Trying to be a generalist with a deep understanding and intuition of recent technologies related to Data Engineer, Data Science, and Machine Learning. Currently leading a team of Data Scientists helping customers sorting their data, lifting its quality to ML-readiness, and eventually obtaining business value from modern data-driven approaches.
Before that, I obtained my PhD in applied Machine Learning research, namely Music Information Retrieval, supervised by Prof. Dr. Meinard Müller at the International Audio Laboratories Erlangen. I continued my research as a Post-Doc at the Institute for Computational Perception at JKU Linz, led by Prof. Dr. Gerhard Widmer. From 2019 to summer 2023, I led a team of data scientists at pmOne where we applied Machine Learning approaches to various industrial applications. Since fall 2023, I am professor for Data Science at Hochschule Weserbergland in Hameln.
A printable version of my curriculum vitae can be found here.
|Aug 1, 2023||Happy to announce that I was appointed full professor for Data Science (W2) at Hochschule Weserbergland in Hameln.|
|May 25, 2023||Another (now almost yearly) funding by “Deutsche Gesellschaft für Engagement & Ehrenamt” for financing instruments. We will use these instruments to establish “Musikalische Früherziehung”, an offering to get kids from 4-6 used to concepts of pitch and rhythm through singing and musical instruments.|
|Feb 23, 2023||Wow, through local crowd funding, we were able to collect money to buy high-quality chimes for the orchestra. Might produce a dataset for that soon…|
MTD: A Multimodal Dataset of Musical Themes for MIR ResearchTransactions of the International Society for Music Information Retrieval (TISMIR), 3(1), 180–192, 2020
Score Following as a Multi-Modal Reinforcement Learning ProblemTransactions of the International Society for Music Information Retrieval (TISMIR), 2(1), 67–81, 2019
Cross-Modal Music Retrieval and Applications: An Overview of Key MethodologiesIEEE Signal Processing Magazine, 36(1), 52–62, 2019