I use quantitative modeling and simulation to evaluate how well a product or system fits and accommodates the people who use it, answering questions like “will this design work for 90% of my users” , or “which users may be disaccommodated by the constraints?” This includes configuring and applying digital human models, conducting statistical accommodation analyses using anthropometric, posture, and preference data, and translating results into design recommendations. I have applied these methods extensively for the Army, but the underlying techniques are relevant to any domain where product fit, reach, clearance, or physical usability matters — from vehicle and workstation design to medical devices and consumer products.

I model and analyze how humans perform in complex systems, predicting metrics like workload, task time/accuracy,  and situation awareness under both realistic and extreme operational conditions. Using task network modeling and simulation, I help teams understand human performance risks early in the design process, before hardware is built and failures become expensive. I also work on integrating human performance models with broader engineering simulation environments, so that human factors considerations can be evaluated alongside technical system performance rather than as an afterthought.

I design, build, and apply analytical software tools and data collection systems that make human factors methods practical for analysts and decision-makers. This spans the full development lifecycle: identifying analytical gaps, designing interfaces, building software across web, mobile, and desktop platforms, and deploying and evaluating those tools with users in field environments. I also leverage AI-assisted development workflows to accelerate development and documentation. My experience building data collection apps spans small-scale usability studies to large, complex field experimentation events, but the skills transfer to product testing, UX research, and applied human factors in any domain.