Christian Weber

Dr.-Ing.

Researcher - IPVS - Applications of Parallel and Distributed Systems

My dissertation is entitled "A Platform for Managing Machine Learning Models in Industry 4.0 Environments".

For many data scientists, the use of a software platform for model management means a noticeable facilitation of their daily workflows and provides valuable support for the management of their ML models. Currently, however, such platforms are not aligned with the lifecycle of ML models and focus on data scientists in isolation. 

In my dissertation, I present new concepts for building a model management platform. My goal is to support other user groups besides data scientists, such as domain experts and business analysts. The foundation of the concepts is a solid metadata management that enables many intelligent functions for managing and deploying ML models.

 

Funding

This project was primarily funded by the German Research Foundation (DFG) within the Graduate School of Excellence advanced Manufacturing Engineering (GSaME).

GSaME-Logo_komplett_RGB            dfg_logo_schriftzug_blau_foerderung_en

Additionally, it was supported by the Software Campus Initiative, which is funded by the German Federal Ministry of Education and Research (BMBF).

SWC      bmbf_logo_neu_eng

2021

Zacarias, A.G.V., Weber, C., Reimann, P., Mitschang, B.: AssistML: A Concept to Recommend ML Solutions for Predictive Use Cases. In: 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA). pp. 1–12 (2021). https://doi.org/10.1109/DSAA53316.2021.9564168.

2020

Weber, C., Reimann, P.: MMP - A Platform to Manage Machine Learning Models in Industry 4.0 Environments. In: 24th IEEE International Enterprise Distributed Object Computing Workshop, EDOC Workshops 2020, Eindhoven, Netherlands. IEEE (2020).
 
Weber, C., Hirmer, P., Reimann, P.: A Model Management Platform for Industry 4.0 - Enabling Management of Machine Learning Models in Manufacturing Environments. In: Abramowicz, W., Alt, R., Klein, G., Paschke, A., and Sandkuhl, K. (eds.) Proceedings of the 23rd International Conference on Business Information Systems. Springer International Publishing (2020).
 
Stach, C., Giebler, C., Wagner, M., Weber, C., Mitschang, B.: AMNESIA: A Technical Solution towards GDPR-compliant Machine Learning. In: Proceedings of the 6th International Conference on Information Systems Security and Privacy. SCITEPRESS - Science and Technology Publications (2020). https://doi.org/10.5220/0008916700210032.

2019

Weber, C., Hirmer, P., Reimann, P., Schwarz, H.: A New Process Model for the Comprehensive Management of Machine Learning Models. In: Filipe, J., Smialek, M., Brodsky, A., and Hammoudi, S. (eds.) Proceedings of the 21st International Conference on Enterprise Information Systems, ICEIS 2019, Heraklion, Crete, Greece, May 3-5, 2019, Volume 1. pp. 415–422. SciTePress (2019). https://doi.org/10.5220/0007725304150422.

2018

Brenner, D., Weber, C., Lenz, J., Westkaemper, E.: Total Tool Cost of Ownership Indicator for Holistical Evaluations of Improvement Measures within the Cutting Tool Life Cycle. In: Wang, L., Kjellberg, T., Wang, X.V., and Ji, W. (eds.) Procedia CIRP. pp. 1404–1409. Elsevier B.V. (2018). https://doi.org/10.1016/j.procir.2018.03.164.
 
Weber, C., Wieland, M., Reimann, P.: Konzepte zur Datenverarbeitung in Referenzarchitekturen für Industrie 4.0. Datenbank-Spektrum. 18, 39--50 (2018). https://doi.org/10.1007/s13222-018-0275-z.

2017

Weber, C., Königsberger, J.: Industrie 4.0: Aktuelle Entwicklungen für Analytics. Teil 2: Vergleich und Bewertung von Industrie 4.0-Referenzarchitekturen. wt Werkstattstechnik online. 107, 405–409 (2017).
 
Weber, C., Königsberger, J.: Industrie 4.0: Aktuelle Entwicklungen für Analytics. Teil 1: Analytics und Datenmanagement in Industrie 4.0-Referenzarchitekturen. wt Werkstattstechnik online. 107, 113–117 (2017).
 
Weber, C., Königsberger, J., Kassner, L., Mitschang, B.: M2DDM - A Maturity Model for Data-Driven Manufacturing. In: Tseng, M.M., Tsai, H.-Y., and Wang, Y. (eds.) Manufacturing Systems 4.0 – Proceedings of the 50th CIRP Conference on Manufacturing Systems. pp. 173–178. Elsevier B.V. (2017). https://doi.org/10.1016/j.procir.2017.03.309.

2016

Kassner, L., Gröger, C., Königsberger, J., Hoos, E., Kiefer, C., Weber, C., Silcher, S., Mitschang, B.: The Stuttgart IT Architecture for Manufacturing - An Architecture for the Data-Driven Factory. In: Hammoudi, S., Maciaszek, L.A., Missikoff, M., Camp, O., and Cordeiro, J. (eds.) Enterprise Information Systems - 18th International Conference, ICEIS 2016, Rome, Italy, April 25-28, 2016, Revised Selected Papers. pp. 53–80. Springer International Publishing (2016). https://doi.org/10.1007/978-3-319-62386-3.
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