I am a self-professed ChemE turned software developer passionate about using machine learning to drive automation and optimization for engineering applications.I profoundly believe that automation and machine learning will accelerate engineering innovation. Between 2 years of research assistantships at UIUC and BYU – across nuclear engineering, physics, manufacturing engineering, and materials science and engineering departments – I’ve amassed 3 years of experience in industry and government lab settings as a Lead R&D Process Engineer at Neptune Plastics and, more recently, as a Machine Learning Developer at Los Alamos National Laboratory. In those roles, I’ve been integral in driving efficiencies on a number of fronts, in particular for automation.My love of automation extends beyond my 9 to 5, as well. I have a number of side projects in the works, including Limonata, a first-of-its-kind chemical printer that’s intended to reduce the time associated with chemical engineering prototyping by orders of magnitude.* Notable Professional Achievements *Developed highly innovative unsupervised learning approach in nuclear material surveillance and at Los Alamos National Laboratory. Orchestrated a regression-enabled optimization approach with labeled point cloud data for nuclear reactor (MSR) design optimization; macro-enabled reinforcement learning approach in development.Played key role in designing an automated annotation GUI, accelerating image data collection at LANL by 125%.Leveraged machine learning to implement automated processes at Neptune Plastics, enabling a triple-digit increase in production and reducing packaging time by more than half.Co-invented a novel process to reduce bioplastics manufacturing time at Neptune Plastics by 65%.* Key Strengths *Applied Machine LearningDeep LearningSupervised & Unsupervised LearningReinforcement LearningComputer VisionData-Driven ModelingData StructuresAlgorithmsProcess EngineeringTransient AnalysisAnomaly Detection* Technical Expertise *Languages: Python, C/C++, Java, Arduino, Fortran-95, JuliaPackages: PyTorch, TensorFlow, Keras, Scikit-Learn, JAX, OpenCV, Detectron2, Dopamine, ChatGPT APISoftware: Aspen HYSYS, STARCCM+, RELAP5-3D, RMCProfile, MS Azure Machine Learning, Linux CLI, Arduino IDE, LabVIEW, D-Wave Leap, MS Office Suite* Eligible for Security Clearance *