Nico Loewe

Dr. Nico Loewe

  • Karlsruhe Institute of Technology (KIT)
    Institute of Information Systems and Marketing (IISM)
    Kaiserstraße 89
    76133 Karlsruhe


Research Interest:

  • Research in Information Systems (IS) and Human Computer Interaction (HCI)
  • Flow classification based on physiological signals with supervised machine learning (ML) techniques
  • IT-mediated interruptions
  • Adaptive Systems & Physiological Computing

Short CV

Since 11.2018 Doctoral Researcher at Institute of Information Systems and Marketing (IISM) within the Research Group Information Systems I at the Karlsruhe Institute of Technology (KIT)
04.2018 Business Information Systems at University of Applied Sciences Friedberg (THM); Thesistopic: "Detecting Flow using Wearables and Machine Learning"
04.2018-07.2018 Lehrauftrag für Wirtschaftsinformatik, Bachelor Betriebswirtschaftslehre, THM StudiumPlus, Wetzlar
10.2016-10.2018 Working Student, Innovation Center Network: Research an Innovation, SAP SE , Walldorf
06.2016 B. Sc. Business Information Systems at University of Applied Sciences Friedberg (THM); Thesistopic: "Monetäre Bewertung von Verkehrsszenarien im Kontext von Smart City"

Teaching (Lectures, Thesis Projects, etc.)


  • Summer 2021: Foundations of Interactive Systems (Course)
  • Summer 2021: Interactive Analytics Seminar (Course / Topic)
  • Summer 2020: Foundations of Interactive Systems (Course)
  • Summer 2020: Interactive Analytics Seminar (Seminar)
  • Summer 2019: Foundations of Interactive Systems (Course)
  • Summer 2019: Interactive Analytics Seminar (Seminar)


Community Work


PhD Theses
Designing flow-adaptive systems for knowledge work using physiological data and machine learning. PhD dissertation
Loewe, N.
2022, August 29. Karlsruher Institut für Technologie (KIT)
Conference Papers
Toward User-adaptive Interactive Labeling on Crowdsourcing Platforms
Knaeble, M.; Nadj, M.; Maedche, A.; Loewe, N.
2022. CHI 2022 Workshop - REGROW: Reimagining Global Crowdsourcing for Better Human-AI Collaboration
Predicting In-Field Flow Experiences Over Two Weeks From ECG Data: A Case Study
Knierim, M.; Pieper, V.; Schemmer, M.; Loewe, N.; Reali, P.
2021. Information Systems and Neuroscience: NeuroIS Retreat 2021. Ed.: F. D. Davis, 107–117, Springer. doi:10.1007/978-3-030-88900-5_11
Physio-Adaptive Systems - A State-of-the-Art Review and Future Research Directions
Loewe, N.; Nadj, M.
2020. ECIS 2020 Proceedings - Twenty-Eighth European Conference on Information Systems, Marrakesh, Marokko, June 15 - 17, 2020, 19 S
Journal Articles
To Be or Not to Be in Flow at Work: Physiological Classification of Flow using Machine Learning
Rissler, R.; Nadj, M.; Li, M. X.; Loewe, N.; Knierim, M. T.; Maedche, A.
2020. IEEE transactions on affective computing, 14 (1), 463–474. doi:10.1109/TAFFC.2020.3045269