Wylie Stroberg

Wylie Stroberg is an Assistant Professor in the Department of Mechanical Engineering within the Faculty of Engineering at the University of Alberta. He leads the Computational BioSystems Lab, where he conducts research at the interface between cell biology, physiology and engineering using a range of computational and theoretical techniques.

His research interests span multiple areas including:

• Biomechanics and Biomedical Engineering
• Biomaterials Mechanics and Materials
• Composites and Polymers
• Nano and Micro Materials
• Computational Mechanics
• Systems Biology of Proteostasis and the Unfolded Protein Response
• Reactions in Crowded Cellular Compartments
• Wetting Phenomena of Nanoscale Structures

Dr. Stroberg's research focuses on developing new quantitative techniques for studying complex biological systems across disparate length and time scales. His work has significant implications for understanding cellular physiology, protein homeostasis, and developing new therapeutic approaches for age-associated and protein folding diseases. He employs advanced computational methods including multiscale modeling, machine learning, and theoretical analysis to investigate biological phenomena from the molecular to cellular level.

His research group has published extensively in mathematical biology and computational mechanics, with a consistent focus on enzyme kinetics, cellular stress responses, and computational modeling of biological processes. The publications demonstrate a strong interdisciplinary approach combining techniques from mechanical engineering, computational science, and molecular biology.

Dr. Stroberg has received recognition for his work in mathematical biology and systems biology, with publications in journals such as the Journal of Theoretical Biology, Biophysical Journal, and Mathematical Biosciences.

He currently advises several graduate students working on diverse projects including multiscale modeling of enzymatic nanosensors, protein-based modulation of endoplasmic reticulum shape, development of machine learning-based coarse grained models for high-entropy alloys, and simulation of high-entropy alloys for thermal-spray deposition. His lab has trained undergraduate and master's students who have gone on to further academic pursuits.

The Computational BioSystems Lab maintains active collaborations with other researchers at the University of Alberta and beyond, working at the intersection of engineering, biology, and computational science.