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.)

Lectures

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)

Projects

KD²Ex: Experimental Research for Wellbeing, Work, and Education at Home (ongoing)
WorkLifeSens (finished)
Kern - Kompetenzen entwickeln und richtig nutzen (finished)

Community Work

Reviewer for Internation Conference on Information Systems (ICIS) 2022 (https://icis2022.aisconferences.org/)
Reviewer for Conference on Human Factors in Computing Systems (CHI) 2023 (https://chi2023.acm.org/)

Publications

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