Agrograph
Scott is an electrical engineer with a background in signal processing and machine learning. He has almost two decades of experience working on problems in diverse areas such as finance/trading, biomedical, food production, and IoT. He is well-versed in most aspects of machine-learning problems from data infrastructure to the deployment of models in mission-critical production settings. He has an M.S.E.E. from Stanford University and a Ph.D. E.E. from the University of Illinois.
This person is not in any offices
Agrograph
Data solutions for ag lenders, crop insurers, ag services providers and specialty finance groups who anticipate trends, create pricing models and proactively manage risk.