Explainable Artificial Intelligence - Anomaly Detection - Machine Learning
I am part of the DMIR research group since I recieved my Master's Degree in Computer Science from the University of Würzburg in early 2019. As part of the BMBF founded research program DeepScan, I am investigating the explainable detection of anomalous and fraudulent behavior in ERP (Enterprise Resource Planning) systems.
“Open ERP System Data For Occupational Fraud Detection”, arxiv, available: https://arxiv.org/abs/2206.04460.(2022)
“A financial game with opportunities for fraud”, IEE COG 2021, 2021, available: https://ieee-cog.org/2021/assets/papers/paper_273.pdf.(2021)
“Emote-Controlled: Obtaining Implicit Viewer Feedback through Emote based Sentiment Analysis on Comments of Popular Twitch.tv Channels”, ACM Transactions on Social Computing.(2020)
“Evaluation of post-hoc XAI approaches through synthetic tabular data”, International Symposium on Methodologies for Intelligent Systems.(2020)