Prior to co-founding Predikto, Inc., Robert was an award winning Associate Professor of Criminology (with tenure) at the University of Texas at Dallas. At UTD, he taught a variety of courses covering advanced data analytics (machine learning) for the social sciences and for operations research. He has published over 60 peer-reviewed journal articles across many disciplines in outlets such as PLoS One, Journal of Quantitative Criminology, Justice Quarterly, Intelligence, etc.
Robert’s expertise lies machine learning approaches for longitudinal processes to predict human (criminal) behavior. However, he now applies this philosophy into Predikto’s patent pending automated machine learning platform, which has been successful predicting unplanned events across a wide range of industrial assets including: freight locomotives (electric and diesel), high-speed (bullet) trains, rail cars, commercial aircraft, wayside detectors, quay cranes, consumer vehicles and batteries, commuter train doors, steel manufacturing equipment, datacenter HVAC, and more.
Robert holds a Ph.D. in criminology from Sam Houston State University; MA and BA from the University of Texas at Arlington.