Jacob Lindbäck

Jacob Lindbäck is a doctoral student at KTH Royal Institute of Technology, affiliated with the Division of Decision and Control Systems and the Wallenberg AI, Autonomous Systems and Software Program (WASP). His research focuses on the analysis and development of scalable optimization algorithms for machine learning, particularly computational optimal transport and its applications.

Key research areas:

• Machine Learning
• Optimization Algorithms
• Optimal Transport
• Computational Mathematics

Publications highlight advancements in GPU-accelerated splitting methods for optimal transport, novel algorithms, and computational efficiency. He also contributes as an assistant for the course Modelling of Dynamical Systems (EL2820).