My passions include understanding human behavior at mass scale and leveraging those insights to build truly transformative experiences that improve as many lives as possible. Specifically, I develop algorithms and control systems that are focused on product needs and develop analytical teams around those designs to take those and other emergent ideas to scale. Fundamentally, I believe that data science is NOT machine learning, but is an iterative quantitative science that uses many different domains including experimental design, closed form algorithms, statistical learning (ML), dynamic visualization, etc. to use data to improve products. I have over 12 years of experience researching and managing data/algorithms in: psychometrics, human-machine interaction, psychophysics, biophysics, robotics, MRI, image processing, machine vision, time-series algorithms, matching, recommendation, & reinforcement algorithms, animal-models, control systems, cost-optimization models, and iterative bayesian methods. Interests: - unstructured statistical learning systems. - knowledge graphs. - Non-sparse, dynamic models of latent traits. - Scalable tools for psychological assessment based upon validated theoretics and coupling them with conical digital metrics. - Business optimization models. - Sequential interaction models for dynamic personalization (e.g. Risk trending, Acute Financial Stress and online Cognitive Behavioral Therapy tools) - Advising early stage companies and data-driven initiatives. - World-wide education in science, and specifically data science Skills: - Professional Nerd - Bayesian Ninja