First US-based machine learning engineer.

Built PyTorch-based simulation software for photonic machine learning.

Selected as a Program for Research in Science and Engineering (PRISE) Fellow for summer of 2022. PRISE is a prestigious, 10-week residential research program for advanced undergraduates.

Received HCRP funding from Harvard University to conduct research on the efficacy of transformer models in abstract visual reasoning.

Independently designed, structured, and created the Deep Learning flow for advanced high school students, consisting of code-based assignments and lessons. Created material on feedforward neural networks, CNNs, RNNs, and more for a variety of tasks from image classification to language modelling.

The Salisbury Open Data Project (SODP) aims to increase data transparency, explore public policy issues through data mining and visualization, and create Salisbury’s first open data catalog. We use data science methods and insights from artificial intelligence to analyze public data and produce projects. Our mission is to educate, inform, and create engagement within the Salisbury community.

Analyzed the prevalence of COVID-19 comorbidities and vaccine hesitancy in Refugee, Immigrant, and Minority (RIM) communities in the US, with particular focus on the Iraqi community. Worked with a team from IDEO to produce a visualization tool for the Center for Disease Control (CDC).

Use data science methods and microsimulation models to analyze the potential impact of a UBI on the UK and US economies. Additionally conduct research on the specific impacts of the welfare system by demographic.

Selected in highly competitive process to be a Summer Honors Program participant in the course "Freedom, Progress, and Tradition" taught by Dr. Yuval Levin. Analysed influential texts from political theory on prudence and the role of freedom in democracy. Debated these ideas and subsequent policy prescriptions with cohort of peers.