Ahmed Abbasi Research Group

The lab develops human-centered analytics and machine learning methods for modeling behavior in health and online communities using deep learning, psychometric NLP, and multimodal feature fusion. Researchers build and evaluate large-scale digital experimentation platforms and design robustness methods to detect distribution shifts and adversarial conditions through predictive modeling and evaluation. The group applies high-dimensional deep document and hierarchical models to extract personality, psychometrics, and adverse-event signals from textual and search data for health monitoring. The lab integrates interdisciplinary computational, statistical, and experimental methods to frame, evaluate, and solve applied problems in trustworthy AI.