About
Patrik Rydén is a Professor of Mathematical Statistics at the Department of Mathematics and Mathematical Statistics, Umeå University, where he applies statistical methods to complex datasets. He also directs the Industrial Doctoral School for Research and Innovation, fostering academia-industry collaboration. His research spans healthcare (ambulance logistics, cancer diagnostics), industrial optimization (automotive quality control), and bioinformatics.
Research Focus
Rydén develops data-driven methodologies for:
- Healthcare: Optimizing ambulance deployment, predicting patient care times, and modeling disease spread.
- Industry: Statistical process control for manufacturing and quality improvement.
- Bioinformatics: Cancer subtype identification and vaccine efficacy modeling.
Publication Trends
His recent work emphasizes applied statistics in healthcare (40%), industrial machine learning (30%), and genomic analysis (30%), with strong themes in predictive modeling, spatio-temporal analysis, and high-dimensional data interpretation.
Leadership & Projects
As director of the Industrial Doctoral School, he bridges academic research with industry needs. Key projects include:
- Predicting post-anesthesia care time using ML (2022–2027)
- Data-driven prehospital care optimization (2018–2028)
- Statistical learning for industrial defect detection (2017–2023)
