Machine Learning Engineer for Reinforcement Learning Applications

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Description

tensorflow.js javascript (d3.js c/C++ (gazebo petsc opencv) matlab (simulink) cuda node) django) flask docker python (pytorch

I'm a PhD candidate in electrical engineering, graduating in Spring '23. I research reinforcement learning (RL) for control under disturbances/faults. My work is applied to drones and smart buildings. I develop high-performance python simulations for experiments, and maintain/deploy RL controllers in production on campus buildings. Previously I worked as an Applied Scientist Intern at AWS (predictive analytics/signal processing), and a Research Intern at TieSet (federated learning/webdev/RL).