Julian Hoever, M.Sc.

Portrait photo of Julian Hoever in front of a grey/blue background

Short CV

Julian Hoever, M.Sc., has been working as a research assistant at the Department of Intelligent Embedded Systems in the Faculty of Computer Science at the University of Duisburg-Essen since June 2024. He completed his Bachelor's degree in Applied Computer Science at the University of Duisburg-Essen. He then completed a Master's degree in Cyber Physical Systems at the same university in May 2024. His master's thesis focused on the application of knowledge distillation to precomputable neural networks for FPGAs.

Research

He is currently employed for the ZaKI.D project. The aim of this project is to make artificial intelligence accessible to companies in and around Duisburg. Within the framework of small projects and training programs, a transfer of knowledge to companies is to be made possible. One relevant technology that is the focus of his research is knowledge distillation. Knowledge distillation makes it possible to develop more efficient and accurate AI models, which makes this technique particularly interesting for the ZaKI.D projects.

M. Sc. Julian Hoever

Informatik / AI

Address
Bismarckstr. 90
47057 Duisburg
Room
BC 205
Phone
+49 203 37 91803
E-Mail
julian.hoever@uni-due.de

Functions

  • Wissenschaftliche/r Mitarbeiter/in, Intelligente Eingebettete Systeme

Current lectures

The following publications are listed in the online university bibliography of the University of Duisburg-Essen. Further information may also be found on the person's personal web pages.

    Journal articles

  • Ling, Tianheng; Qian, Chao; Klann, Theodor Mario; Hoever, Julian; Einhaus, Lukas; Schiele, Gregor
    Configurable Multi-Layer Perceptron-Based Soft Sensors on Embedded Field Programmable Gate Arrays : Targeting Diverse Deployment Goals in Fluid Flow Estimation
    In: Sensors, Vol. 25, 2025, Nr. 1, 83
    DOI (Open Access)

    • Book chapters / Proceedings papers

  • Einhaus, Lukas; Maman, Natalie; Hoever, Julian; Erbslöh, Andreas; Schiele, Gregor
    Demo: Deriving LUT-based Neural Network Hardware Accelerators for Tiny Smart Sensor Systems
    In: Proceedings of the International Conference on Smart Computing Workshops and Other Affiliated Events (SMARTCOMP Companion 2026) / International Conference on Smart Computing Workshops and Other Affiliated Events (SMARTCOMP Companion 2026); 22-25 June 2026; Messina, Italy / Institute of Electrical and Electronics Engineers (IEEE) (Eds.). Piscataway: IEEE, 2026, pp. 409 – 411
    DOI, Online Full Text
  • Einhaus, Lukas; Maman, Natalie; Hoever, Julian; Erbslöh, Andreas; Schiele, Gregor
    Precomputed 1D-CNNs for Atrial Fibrillation Detection on Tiny Smart Sensor Systems
    In: 2026 IEEE International Conference on Smart Computing (SmartComp) / 2026 IEEE International Conference on Smart Computing (SmartComp), 22-25 June 2026, Messina, Italy. Piscataway: Institute of Electrical and Electronics Engineers Inc., 2026, pp. 9 – 16
    DOI