Research Assistant, VCU Biotech 8, Dr. Tyler McQuade Spring 2019 – Spring 2020Assisted in NSF Grant “MPrint-OKN”, Award Abstract #1937017:• Created uniquely formatted input files in Python for DFT calculations• First at University of Richmond to create a high-throughput process in Bash to submit to computer clusters for DFT calculations using Q-chem and retrieve more than 2TB of data • Cooperated with professors and engineers from University of Richmond, University of Florida and TwoSix Labs to develop “molecular MPrints”, a data science tool that uses machine learning to develop material and molecular engineeringResearch Assistant, VCU Biotech 8, Dr. James Ferri Summer 2020 – Fall 2020• Integrated continuous integration platform, CircleCI, in Github for unit testing• Developed unit tests using Python for machines learning pipeline from start to finish• Incorporated Keras’ Convolutional Neural Network into machine learning pipeline• Integrated RDKit descriptors to machine learning pipeline• Developed a high-throughput process using Python to generate knowledge graphs in Graph Database application Neo4j directly from machine learning pipeline

• Working on a DARPA funded project along with professionals from IBM, Tom Sawyer and P&G on an Authoritative System Knowledge• Scraped consumer product data from Walmart to study consumer perception using machine learning

• Participating as a member of the Software team and Communication and Controls system team • Developed the Finite State Machine Diagram for the team’s Preliminary Design Briefing• Created a Graphical User Interface for the team’s Preliminary Design Briefing• Proposed the Testing and Validation tests for the team’s Boring machine in the Preliminary Design Briefing