Mag. Christian Lettner

Senior Research Project Manager Data Science
Research Team Lead Data Centric AI Engineering

Details

Christian Lettner is Senior Research Project Manager for Data Science. He has more than 20 years of experience in industrial and application oriented research projects.

Research Interests

Developing architectures for scalable data platforms
Exploring methods for ensuring high quality data
Deploying and maintaining machine learning models in production
Applying data analysis and machine learning to improve machine and process control

Key Facts

Master in Business Informatics from Johannes Kepler University Linz
Managed several industrial and research projects, e.g. Sebista (FFG COMET) and Deepred (FFG Comet)

Publikationen

2024
DQD: The Data Quality Definition Ontology

Schrott, J., Meindl, R., Lettner, C., Wöß, W., Ehrlinger, L. (2024). DQD: The Data Quality Definition Ontology. In: Garoufallou, E., Sartori, F. (eds) Metadata and Semantic Research. MTSR 2023. Communications in Computer and Information Science, vol 2048. Springer, Cham.
2023
GOLDCASE: A Generic Ontology Layer for Data Catalog Semantics

Schrott, J., Weidinger, S., Tiefengrabner, M., Lettner, C., Wöß, W., & Ehrlinger, L. (2023). GOLDCASE: A Generic Ontology Layer for Data Catalog Semantics. Communications in Computer and Information Science, 26–38.
2022
Data Integration, Management, and Quality: From Basic Research to Industrial Application

Ehrlinger, L., Lettner, C., Fragner, W., Gsellmann, G., Nestelberger, S., Rauchenzauner, F., Schützeneder, S., Tiefengrabner, M., & Zeindl, J. (2022). Data Integration, Management, and Quality: From Basic Research to Industrial Application. Database and Expert Systems Applications - DEXA 2022 Workshops, 167–178.
Using Property Graphs to Segment Time-Series Data

Karetnikov, A., Rehberger, T., Lettner, C., Himmelbauer, J., Nikzad-Langerodi, R., Gsellmann, G., Nestelberger, S., & Schützeneder, S. (2022). Using Property Graphs to Segment Time-Series Data. Database and Expert Systems Applications - DEXA 2022 Workshops, 416–423.
2021
DaQL 2.0: Measure Data Quality based on Entity Models

Lettner, C., Stumptner, R., Fragner, W., Rauchenzauner, F., & Ehrlinger, L. (2021). DaQL 2.0: Measure Data Quality based on Entity Models. Procedia Computer Science, 180, 772–777.
Steering Drivers of Change: Maximising Benefits of Trustworthy IoT

Veledar, O., Armengaud, E., Botler, L. H., Damjanovic-Behrendt, V., Derler, C., Jaksic, S., Krammer, L., Lettner, C., Macher, G., Marksteiner, S., Martin, A., Matschnig, M., Priller, P., Ramacher, S., Römer, K., Schmittner, C., Tiefnig, C., Vallant, H., Weiskirchner, H., & Drobics, M. (2021). Steering Drivers of Change: Maximising Benefits of Trustworthy IoT. Systems, Software and Services Process Improvement, 663–674.
2020
A semi-supervised approach for network intrusion detection

Švihrová, R., & Lettner, C. (2020). A semi-supervised approach for network intrusion detection. Proceedings of the 15th International Conference on Availability, Reliability and Security.
An integrated approach for power transformer modeling and manufacturing

Lettner, C., Moser, M., & Pichler, J. (2020). An integrated approach for power transformer modeling and manufacturing. Procedia Manufacturing, 42, 351–355.
General model for tracking manufacturing products using graph databases

Martinez-Gil, J., Stumptner, R., Lettner, C., Pichler, M., Mahmoud, S., Praher, P., & Freudenthaler, B. (2020). General Model for Tracking Manufacturing Products Using Graph Databases. Data-Driven Process Discovery and Analysis, 86–100.
Tackling semantic shift in industrial streaming data over time

Ehrlinger, L., Lettner, C., & Himmelbauer, J. (2020) Tackling semantic shift in industrial streaming data over time Proceedings of the 12th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2020), pages 36-39, IARIA, October 2020.
Reinforcement-Learning-based Optimization for Day-ahead Flexibility Extraction in Battery Pools

Chasparis, G. C., & Lettner, C. (2020). Reinforcement-Learning-based Optimization for Day-ahead Flexibility Extraction in Battery Pools. IFAC-PapersOnLine, 53(2), 13351–13358.
2019
Design and implementation of a graph-based solution for tracking manufacturing products

Martinez-Gil, J., Stumpner, R., Lettner, C., Pichler, M., & Fragner, W. (2019). Design and Implementation of a Graph-Based Solution for Tracking Manufacturing Products. New Trends in Databases and Information Systems, 417–423.
Decentralized energy networks based on blockchain: Background, overview and concept discussion

Pichler, M., Meisel, M., Goranovic, A., Leonhartsberger, K., Lettner, G., Chasparis, G., Vallant, H., Marksteiner, S., & Bieser, H. (2019). Decentralized Energy Networks Based on Blockchain: Background, Overview and Concept Discussion. Lecture Notes in Business Information Processing, 244–257.

Mag. Christian Lettner

Details

Research Interests

Key Facts

Publikationen

2024

DQD: The Data Quality Definition Ontology

2023

GOLDCASE: A Generic Ontology Layer for Data Catalog Semantics

2022

Data Integration, Management, and Quality: From Basic Research to Industrial Application

Using Property Graphs to Segment Time-Series Data

2021

DaQL 2.0: Measure Data Quality based on Entity Models

Steering Drivers of Change: Maximising Benefits of Trustworthy IoT

2020

A semi-supervised approach for network intrusion detection

An integrated approach for power transformer modeling and manufacturing

General model for tracking manufacturing products using graph databases

Tackling semantic shift in industrial streaming data over time

Reinforcement-Learning-based Optimization for Day-ahead Flexibility Extraction in Battery Pools

2019

Design and implementation of a graph-based solution for tracking manufacturing products

Decentralized energy networks based on blockchain: Background, overview and concept discussion