Jakub Pawlak

Jakub Pawlak is an AI and robotics researcher who completed his computer science studies at TU Kaiserslautern (2014-2022), specializing in robotics and artificial intelligence with a particular focus on domain adaptation and synthetic data generation for machine learning applications.
Currently, he is pursuing his Ph.D. at the Chair of Robot Systems at TU Kaiserslautern, where his research centers on advancing robust perception in robotic systems through generative deep learning methods, including GANs and style transfer. His work bridges the reality gap between simulation and real-world robotics applications through efficient data generation and knowledge transfer techniques. Recently, he has expanded his research into unsupervised and embodied learning approaches for autonomous robotic systems.