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Personal profile

Ancillary activities

  • Provinciale Staten Noord-Holland | Haarlem | member of the provincial council | 2015-03-26 - present

Ancillary activities are updated daily

Research

In my research I focus on the role of technology for behavior change, especially behaviors related to health and wellbeing. I try to find out how we can understand human behavior based on sensor data, how we can use computational means to decide about useful interactions, and how we can design computer-based systems that support people in achieving behavior change.

Fingerprint Dive into the research topics where Michel Klein is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Research Output 2000 2019

Designing a system with persuasive communication to improve diet compliance for elderly users

van der Lubbe, L. M. & Klein, M. C. A., 2019, Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Nutrition
Communication
Compliance

There is an app for that! Active2Gether – Smart coaching strategies to promote physical activity

Middelweerd, A., 2019, 264 p.

Research output: PhD ThesisPhD Thesis - Research VU, graduation VUAcademic

Open Access
File

Applying machine learning algorithms for deriving personality traits in social network

Araújo, E. F. M., Simoski, B. & Klein, M., 9 Apr 2018, Proceedings of the 33rd Annual ACM Symposium on Applied Computing, SAC 2018. Association for Computing Machinery, Vol. Part F137816. p. 346-349 4 p.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Learning algorithms
Learning systems
Tuning

Computational model for reward-based generation and maintenance of motivation

Taj, F., Klein, M. C. A. & van Halteren, A., 2018, Brain Informatics: International Conference, BI 2018, Proceedings. Yang, Y., Yamamoto, V., Wang, S., Jones, E., Su, J., Mitchell, T. & Iasemidis, L. (eds.). Springer - Verlag, p. 41-51 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11309 LNAI).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Reward
Computational Model
Maintenance
Hebbian Learning
Student Learning
Open Access
File