Computational Modeling & Data Analysis

Experience using computational and quantitative methods to analyze biomedical data, model physiological systems, and extract meaningful information from complex experimental measurements.

My work has included biomechanical and musculoskeletal modeling of upper-limb movement, neural and physiological signal analysis, feature extraction, statistical modeling, and the development of algorithms for predicting or classifying physiological states and behaviors.

I have applied machine-learning methods including logistic regression, linear and quadratic discriminant analysis, k-nearest neighbors, and artificial neural networks to biomedical data. Applications have included decoding information from EEG and other physiological measurements and evaluating relationships between measured signals and human performance.

Across these applications, computational methods serve as tools for answering the underlying biomedical question. I select analytical approaches based on the physiology, experimental design, characteristics of the available data, and intended application rather than treating a particular modeling technique as the objective itself.