My publications are best read as Statistical Modeling and Applied AI/ML case studies. Across different domains (including simulation-based VR training), I work end-to-end: turning noisy real-world data into clean features, building and validating models, and translating results into decisions you can act on. 

Below you’ll see projects led to publications that combine machine learning, time-series analysis, and modern inference (e.g., latent-variable, VAE and SEM-style modeling).

My project in other domains (e.g. Image processing, Machine vision, Chaos and non-linear dynamics) which did not lead to publications, are mentioned in Projects section.