Rodrigo Lopez Negrete
Rodrigo Lopez Negrete obtained his BS and MSc from the Universidad Iberoamericana in Mexico City in 2005 and 2007, respectively. He obtained his PhD from Carnegie Mellon University in Pittsburgh, PA in 2011. All his degrees are in chemical engineering, specializing in process systems engineering, nonlinear programming, and controls.
From 2011 to 2018 he worked as a Real-Time Optimization and Controls Engineer at GE Research. He focused on development of software and algorithms to implement real-time model predictive control and estimation for combined cycle power plants, wind turbines, mining processes. Dr. Lopez Negrete was awarded the GE Physical & Digital Team Award in 2016 for his contributions helping to optimize combined cycle power plants.
In 2018 he worked at Aspen Technology Inc. to develop new algorithms to improve the capabilities of the Aspen Fleet Optimizer for planning and scheduling of the secondary distribution of fuels. In 2020 he was awarded the CTO Aspen Technology Group Recognition: Outstanding Innovation, Collaboration, and Execution for the Development of the New Replenishment Planner in Aspen Fleet Optimizer V12.
Finally, in 2021 he moved back to GE Research where his research interests are in nonlinear programming algorithms for real-time model predictive controls and estimation, model based controls, stochastic optimization, and the application of these algorithms to generate power efficiently and cleanly from renewable sources.