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Chair of Cognitive Material Analytics (gemeinsame Berufung mit Fraunhofer IKTS Dresden) Prof. Dr.-Ing. Constanze Tschöpe

Dr.-Ing. Ivan Kraljevski

Scientific Assistant
(Fraunhofer project group KogMatD)

Building 3A, Room 333
T +49 (0) 355 60 5112
ivan.kraljevski(at)ikts.fraunhofer.de

Ivan Kraljevski was born in Emmen in the Netherlands in 1974. He received a B.Sc. degree in Electronics and Telecommunications in 1997, an M.Sc. degree in Computer Technology and Informatics in 2000 and a Ph.D. degree in 2004, all from the Faculty of Electrical Engineering and Information Technology at the University "St. Cyril and Methodius" in Skopje, Macedonia. From October 2011 to September 2013, he worked as a researcher in the field of speech technology at the Institute of Acoustics and Speech Communication (IAS), TU Dresden, Germany. From October 2013 to May 2019, he was employed as a research and development engineer at voiceINTERconnect GmbH in Dresden, Germany. He is currently a research associate in the project group "Cognitive Material Diagnostics" at the Fraunhofer Institute for Ceramic Technologies and Systems (IKTS). His scientific and professional interests include speech and audio signal processing, speech technology, pattern recognition and artificial neural networks.

  • I. Kraljevski, F. Duckhorn, Y. C. Ju, C. Tschöpe, M. Wolff. Acoustic Resonance Testing of Glass IV Bottles. In Proc. International Conference on Artificial Intelligence Applications and Innovations (AIAI), Part II, S. 195–206, Springer, 2020, doi: https://doi.org/10.1007/978-3-030-49186-4_17
  • I. Kraljevski, F. Duckhorn, Y. C. Ju, C. Tschöpe, C. Richter, M. Wolff. Acoustic Resonance Recognition of Coins. In Proc. IEEE International Instrumentation and Measurement Technology Conference (I2MTC), S. 1–6, 2020, doi: 10.1109/I2MTC43012.2020.9129256. 
  • I. Kraljevski, F. Duckhorn, C. Tschöpe, M. Wolff. Convolutional Autoencoders for Health Indicators Extraction in Piezoelectric Sensors. In Proc. IEEE SENSORS, 1–4, 2020. doi: 10.1109/SENSORS47125.2020.9323023.
  • I. Kraljevski, M. Rjelka, F. Duckhorn, C. Tschöpe, M. Wolff. Cross-Lingual Acoustic Modeling in Upper Sorbian – Preliminary Study. In Proc. Elektronische Sprachsignalverarbeitung (ESSV). B. Weiß (Hrsg.): Studientexte zur Sprachkommunikation, TUDpress Dresden, 2021
  • I. Kraljevski, F. Duckhorn, C. Tschöpe, M. Wolff. Machine Learning for Anomaly Assessment in Sensor Networks for NDT in Aerospace. IEEE Sensors Journal 21, no. 9 (2021): 11000-11008, doi: 10.1109/JSEN.2021.3062941 
  • I. Kraljevski, M. P. Bissiri, F. Duckhorn, C. Tschöpe, M. Wolff. Glottal Stops in Upper Sorbian: a Data-Driven Approach. In Interspeech, pp. 1001-1005. 2021. http://dx.doi.org/10.21437/Interspeech.2021-1101.  
  • I. Kraljevski, F. Duckhorn, M. Barth, C. Tschöpe, F.Schubert, M. Wolff. Autoencoder-based Ultrasonic NDT of Adhesive Bonds. In 2021 IEEE Sensors, pp. 1-4. IEEE, 2021. https://doi.org/10.1109/SENSORS47087.2021.9639864.
  • C. Tschöpe, I. Kraljevski, F. Duckhorn, M. Wolff. Sprachtechnologie und akustische Mustererkennung in der medizinischen Anwendung. 16. Landeskonferenz „Digitalisierung im Gesundheitswesen“, Potsdam, 24.02.2021
  • C. Tschöpe, M. Mühle, Y. C. Ju, I. Kraljevski, M. Wolff. Künstliche Intelligenz in der ZfP – Welchen Beitrag kann KI in der ZfP leisten? DGZFP-Jahrestagung, 2021. https://www.ndt.net/article/dgzfp2021/papers/19.pdf.
  • Y.C. Ju, I. Kraljevski, H. Neunübel, C. Tschöpe, M. Wolff. Acoustic Resonance Testing of Small Data on Sintered Cogwheels. Sensors 2022, 22, 5814. https://doi.org/10.3390/s22155814
  • I. Maier, J. Kuhn, F. Duckhorn, I. Kraljevski, D. Sobe, M. Wolff, C. Tschöpe. Word Class Based Language Modeling: A Case of Upper Sorbian. In Proceedings of The Workshop on Resources and Technologies for Indigenous; Endangered and Lesser-resourced Languages in Eurasia within the 13th Language Resources and Evaluation Conference, pp. 28-35, European Language Resources Association, 2022.
  • R. R. Schmidt, J. Hildebrand, I. Kraljevski, F. Duckhorn and C. Tschöpe. A Study for Laser Additive Manufacturing Quality and Material Classification Using Machine Learning. 2022 IEEE Sensors, Dallas, TX, USA, 2022, pp. 1-4, doi: 10.1109/SENSORS52175.2022.9967311
  • I. Kraljevski, F. Duckhorn, C. Tschöpe, F. Schubert, M. Wolff. Paper Tissue Softness Rating by Acoustic Emission Analysis. Appl. Sci. 2023, 13, 1670. https://doi.org/10.3390/app13031670
  • I. Kraljevski, C. Tschöpe, M. Wolff. Limits and Prospects of Big Data and Small Data Approaches in AI Applications. In AI - Limits and Prospects, transcript Verlag, 2023, http://dx.doi.org/10.14361/9783839457320-006
  • I. Kraljevski, Y. C. Ju, D. Ivanov, C. Tschöpe, M. Wolff. How to Do Machine Learning with Small Data? – A Review from an Industrial Perspective, arXiv preprint arXiv:2311.07126, 2023, http://dx.doi.org/10.48550/arXiv.2311.07126
  • I. Kraljevski, F. Duckhorn, D. Sobe, C. Tschöpe, M. Wolff. Preserving Language Heritage Through Speech Technology: The Case of Upper Sorbian, International Conference on Speech and Computer, 2024, Springer Nature Switzerland Cham., http://dx.doi.org/10.1007/978-3-031-77961-9_1
  • H. Li, I. Kraljevski, P. Meyer, C. Tschöpe, M. Wolff. YOLO-ICP: Deep Learning Integrated Pose Estimation for Bin-Picking of Multiple Objects, 2024 IEEE SENSORS, 2024, IEEE, http://dx.doi.org/10.1109/SENSORS60989.2024.10784539
  • I. Kraljevski, Y. C. Ju, M. Mühle, D. Lembcke, S. Uhlig, M. Käso, I. Alkhasli, C. Tschöpe. Setup and Knowledge Sharing of the new Fraunhofer Research Group for Cognitive Material Diagnostics. KM2021 Conference, Pre-Conference Industry Day, Leipzig, 29.06.2021. (Invited Talk)
  • C. Tschöpe, I. Kraljevski, F. Duckhorn, M. Wolff. Sprachtechnologie und akustische Mustererkennung in der medizinischen Anwendung. 16. Landeskonferenz »Digitalisierung im Gesundheitswesen«, Potsdam, 24.02.2021.

Lecture: Artificial Intelligence in Material Diagnostics

Supervised theses

  • Dario Lembcke: Klanganalyse mit Methoden des maschinellen Lernens am Beispiel einer Münzerkennung, Master thesis, BTU Cottbus-Senftenberg, 2020 (in cooperation with Chair of Programming Languages and Compiler Construction).
  • Maximilian Gast: Datensammlung zur Erkennung metallischer Bauteile, Bachelor thesis, BTU Cottbus-Senftenberg, 2022 (in cooperation with Chair of Communication Technology).

Researchgate profile