Large-Scale Spatio-Temporal Reasoning and Learning
Title: Large-Scale Spatio-Temporal Reasoning and Learning
DNr: Berzelius-2024-84
Project Type: LiU Berzelius
Principal Investigator: Fredrik Heintz <>
Affiliation: Linköpings universitet
Duration: 2024-03-01 – 2024-09-01
Classification: 10201


The goal of our research is to develop novel reasoning and learning methods for large-scale spatio-temporal applications. This includes for example time-series learning (diffusion models and GANs) and multi-agent reinforcement learning. The expected scientific impact is publications in top-level conferences and the expected soecity impact is more effective decision-making methods for autonomous systems such as unmanned aircraft, more effective transporation solutions and methods for privacy-preserving synthetic data generation.