- Contributed to development of data pipelines in AWS that processed ~10s of TB daily- Provided guidance on usage of data lake to over a dozen groups within organization- Created AWS Lambda function in Golang which efficiently traversed ~4700 TB of raw sensor data to identify nearly 3500 TB of unused data that could be deleted, leading to savings of ~$85,000/month- Demonstrated proof-of-concept synthetic robotics data generation system that was 2-3x faster than the current system- Created a Tableau dashboard to analyze data lake usage which helped identify the most frequently accessed tables- Designed new method to deserialize raw binary robotics data using Python and Numpy, achieving a 29xspeed-up in processing time- Developed Python library using PyArrow to convert generic JSON-like data into Pandas DataFrames,standardizing robotics data for seamless integration into the data lake- Leveraged Terraform to create and maintain data infrastructure- Contributed to development of self-service web apps written in Vue.js that allowed users to view status of data collection

• Created SQL data pipeline to process millions of data points for validating engineering calculations• Wrote PowerShell script that automated computationally intense calculations which reduced load on client servers and time spent on task by 67%• Used PowerShell and .NET assemblies to extract, transform and load millions of time series data points

• Coded console application that created file backups of time series database resources using C#• Created command line interface for interacting with time series database using PowerShell and .NET• Developed custom extensions for data visualization web app that utilized REST API using JavaScript, CSS, HTML, and AngularJS• Assessed client data historian usage and condition by using Python and Jupyter notebooks to analyze their operations data• Designed continuous integration build process for .NET console application using CircleCI and GitHub• Contributed to development of custom Docker image for running .NET applications in Windows containers

- Performed 1D CFD analysis on engine flow subsystems (fuel, cooling and lube systems) using GT Suite- Calibrated QSK60 T4 cooling system models to within 6% of test data using optimization software (GT Optimizer)- Solved integration issue between modeFRONTIER and ANSYS by developing a process in the former software that works around it- Improved computation speed of engine benchmark calculation by 10x using Python

- Performed microscope experiments to track nanoparticle movement in complex fluids- Worked under the supervision of a professor and 2 PhD candidates- Analyzed experimental data using MATLAB and visualized data with VBA and Python- Presented research at the 6th Texas Soft Matter Conference