Title: Applied Mathematician – Algorithm Design & Development
Company: General Motors
Brief Bio: Dana Suttman works for General Motors currently in the Next Generation Controls group developing the future of methods for embedded vehicle software by leveraging Machine Learning(ML). She also held a role at GM in Product Development Analytics optimizing cost for supplier footprint of vehicle parts sourcing across the globe. Dana also spent time at FCA applying ML to powertrain modeling and optimization for engine calibration. Dana’s background is in Applied Interdisciplinary Mathematics graduating with MS from University of Michigan.
Topic: Machine Learning for Vehicle Embedded Systems and Controls
Abstract: The conference topic will cover key areas where Machine Learning provides opportunity in embedded vehicle systems and controls. This will also include an introduction to Machine Learning in the context of embedded vehicle systems. Dana will cover factors that drive ML to the forefront in areas such as diagnostics, improving development time, simulation results and accuracy.