Prof. Dr.-Ing. Alexander Lampe

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Faculty Engineering Sciences

Chair in Signal and System Theory

Prof. Dr.-Ing. Alexander Lampe
FakultƤt Ingenieurwissenschaften
+49 3727 581201
lampe@hs-mittweida.de
3-103
Visitor address
Am Schwanenteich 4a
09648 Mittweida
3-103
Postal address
Mittweida University
FakultƤt Ingenieurwissenschaften
Technikumplatz 17
09648 Mittweida

Teaching

  • Signal and System Theory
  • Digital Signal Processing
  • Image Processing and Machine Vision
  • Stochastic processes with applications in signal processing
  • Artificial Intelligence ā€“ Fundamentals and Applications
  • Artificial Intelligence ā€“ Frameworks and Applications
  • Selected chapters on AI and data science
  • Fundamentals of quantum computing

  • Industrial AI
  • Intelligent algorithms for digital signal processing, with a focus on image and sensor
     data processing

Career

Prof. Dr.-Ing. Alexander Lampe was born in Leipzig in 1970. He studied electrical engineering at the University of Erlangen-Nuremberg, graduating in 1998 with a degree in engineering (Dipl.-Ing.). In 2003, he was awarded a doctorate in engineering (Dr.-Ing.) from the same university.

After completing his studies, he worked from 2002 to 2009 in the field of research and development of mobile communications algorithms and chips at Philips Semiconductors, NXP and ST-Ericsson. Since 2009, he has been Professor of Signal and System Theory at Mittweida University of Applied Sciences.

His teaching areas include, amongst others, signal and system theory, stochastic processes in signal processing, as well as artificial intelligence and quantum computing.

His current research focuses on industrial AI and intelligent algorithms for digital signal processing, with an emphasis on image and sensor data processing.
 

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Projects and Publications

Entwicklung AI Agent Phase 0

  • Term: 2024/08/05 ā€“ 2025/12/31
  • Financed by: Stadler Chemnitz GmbH
  • Project managers: Alexander Lampe
2816 Alexander Lampe

AI in the Loop

  • Term: 2022/01/01 ā€“ 2024/12/31
  • Financed by: Deutsches Zentrum fĆ¼r Luft- und Raumfahrt e.V.
  • Project managers: Alexander Lampe
2340 Alexander Lampe

Innovationscluster HSMW 2021, AP 9-19: Forschungsanschub zur Steigerung der DrittmittelfƤhigkeit der Hochschule

  • Term: 2021/07/01 ā€“ 2021/12/31
  • Financed by: SƤchsisches Staatsministerium fĆ¼r Wissenschaft, Kultur und Tourismus
  • Project managers: Alexander Lampe
2346 Alexander Lampe

Nachwuchsforschergruppe MaLeKITA Maschinelles Lernen und KI in Theorie und Anwendungen, MaLeKITA Technik

  • Term: 2019/09/06 ā€“ 2022/12/31
  • Financed by: SƤchsische Aufbaubank
  • Funding code: 100381749
  • Project managers: Alexander Lampe
2134 Alexander Lampe

Entwicklung, EinfĆ¼hrung und Test eines Ausbildungsangebotes mit dem Schwer-punkt Automatisierungstechnik, TU Jiangsu (F+U Sachsen gGmbH)

  • Term: 2018/01/15 ā€“ 2019/12/31
  • Financed by: F+U Sachsen gGmbH
  • Project managers: Alexander Lampe
2352 Alexander Lampe
C. Schrƶder, R. Bƶhm, A. Lampe

Comparison of Autoscaling Frameworks for Containerised Machine-Learning-Applications in a Local and Cloud Environment

Presented on: 2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI), 2024
21031 konferenzpaper
M. Ritter, N. Hentschel, T. Kaminsky, M. Vodel, A. Sieber, M. Marasas, R. Beier-Grunwald, C. Roschke, I. Heinze, A. Lampe

Raspberry Pi Controller for Remote Laboratory Hardware Access

Presented on: The Sixteenth International Conference on Mobile, Hybrid, and On-line Learning - eLmL 2024, 2024
21015 konferenzpaper
A. Lampe, C. Scholz, C. Kƶnig, D. Beger, E. Weinhold, F. Matthes, K. Hallmann, M. Ritter, M. Achilles, M. Schweizer, R. Beier-Grunwald, C. Roschke, M. Vodel

Enhancing Digital Learning: A User Management and Access System for Remote Laboratories

Presented on: The Fifteenth International Conference on Mobile, Hybrid, and On-line Learning - eLmL 2023, 2023
20861 konferenzpaper
D. Staps, R. Schubert, M. Kaden, A. Lampe, W. Hermann, T. Villmann

Prototype-based One-Class-Classification Learning Using Local Representations

Appeared in: 2022 International Joint Conference on Neural Networks (IJCNN), 2022
15833 konferenzpaper
J. Schulte, D. Staps, A. Lampe

A feasibility study of deep neural networks for the recognition of banknotes regarding central bank requirements

Appeared in: arXiv, 2019
20930 konferenzpaper
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