Jorge Ortiz recently spent 5 years at IBM Research working on machine learning for cyber-physical systems and the Internet-of-Things. His work applies machine learning techniques to problems in intelligent infrastructure systems and smart health applications. He has examined how learning techniques can be used to identify human activities using mobile phones, how to create models that can run on resource-constrained devices with small data, and has created tools that use machine learning to assist in the interaction between humans and cyber-physical systems. His work has also examines how to build smarter systems in the built environment, allowing buildings to integrate more easily with existing software and identify anomalous energy use patterns. The goal of his work is to make sensor-based systems smarter, trustworthy, and easier to use.
He attained his M.S. and Ph.D. in Computer Science from UC Berkeley (2010, 2013), and B.S. in Computer Science from the Massachusetts Institute of Technology (2003).