Experience

ATOM Accelerating Therapeutics for Opportunities in Medicine

• United States
• Biotechnology Research
• 1 - 100 Employee

• Data Scientist

  • Nov 2021 - Present

  - Utilized large scale molecular databases to collect, curate, and manipulate data for input to machine learning and other artificial intelligence-based model training using several tools including ATOM Modeling Pipeline (AMPL) - Led research project to train a machine learning model to predict binding free energy of molecule-protein poses to reduce need for computationally expensive simulations. - Deployed packages to various cloud computing and HPC systems including Google Cloud, Microsoft Azure, and others. - Designed and implemented modular software packages based on evolutionary and swarm-based algorithms to create new molecules with optimized properties for drug discovery. - Collaborated with customers to assist in installation, testing, and training on AMPL. Used information learned from these clients to improve AMPL’s machine learning algorithms and user experience. - Mentored students in Drug Discovery related projects with scope of machine learning in bioinformatics. Show less



The Johns Hopkins University Applied Physics Laboratory

• United States
• Defense and Space Manufacturing
• 700 & Above Employee

• Systems Engineer

  • Jun 2018 - Nov 2021

  -Integrated and utilized an adaptive sampling program in Python and MATLAB to provide the government with a tool to validate their threat models more efficiently. -Utilized the adaptive sampling tool to test a simulation and search for potential bugs in the software. -Developed MATLAB scripts to develop tools that assist in the analysis of test data that verifies combat system performance. -Analyzed results and investigated anomalies from 3 test events to verify combat system performance requirements for the US Navy’s Zumwalt class destroyers. -Spearheaded the Model-Based Systems Engineering (MBSE) model development of a threat model while developing an MBSE approach and educating the government sponsor on MagicDraw to expedite future model development with lower overhead cost and more flexibility. -Led multiple major change packages in MagicDraw to aid in the delivery of an MBSE model for a new EO/IR sensor suite for the US Navy. Show less



Naval Surface Warfare Center Carderock Division (NSWCCD)

• United States
• Armed Forces
• 500 - 600 Employee

• Engineering Intern

  • Jun 2014 - Aug 2017

  - Assisted with the testing and implementation of multiple STEM outreach programs. - Performed an investigation into the strengths and weaknesses of four hydrodynamic resistance prediction programs that were then used to evaluate a new hull optimization software called SimDShip. - Prepared, mounted, imaged, and characterized metal and plastic samples produced by additive manufacturing techniques. - Troubleshooted, repaired, and utilized a hobyist level desktop 3D printer to manufacture the rudder assembly to a naval ship. Wrote an article based on this task that was published in the Naval Engineers Journal (“Limitations of a Hobbyist Level 3D Printer,” Naval Engineers Journal) Show less