Dávid Terjék
Assistant Research Fellow, Artificial Intelligence Research Department, HUN-REN Alfréd Rényi Institute of Mathematics
Professional profileDávid Terjék is an Assistant Research Fellow in the Artificial Intelligence Research Department at the HUN-REN Alfréd Rényi Institute of Mathematics. He earned his MSc in Computer Science Engineering with highest honours from the Budapest University of Technology and Economics, specialising in computer graphics and artificial intelligence. Prior to his current role, he spent two years as a research engineer in the Advanced Engineering team at Bosch, where he initiated deep learning research and advanced to the position of Lead Engineer.
His research interests include deep generative models, regularisation of neural networks, information theory, and optimal transport. Notably, he authored the paper "Adversarial Lipschitz Regularization," which was presented at the 8th International Conference on Learning Representations (ICLR) in 2020.
Currently, he is a participant in the "Mathematical Foundations of Artificial Intelligence" project, which aims to integrate theoretical and applied research to support domestic practical applications and connect Hungary to international research networks.