Chief Technology Officer

As CTO, Christopher will identify technological and developmental requirements for customer delivery and manage execution of strategic technical development to meet customer requirements and solution enhancements. He is developing forecasting systems and end-to-end deep topological approaches geared toward large-scale machine learning, inference, and explainability. Christopher's research interests are designing scalable and explainable probabilistic models of multimodal data, Bayesian nonparametric models, and Bayesian deep learning. ‍ Christopher has a PhD from the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Lab (CSAIL). He also earned his Master’s at MIT in Electrical Engineering and Computer Science and his Bachelor’s in Computer Science and Engineering from The Ohio State University. In his spare time, Christopher enjoys cycling, brewing beer, baking, and traveling.