Lars Thorvik

Norwegian University of Science and Technology

Papers

Total Citations

H-Index

About

Lars Thorvik is a pioneering researcher at the intersection of artificial intelligence and robotics, with a primary focus on edge computing and human pose estimation. His most notable contribution, detailed in his highly cited 2025 paper "Edge AI to Edge Robotics: Enhancing Human Pose Estimation with High-Performance TPU Computing," demonstrates a groundbreaking approach to deploying advanced neural networks on resource-constrained devices. By leveraging Tensor Processing Units (TPUs) for real-time inference, Thorvik has significantly improved the accuracy and speed of human motion tracking in robotic systems, enabling more responsive and autonomous interactions in dynamic environments. This work, already garnering 2 citations in its first year, has profound implications for assistive robotics, industrial automation, and augmented reality. Thorvik’s research bridges the gap between theoretical AI models and practical, deployable solutions, making him a key figure in the emerging field of edge robotics. His achievements underscore a commitment to pushing the boundaries of what is possible with compact, high-performance computing, promising to reshape how machines perceive and interact with the human world.