Challenges from Data-Driven Predictive Maintenance in Brownfield Industrial Settings. - Georgios Koutroulis; Stefan Thalmann (BIS (Workshops), 2018)

Enhanced Active Learning of Convolutional Neural Networks: A Case Study for Defect Classification in the Semiconductor Industry. - Georgios Koutroulis; Tiago Santos; Michael Wiedemann; Christian Faistauer; Roman Kern; Stefan Thalmann (KDIR, 2020)

Visual Exploration of Anomalies in Cyclic Time Series Data with Matrix and Glyph Representations. - Josef Suschnigg; Belgin Mutlu; Georgios Koutroulis; Vedran Sabol; Stefan Thalmann; Tobias Schreck (Big Data Res., 2021)

KOMPOS: Connecting Causal Knots in Large Nonlinear Time Series with Non-Parametric Regression Splines. - Georgios Koutroulis; Leo Botler; Belgin Mutlu; Konrad Diwold; Kay Römer; Roman Kern (ACM Trans. Intell. Syst. Technol., 2021)

Poster Abstract: Accurate and Efficient Hybrid Indoor Localization using ML Methods. - Milot Gashi; Leo Botler; Georgios Koutroulis; Konrad Diwold (IPSN, 2022)

ManEx: The Visual Analysis of Measurements for the Assessment of Errors in Electrical Engines. - Joscha Eirich; Georgios Koutroulis; Belgin Mutlu; Dominik Jäckle; Roman Kern; Tobias Schreck; Jürgen Bernard (IEEE Computer Graphics and Applications, 2022)

Constructing robust health indicators from complex engineered systems via anticausal learning. - Georgios Koutroulis; Belgin Mutlu; Roman Kern (Eng. Appl. Artif. Intell., 2022)

A Causality-Inspired Approach for Anomaly Detection in a Water Treatment Testbed. - Georgios Koutroulis; Belgin Mutlu; Roman Kern (Sensors, 2023)

Local machine learning model-based multi-objective optimization for managing system interdependencies in production: A case study from the ironmaking industry. - Matej Vukovic; Georgios Koutroulis; Belgin Mutlu; Petra Krahwinkler; Stefan Thalmann (Eng. Appl. Artif. Intell., 2024)

MANDALA - Visual Exploration of Anomalies in Industrial Multivariate Time Series Data. - Josef Suschnigg; Belgin Mutlu; Georgios Koutroulis; H. Hussain; Tobias Schreck (Comput. Graph. Forum, 2025)