Prof. Dr.-Ing. Uwe Handmann

Profile

Chairman of Neuroinformatics at Hochschule Ruhr West

Director of the Computer Science Institute
Dean of Faculty 1
Scientific Director of zdi-center Bottrop, Oberhausen and mint4u

Chairman of Prosperkolleg e.V.

Visiting Professor at Babeș-Bolyai-University Cluj
Expert in AI, sensor data fusion, computer vision, HCI, autonomous systems, predictive maintenance, twin transition, circular economy

Activities & Memberships

Promotionskolleg NRW (Section 'Computer- and Data-Science')
Institute Positive Computing at HRW
Prosperkolleg e.V.
Strategic Circle of zdi NRW (since 2018)
Advisory Board “Round Table Circular Economy NRW”
Monitoring Committee ERDF 2021–2027
Advisory Board “Umbau 21” 2017-2024

Selected Publications

[28]	J. Stehr, N. Abou Baker, and U. Handmann. From Chat to Grasp Using LLM-Controlled Dual Robot Arm. In 6th International Conference on Robotics, Computer Vision and Intelligent Systems (ROBOVIS 2026), Marabella, Spain, 2026. [ bib \| url \| pdf ]
[27]	N. Abou Baker and U. Handmann. The Hidden Price Tag Behind LLMs and Their Environmental Cost. In 15th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2026), pages 250–261, Marabelle, Spain, 2026. SciTePress. [ bib \| DOI \| url \| pdf ]
[26]	D. Rohrschneider, M. Pehlke, U. Handmann, and M. Jansen. Llm-based json mapping and blockchain integration for digital product passports. Digital Business, 2026. [ bib \| DOI \| url \| pdf ]
[25]	N. Abou Baker and U. Handmann. One size does not fit all: Benchmarking modelselection scores for image classification. Scientific Reports (Sci Rep), 14(30239):1–26, December 2024. [ bib \| DOI \| url \| pdf ]
[24]	N. Abou Baker, D. Rohrschneider, and U. Handmann. Parameter-efficient fine-tuning of large pretrained models for instance segmentation tasks. Machine Learning and Knowledge Extraction, 6(4):2783–2807, December 2024. [ bib \| DOI \| url \| pdf ]
[23]	S. Büttner, U. Handmann, and W. Irrek. Transformation zur Circular Economy - Kleine und mittlere Unternehmen im Wandel begleiten. Springer, July 2024. [ bib \| DOI \| url \| pdf ]
[22]	W. Irrek and U. Handmann. Sauber getrennt ist halb verwertet - Recycling mittels KI. IM+io Best & Next Practices aus Digitalisierung, Management, Wissenschaft, 2023(01):26–29, March 2023. [ bib \| url \| pdf ]
[21]	D. Rohrschneider, N. Abou Baker, and U. Handmann. Double transfer learning to detect lithium-ion batteries on x-ray images. In 17th International Work-Conference on Artificial Neural Networks (IWANN 2023), Ponta Delgada, Portugal, June 19 - 21, 2023, Proceedings, Part I, volume 14134 of Lecture Notes in Computer Science (LNCS), pages 175–188, Springer Nature, Switzerland, 2023. [ bib \| DOI \| url \| pdf ]
[20]	N. Abou Baker, N. Zengeler, and U. Handmann. A transfer learning evaluation of deep neural networks for image classification. Machine Learning and Knowledge Extraction, 4(1):22–41, 2022. [ bib \| DOI \| url \| pdf ]
[19]	N. Abou Baker, J. Stehr, and U. Handmann. Transfer Learning Approach towards a Smarter Recycling. In 31st International Conference on Artificial Neural Networks (ICANN 2022), Bristol, UK. Artificial Neural Networks and Machine Learning, volume 13529 of Lecture Notes in Computer Science (LNCS), pages 685–696, Springer, Cham, 2022. [ bib \| DOI \| url \| pdf ]
[18]	N. Zengeler, T. Glasmachers, and U. Handmann. Transfer Meta Learning. In 26TH International Conference on Pattern Recognition (ICPR 2022), pages 4471–4478, Montreal, Canada, 2022. [ bib \| DOI \| url \| pdf ]
[17]	N. Abou Baker, D. Rohrschneider, and U. Handmann. Battery detection of xray images using transfer learning. In The 30th European Symposium on Artificial Neural Networks (ESANN 2022), pages 241–246, Bruges, Belgium, 2022. [ bib \| DOI \| url \| pdf ]
[16]	I. Larson, K. Schwermer, and U. Handmann. Digital4u: Finde deinen Traumberuf! Schulwelt NRW, September 2021. [ bib \| pdf ]
[15]	M. Wehrmann, N. Zengeler, and U. Handmann. Observation Time Effects in Reinforcement Learning on Contracts for Difference. Journal of Risk and Financial Management, 14(2:54):1–15, 2021. MDPI, Basel, Switzerland. [ bib \| DOI \| url \| pdf ]
[14]	N. Abou Baker, P. Szabo-Müller, and U. Handmann. Transfer learning-based method for automated e-waste recycling in smart cities. EAI Endorsed Transactions on Smart Cities, 5(16):1–9, 4 2021. [ bib \| DOI \| url \| pdf ]
[13]	N. Zengeler and U. Handmann. Contracts for Difference: A Reinforcement Learning Approach. Journal of Risk and Financial Management - Special Issue 'AI and Financial Markets', 13(4:78):1–12, 2020. MDPI, Basel, Switzerland. [ bib \| DOI \| url \| pdf ]
[12]	N. Zengeler, U. Handmann, and Th. Kopinski. Hand Gesture Recognition in Automotive Human Machine Interaction. Sensors, 19(1;59):1–28, 2019. MDPI, Basel, Switzerland. [ bib \| DOI \| url \| pdf ]
[11]	C. Straßmann, S. Eimler, A. Arntz, D. Keßler, S. Zielinski, G. Brandenberg, V. Dümpel, and U. Handmann. Relax yourself - Using Virtual Reality to enhance employees mental health and work performance. In ACM CHI Conference on Human Factors in Computing Systems (CHI' 19), Glasgow, Scotland, 2019. [ bib \| DOI \| url \| pdf ]
[10]	C. Thiel, S. Sommer, L. Günther, A. Osterhoff, O. Koch, U. Handmann, and C. Grüneberg. Implementierung und erste Effekte Smartphone-unterstützter körperlich-kognitiver Aktivitäten im Quartier zur Förderung der sozialen Teilhabe älterer Menschen. In B&G - Bewegungstherapie und Gesundheitssport, volume 35, pages 235–245. Georg Thieme Verlag KG, 2019. ISSN 1613-0863. [ bib \| DOI \| url \| pdf ]
[9]	Th. Kopinski, F. Sachara, A. Gepperth, and U. Handmann. A Deep Learning Approach for Hand Posture Recognition From Depth Data. In Artificial Neural Networks and Machine Learning (ICANN 2016), volume 9887 of Lecture Notes in Computer Science (LNCS), pages 179–186. Springer Verlag, 2016. [ bib \| DOI \| url \| pdf ]
[8]	J. M. Pawlowski, S. C. Eimler, M. Jansen, J. Stoffregen, S. Geisler, O. Koch, G. Müller, and U. Handmann. Positive computing. Business & Information Systems Engineering, 57(6):405–408, 2015. Springer, Heidelberg, Germany. [ bib \| DOI \| url \| pdf ]
[7]	A. Siddiqui, O. Koch, A. Rabie, and U. Handmann. Personalized and adaptable mhealth architecture. In 4th International Conference on Wireless Mobile Communication and Healthcare - 'Transforming healthcare through innovations in mobile and wireless technologies' (MOBIHEALTH 2014), pages 381 – 384, Athens, Greece, 2014. [ bib \| DOI \| url \| pdf ]
[6]	S. Hommel, A. Rabie, and U. Handmann. Attention and emotion based adaption of dialog systems. In Intelligent Systems: Models and Applications, Topics in Intelligent Engineering and Informatics, volume 3 (4), pages 215–235. Springer Verlag, Berlin, Heidelberg, Germany, 2013. [ bib \| DOI \| url \| pdf ]
[5]	U. Handmann, S. Hommel, M. Brauckmann, and M. Dose. Face detection and person identification on mobile platforms. In Towards Service Robots for Everyday Environments - Springer Tracts in Advanced Robotics (STAR), volume 76, pages 227–234. Springer Verlag, Berlin, Heidelberg, Germany, 2012. [ bib \| DOI \| url \| pdf ]
[4]	S. Wiegand, C. Igel, and U. Handmann. Evolutionary multi-objective optimization of neural networks for face detection. International Journal of Computational Intelligence and Applications, 4(3):237–253, 2004. [ bib \| DOI \| url \| pdf ]
[3]	W. v.Seelen, J. Gayko, U. Handmann, and T. Kalinke. Scene analysis and organization of behavior in driver assistance systems. In International Conference on Image Processing; IEEE Signal Processing Society, Vancouver, Canada, Proceedings, volume 3, pages 524–527, 2000. [ bib \| DOI \| url \| pdf ]
[2]	U. Handmann. Neuronale Informationsverarbeitung für Fahrerassistenzsysteme. Logos-Verlag, Berlin, Germany, 2000. [ bib \| url ]
[1]	U. Handmann, T. Kalinke, C. Tzomakas, M. Werner, and W. v.Seelen. An image processing system for driver assistance. Image and Vision Computing, Elsevier Science, 18(5):367–376, 2000. [ bib \| DOI \| url \| pdf ]