Alchemist Class 38

Graduated with a BS in CS in under 3 academic years. Selected as "best project" in three CS classes. Coursework centered around human computer interaction, blockchain, and AI/ML.

Lead proof of concept testing for expansion of unit21's no-code compliance product to new verticals. Designed and built landing page. Conducted user research and interviews.

Worked with founders to take the first steps to cement ABI (at the time BDI) as one of the first voices for blockchain in Washington.

Built internal tools for growth including an automated content engine using Node.js and TypeScript

Conducted product and user behavior analysis with a variety of tools such as hotjar, segment, and heap. Redesigned aspects of Tallysight's product offering such as the general copy, email capture modal, and user email journeys.

Designed, trained, and tested a gradient boosting (ML) based predictor of the change in the binding affinity of a protein complex upon point residue mutation. Applied predictor to generate mutant structures with optimized binding affinity for a novel influenza immunogen to submit to the vaccine design challenge at the NIH VRC.

Designed, scripted, and ran simulations as proof of concept for new method of statistically calculating rates of protein binding (Transition Path Sampling)- Did research and ran simulations to design parameters for simulation (determining optimal shooting range, binding condition, generating starting positions with replica exchange monte carlo)- Scripted upload of simulations / analysis to supercomputer for parallel processing - Quantitative analysis of simulations with MDAnalysis, SciPy/Numpy, and Matplotlib- Qualitative analysis of simulations with Visual Molecular Dynamics- Presentation of findings / proof of concept to Theoretical Biophysics department