Summary
William Lindskog-munzing is a Solutions Engineer focused on federated AI systems, currently helping organizations adopt privacy-preserving, decentralized ML at Flower Labs. With six years of hands-on experience spanning industry and academia, he brings deep expertise in federated learning applied to automotive use cases, predictive maintenance, and personalized models. He led R&D at TUM.ai and mentored cohorts on advanced AI topics, bridging research prototypes to real-world deployments. His background includes a PhD track at TUM and practical projects from active learning for time-series maintenance to YOLO-based vision pipelines, reflecting both theoretical rigor and engineering pragmatism. Known for implementing personalization layers in open-source federated toolkits, he combines systems-level thinking with data-centric experimentation to make federated approaches production-ready.
6 years of coding experience
2 years of employment as a software developer
High School Diploma Natural Sciences, High School Diploma Natural Sciences at Fyrisskolan, Uppsala
Master of Science in Engineering Mathematics Artificial Intelligence Machine Learning Data Science, Master of Science in Engineering Mathematics Artificial Intelligence Machine Learning Data Science at The Faculty of Engineering at Lund University
Doctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at Technical University of Munich
Computer/Information Technology Administration and Management, Computer/Information Technology Administration and Management at ETH Zürich
Spanish, Spanish at EF Executive Language Institute
Spanish, Swedish, English, German