Jeff McGehee’s career has been focused on applying computation to engineering problems—the majority of which have involved simulation, calibration, system control, and optimization. The more he’s studied machine learning, the more he’s become motivated to understand how it can be applied effectively to complex problems in the real (engineering) world.
At Very, he brings his applied mathematics and machine learning knowledge to a wide array of problems and projects involving images, natural language, social graphs, temporal data, and geospatial data. Before joining Very, Jeff was a research and design engineer at Variable, Inc., where he developed proprietary mathematical models for accurate color measurement; set up a scientific analysis python environment with custom modules for internal company use; and built and deployed internal tools allowing non-technical workers to apply machine learning models. (Among other things.)