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Lucas Baier, M. Sc.

Lucas Baier, M. Sc.

Digital Service Innovation
Advanced Analytics
Group: Digital Service Innovation
Room: 4B-06
CS 05.20

Phone: +49 721 608-45772
lucas baierAqb8∂kit edu


Activities

Lucas Baier is a research associate at the digital service innovation group within the Karlsruhe Service Research Institute (KSRI). He is a member of the Applied AI lab.

 

Interests

  • Machine Learning in Data Streams
  • Concept Drift Handling in Real-world Applications
  • Sustainable Application of Machine Learning Models
  • Analytics in Healthcare 

 

Theses 

If you are interested in writing a Bachelor or Master thesis, feel free to contact me at any time. 

Curriculum Vitae

Lucas Baier studied Industrial Engineering at Karlsruhe Institute of Technology during his Bachelor and Master and spent a semester abroad in Madrid. He wrote his Master thesis in cooperation with ABB about the data-driven prediction of faults in a chemical batch process.

 

Publications

Due to the interdisciplinary activities of KSRI researchers publication lists also contain publications that have not explicitly been developed in the course of their activities at KSRI.

2020
Zeitschriftenaufsätze
Will the Customers Be Happy? Identifying Unsatisfied Customers from Service Encounter Data.
Baier, L.; Kühl, N.; Schüritz, R.; Satzger, G.
2020. Journal of service management. doi:10.1108/JOSM-06-2019-0173
Proceedingsbeiträge
Handling Concept Drift for Predictions in Business Process Mining.
Baier, L.; Reimold, J.; Kühl, N.
2020. Proceedings of 22nd IEEE International Conference on Business Informatics
Handling Concept Drifts in Regression Problems – the Error Intersection Approach.
Baier, L.; Hofmann, M.; Kühl, N.; Mohr, M.; Satzger, G.
2020. Proceedings of 15th International Conference on Wirtschaftsinformatik, 2020, Potsdam, Germany
2019
Proceedingsbeiträge
Challenges in the Deployment and Operation of Machine Learning in Practice.
Baier, L.; Jöhren, F.; Seebacher, S.
2019. Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm and Uppsala, Sweden, June 8 - 14, 2019. Research Papers., Paper: 163, AIS Electronic Library (AISeL)
How to Cope with Change? Preserving Validity of Predictive Services over Time.
Baier, L.; Kühl, N.; Satzger, G.
2019. Hawaii International Conference on System Sciences (HICSS-52), Grand Wailea, Maui, Hawaii, Januar 8-11, 2019, 1085–1094, University of Hawai’i at Manoa / AIS