Dominik Falkner
Dominik Falkner completed his bachelor's degree in Software Engineering in 2018 and his master's degree in Data Science and Engineering with a specialization in Data Analysis in Production and Marketing at Hagenberg University of Applied Sciences in 2020.
During his studies, he already worked on various software systems, including some for collecting and storing data. Since 2019, he has been employed by the RISC Software GmbH as a Data Scientist, working in customer and research projects. His interests and focus lie in the following disciplines:
Employing machine learning techniques.
The fusion of expert knowledge and machine learning methods
Predictive and prescriptive analytics
Design and architecture of software systems
In the course of his work as a Data Scientist, he mainly deals with time series analyses and classification settings from various industries. In 2022 he will start his PhD studies at the Institute for Formal Models and Verification at Johannes Kepler University in Linz.
Session
Flame cutting is a method where metals are efficiently cut using precise control of the oxygen jet and consistent mixing of fuel gas. The condition of the nozzle is changing over time: deposits formed during the cutting process can degrade the flame quality, reducing the precision of the cut. Traditionally, nozzles suspected of wear are sent back for manual inspection, where experts evaluated the flame visually and audibly to determine whether repair or replacement is needed. This project leverages machine learning to optimize this process by analyzing acoustic emission data.