Dr. Manuel Fritz, MBA

Professional Scrum Product Owner (PSPO I)

Deep Learning Spezialisierung

Link zum Zertifikat und weiteren Details

Software Campus Fellow (inkl. Projektförderung in Höhe von 100.000 EUR)

Projektseite mit weiteren Details

ITIL Service Management (Foundation)

Auszeichnung für herausragende Leistungen im Fach Mathematik

Verein Deutscher Ingenieure (VDI)

Tag der offenen Tür Informatik inkl. Künstliche Intelligenz Services & Systeme (Panel-Talk), Hochschule Furtwangen, Deutschland

18th Symposium and Summer School On Service-Oriented Computing, Kreta, Griechenland

Industry Summit on Data Product Oriented Architectures, Jheronimus Academy of Data Science, 's-Hertogenbosch, Niederlande

Workshop "Neue Ansätze und Anwendungen der KI", Universität Stuttgart, Deutschland

34th GI-Workshop Grundlagen von Datenbanken, Hirsau, Deutschland

Workshop "Complex Data Environments", Universität Stuttgart, Deutschland

16th Symposium and Summer School On Service-Oriented Computing, Kreta, Griechenland

Sarah Oppold, Manuel Fritz, Lucas Woltmann. Data Contracts to Leverage (De-)Centralized Data Management in Manufacturing Industries: An Experience Report. To appear in Proceedings of 21st Conference on Database Systems for Business, Technology and Web (BTW 2025).

Dennis Treder-Tschechlov, Manuel Fritz, Holger Schwarz, Bernhard Mitschang. Ensemble Clustering Based on Meta-Learning and Hyperparameter Optimization. In Proceedings of the International Conference on Very Large Data Bases (VLDB 2024).

Dennis Treder-Tschechlov, Manuel Fritz, Holger Schwarz, Bernhard Mitschang. ML2DAC: Meta-Learning to Democratize AutoML for Clustering Analysis. In ACM Special Interest Group on Management of Data (SIGMOD 2023).

Manuel Fritz, Michael Behringer, Dennis Tschechlov, Holger Schwarz. Efficient Exploratory Clustering Analyses in Large-Scale Exploration Processes. In the International Journal on Very Large Data Bases (VLDB Journal 2022).

Michael Behringer, Manuel Fritz, Holger Schwarz, Bernhard Mitschang. DATA-IMP: An Interactive Approach to Specify Data Imputation Transformations on Large Datasets. In Proceedings of International Conference on Cooperative Information Systems (CoopIS), pp. 55-74, 2022. Lecture Notes in Computer Science, vol 13591. Springer, Cham *Best Conference Paper Award*

Manuel Fritz, Gang Shao, Holger Schwarz. Automatic Selection of Analytic Platforms with ASAP-DM. In Proceedings of the International Conference on Scientific and Statistical Database Management (SSDBM 2021).

Manuel Fritz, Dennis Tschechlov, Holger Schwarz. Efficient Exploratory Clustering Analyses with Qualitative Approximations. In Proceedings of the International Conference on Extending Database Technology (EDBT 2021).

Dennis Tschechlov, Manuel Fritz, Holger Schwarz. AutoML4Clust: Efficient AutoML for Clustering Analyses. In Proceedings of the International Conference on Extending Database Technology (EDBT 2021).

Manuel Fritz, Michael Behringer, Holger Schwarz. LOG-Means: Efficiently Estimating the Number of Clusters in Large Datasets. In Proceedings of 46th International Conference on Very Large Data Bases (VLDB 2020).

Manuel Fritz, Dennis Tschechlov, Holger Schwarz. Learning from Past Observations: Meta-Learning for Efficient Clustering Analyses. In Proceedings of 22nd International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2020).

Michael Behringer, Pascal Hirmer, Manuel Fritz, Bernhard Mitschang. Empowering Domain Experts to Preprocess Massive Distributed Datasets. In Proceedings of 23rd International Conference on Business Information Systems (BIS 2020).

Manuel Fritz, Holger Schwarz. Initializing k-Means Efficiently: Benefits for Exploratory Cluster Analysis. In Proceedings of On the Move to Meaningful Internet Systems: OTM 2019 Conferences (OTM), pp. 146–163, 2019. Lecture Notes in Computer Science, vol 11877. Springer, Cham

Manuel Fritz, Osama Muazzen, Michael Behringer, Holger Schwarz. ASAP-DM: a framework for automatic selection of analytic platforms for data mining. In Software-Intensive Cyber-Physical Systems (pp. 1–13). Springer Berlin Heidelberg.

Manuel Fritz, Michael Behringer, Holger Schwarz. Quality-driven early stopping for explorative cluster analysis for big data. SICS Software-Intensive Cyber-Physical Systems, 34(2–3), 129–140.

Manuel Fritz, Simon Albrecht, Holger Ziekow, Jens Strüker. Benchmarking Big Data Technologies for Energy Procurement Efficiency. In Proceedings of the 23rd America’s Conference on Information Systems (AMCIS 2017).

Simon Albrecht, Manuel Fritz, Jens Strüker, Holger Ziekow. Targeting customers for an optimized energy procurement: A Cost Segmentation Based on Smart Meter Load Profiles. Computer Science - Research and Development, 32(1–2), 225–235.

Dennis Tschechlov. Analysis and Transfer of AutoML Concepts for Clustering Algorithms. (Masterthesis)

Tim Niederhausen. Untersuchung der Auswirkungen von Autoencodern auf Datenanalyseprozesse. (Bachelorthesis)

Julius Voggesberger. Evaluation von Zwischenergebnissen in Entscheidungsbäumen. (Bachelorthesis)

Kay Roggenbuck. Feature-getriebene Darstellung von Clustering-Resultaten. (Bachelorthesis)

Osama Muazzen. Framework for Automatic Selection of Analytic Platforms for Data Mining Tasks. (Masterthesis)

Kinda Loutfi. Evaluation of prediction mechanisms of parameters for data mining algorithms. (Masterthesis)

Birgit Ast. Interaktive und inkrementelle Visualisierung im Kontext von Big Data. (Bachelorthesis)

Dennis Tschechlov. Metriken zur Evaluation von Teilschritten in Data-Mining-Analysen. (Bachelorthesis)