Tomas Olsson, Researcher (not working at IDT anymore)
Tomas Olsson is a PhD student at MdH and a researcher at SICS, with a licentiate degree from Uppsala University. His research interests are in applied AI, statistical machine learning and Case-Based Reasoning.
Diagnostics, data analysis, case-based reasoning, Bayesian statistics, machine learning, intrusion detection, active response, service level agreement, IDS, IPS, Alert correlation, Anomaly detection, risk analysis
Machine Learning Models for Industrial Applications (Feb 2021) Enislay Ramentol , Tomas Olsson, Shaibal Barua AI and Learning Systems - Industrial Applications and Future Directions (intechopen)
A Data-Driven Approach to Remote Fault Diagnosis of Heavy-duty Machines (Oct 2015) Tomas Olsson Doctoral Thesis (PhD Thesis)
Fault Diagnosis via Fusion of Information from a Case Stream (Sep 2015) Tomas Olsson, Ning Xiong, Elisabeth Källström , Peter Funk 23rd International Conference on Case-Based Reasoning (ICCBR 2015)
A Probabilistic Approach to Aggregating Anomalies for Unsupervised Anomaly Detection with Industrial Applications (May 2015) Tomas Olsson, Anders Holst The 28th International FLAIRS Conference (Flairs-28)
Representation and similarity evaluation of symbolic time series in uncertain environments (Sep 2014) Ning Xiong, Peter Funk, Tomas Olsson The Workshop on "Time in CBR" in the International Conference on Case-Based Reasoning, 2014 (RATIC14)
Explaining Probabilistic Fault Diagnosis and Classification using Case-based Reasoning (Sep 2014) Tomas Olsson, Daniel Gillblad, Peter Funk, Ning Xiong 22nd International Conference on Case-Based Reasoning (ICCBR 2014)
| Project Title | Status |
|---|---|
| CREATE ITEA2 | finished |
| ITS-EASY Post Graduate School for Embedded Software and Systems | finished |