No current affiliations available for this person. The person is no longer active at the university.

Academic Education
03/2016 - 01/2020	Doctoral candidate in Information Systems at the University of Münster, Germany
10/2013 - 09/2015	Master studies in Information Systems at the University of Münster
10/2010 - 09/2013	Bachelor studies in Information Systems at the University of Münster
Work Experience
since 03/2016	Research assistant at the chair for Information Systems and Statistics at the University of Münster
03/2016 - 02/2019	Research Associate of the ERCIS Omni-Channel Lab - powered by Arvato
2017	Lecturer at the Data Science certificate programme at the Münster University Continuing Education (WWU Weiterbildung gGmbH)
01/2016 - 02/2016	Graduate student assistant at the chair for Information Systems and Statistics at the University of Münster
04/2014 - 12/2015	Graduate Student Assistant at the IT Security Research Group at the University of Münster
11/2012 - 03/2014	Student assistant at the chair for Information Systems and Information Management at the University of Münster

Machine Learning on Data Streams - Improving the Applicability and Performance of Stream Clustering Algorithms Carnein Matthias (2020) (no publisher available). Type of Publication: Thesis (doctoral or post-doctoral)
confStream: Automated Algorithm Selection and Configuration of Stream Clustering Algorithms Carnein Matthias, Trautmann Heike, Bifet Albert, Pfahringer Bernhard (2020) In: (eds.), . (no publisher available). Type of Publication: Research article in edited proceedings (conference)
Towards Automated Configuration of Stream Clustering Algorithms Carnein Matthias, Trautmann Heike, Bifet Albert, Pfahringer Bernhard (2020) In: (eds.), . (no publisher available). Type of Publication: Research article in edited proceedings (conference)
A Recommender System Based on Omni-Channel Customer Data Carnein Matthias, Homann Leschek, Trautmann Heike, Vossen Gottfried (2019) In: (eds.), . (no publisher available). Type of Publication: Research article in edited proceedings (conference)
Customer Segmentation Based on Transactional Data Using Stream Clustering Carnein Matthias, Trautmann Heike (2019) In: (eds.), . (no publisher available). Type of Publication: Research article in edited proceedings (conference)

9th International Conference on Evolutionary Multi- Criterion Optimization, Münster 19. - 22.03.2017 (EMO 2017) Duration: 19/03/2017 - 22/03/2017 Funded by: Participation / conference fees , DFG - International Scientific Events Type of project: Scientific Event
ERCIS Omni-Channel Lab - powered by Arvato Duration: 01/03/2016 - 28/02/2019 Funded by: ARVATO direct services GmbH Type of project: Individual project

CBI Best Paper Award 2019 Awarded by: 21st IEEE Conference on Business Informatics (CBI '19) Award given to: Carnein, Matthias; Homann, Leschek; Trautmann, Heike; Vossen, Gottfried Announced at: 15/07/2019 \| Date of awarding: 15/07/2019 Type of distinction: Best publication award
Marie Skłodowska-Curie Fellowship Awarded by: Research Executive Agency of the European Commission Award given to: Carnein, Matthias Announced at: 01/01/2019 Type of distinction: Scholarship

Machine Learning on Data Streams - Improving the Applicability and Performance of Stream Clustering Algorithms
Candidate: Carnein, Matthias | Supervisors: Trautmann, Heike; Bifet Albert
Period of time: until 21/01/2020
Doctoral examination procedure finished at: Doctoral examination procedure at University of Münster