Since July 2021, FESTO, a company specialized in control and automation technology, has been deepening its collaboration with the University of Tübingen by means of an Industry-on-Campus project led by Dr. Shahram Eivazi (AI researcher at FESTO).
The initial focus is on Deep Reinforcement Learning for robotics, which combines neural networks with reinforcement learning: The robot tries to achieve a given goal through trial-and-error. Based on the feedback it receives, it gradually optimizes its actions until it successfully solves the task. Meta learning, edge AI, AutoMachineLearning approaches, distributed learning, and generative models are other AI fields that will be investigated in an application-oriented manner. The potential for AI-based applications to increase overall plant effectiveness in production is enormous. The results are therefore continuously incorporated into existing and new AI applications made by FESTO.
Dr. Shahram Eivazi (AI research scientist at Festo) received his PhD in Finland in 2016 on the topic of hands-free surgical microscope.
During his PhD he researched human computer interactive technologies (i.e. eye tracking) in medical domain. After PhD, he held a postdoctoral research position at Tübingen University in the group of Prof. Dr. Enkelejda Kasneci for two years. Eivazi's work focuses on research and emerging technology strategy for AI products in robotic industry. When developing application as a machine learning researcher, he workes on deep learning and reinforcement learning algorithms. With over 30 scientific publications and several years of active teaching experience Dr. Eivazi is leading the FESTO Autonomous Systems lab at Tübingen University.