink foundation. He received his Master's degree in psychology at the University of Amsterdam in 2000, and his PhD in psychology in 2007, at the Institute of Psychology of the Erasmus University Rotterdam. Stefan was/is involved in the EU-Funded Leonardo da Vinci Ontohr, Med-Assess, Ontotech and Nursing AI projects. From 2013-2017 Stefan served on the Board of Management and Supervisory Board of the FP7 Marie Curie Initial Training Network (ITN) Eduworks (see http://www.eduworks-network.eu) a project aimed at the socio-economic and psychological dynamics of labour supply and demand matching processes at aggregated and disaggregated levels. Finally, Stefan was involved in the coordination of a university-wide project aimed at establishing Learning Analytics at the University of Amsterdam from 2013-2016, and its successor from 2017-2019.

Dr. Brian Cahill

Dr Brian Cahill works in the Learning and Skills Analytics Lab of the Leibniz Information Centre for Science and Technology in Hannover as Grant Manager of the COST Action CA19117 on Researcher Mental Health. He is a Member of the Governing Board of EuroScience and was Chair of the Marie Curie Alumni Association from March 2016 to February 2018. In these roles, he engaged with early-career researchers on topics ranging from researcher career development, innovation, research funding, science communication, science policy, researcher pensions, research integrity, responsible research and innovation and many more.

He studied Mechanical Engineering in Ireland and moved to Germany in 1998 to take up a position with Hewlett Packard. He received his PhD for work in electrokinetically-driven fluid flow from the ETH Zurich in 2004 and subsequently carried out postdoctoral research in colloid and interface science at the University of Geneva. He was a Marie Curie fellow and Junior Research Group Leader at the Institute for Bioprocessing and Analytical Measurement Techniques in Heilbad Heiligenstadt (Germany), where his research interests focussed on measurement techniques for droplet-based microfluidics.