Research Foci
- Artificial Neural Networks in the context of Intelligent Matter
- Artificial Neural Networks for depth estimation in event-based neuromorphic vision
CV
Academic Education
- PhD student: Artificial Neural Networks in the context of Intelligent Matter (CRC1459), Computer Vision and Machine Learning Systems (University of Münster)
- PhD student: Artificial Neural Networks for Wildlife Tracking (Scholarship), Institute for Geoinformatics (University of Münster)
- PhD student: Simultaneous Localization, Mapping and Moving Object Tracking (SLAMMOT), CNRS I3S (University Côte d'Azur) and Istituto Italiano di Tecnologia
- Master’s degree in electrical engineering, Technical University of Braunschweig
- Bachelor’s degree in industrial engineering (specialization electrical engineering), Technical University of Braunschweig
WorkExperience
- Research engineer, Volkswagen Group
Conference Contributions
- Becker, M., Konrad, J., Rodriguez, LG., & Risse, B. (). Random Label Prediction Heads for Studying and Controlling Memorization in Deep Neural Networks. in Vondrick, C., Hariharan, B., Faust, A., Pinto, L., Yang, D., Raffel, C., & Xue, Z. (ed.), The Fourteenth International Conference on Learning Representations (ICLR) (pp. 1–8). OpenReview.
- Garcia Rodriguez, L., Konrad, J., Drees, D., & Risse, B. (). S-ROPE: Spectral Frame Representation of Periodic Events. in Del Bue, A., Canton, C., Pont-Tuset, J., & Tommasi, T. (ed.), Lecture Notes in Computer Science: Vol. 15646. Computer Vision – ECCV 2024 Workshops (pp. 307–324). Springer Nature. doi: 10.1007/978-3-031-92460-6.
- Schomerus, V., Konrad, J., Schult, J., Holdegel, M., & Johansson, M. (). Fahrzeugumfeldwahrnehmung für automatische Fahrfunktionen mit Convolutional Neural Networks. in ITS mobility e. V. (Herausgebendes Organ) (ed.), AAET - Automatisiertes und vernetztes Fahren: Beiträge zum gleichnamigen 19. Braunschweiger Symposium am 14. und 15. März 2018, Stadthalle, Braunschweig (pp. 273–293). Braunschweig: ITS mobility e.V..