Guowen Song

Dr. Song's research centers on the design and development of next-generation personal protective systems, integrating expertise across textile materials, end-use products, and environmental sciences. A core aspect of his work involves advanced hazard simulation, which includes cellular and animal models to evaluate biological responses to hazardous exposures—bridging the fields of microbiology, toxicology, and exposure science.
Using cutting-edge numerical modeling and laboratory simulations, his team conducts in-depth analyses to understand how protective systems perform under complex, real-world conditions. This scientific insight is translated into practical tools, technologies, testing methods, standards, and protective solutions that inform system-level design and development.
His research also addresses critical challenges such as contamination and decontamination, extremity protection, and optimization of product fit and sizing through AI-aided anthropometric modeling. By combining materials innovation with biological hazard evaluation, Dr. Song’s work advances the creation of safer and more intelligent protective systems.
Committed to a systematic and convergent research strategy, Dr. Song is leading efforts to incorporate AI and machine learning-powered models and simulations, aiming to develop intelligent interfaces that elevate human-centered system design in occupational and environmental health contexts.