Michael Teichmann

Michael Teichmann is a Researcher at the Professorship of Artificial Intelligence, Department of Computer Science, Chemnitz University of Technology. He has held this position since April 2015, following his role as a PhD student (2012–2015) in the interdisciplinary Research Training Group 'Crossworlds,' which explored connections between virtual and real social environments in communication, emotions, sensomotorics, and learning.

Education:

• Dr. rer. nat. in Artificial Intelligence (2018), Chemnitz University of Technology. Dissertation: 'A plastic multilayer network of the early visual system inspired by the neocortical circuit.'
• Major in Computer Science with minors in Artificial Intelligence and Operation Research (2004–2010), Chemnitz University of Technology.

Research Focus: His work centers on biologically inspired computational models, including:

• Adaptive learning mechanisms in neural networks
• Visual perception and invariance learning
• Emotion-driven perceptual processing
• Robustness in intelligent systems under information loss

Publication Trends: His 15 most recent articles demonstrate a consistent focus on neural plasticity, bio-inspired vision systems, and computational neuroscience. Key thematic clusters include Hebbian learning stabilization, spiking neural networks for image processing, emotion-computer vision intersections, and competitive learning for enhanced robustness in feature detection.

Awards:

• University award for best computer science thesis (2010)

Affiliations: He operates within the Professorship of Artificial Intelligence lab, contributing to projects on neural modeling and vision systems. His prior involvement in the 'Crossworlds' research group emphasized interdisciplinary collaboration between computer science and social sciences.