This project explores how strategic masking—simulating cloud covers and other occlusions—can enhance the robustness of a pretrained Satellite Machine Learning (SatML) model for land cover classification tasks through fine-tuning.

This project predicts Boston housing values using machine learning. I explored the impact of physical and environmental factors by engineering features from the Boston Housing dataset and comparing the performance (RMSE) of LASSO Regression, Random Forest, and Ensemble models.

I Developed over a dozen global datasets on climate risks and socio-economic conditions during my work at a climate-tech startup, AlphaGeo.
I conducted research, data sourcing, and processing to create 1km resolution datasets and automated pipelines. In addition, I developed the "resilience-adjusted risk score" methodology with the CTO to evaluate risks under climate change scenarios.

This project, developed for the MIT Civic Data & Design Lab (CDDL) in spring 2023, investigates the transformation of Beirut's urban form and its impact on small businesses and street commerce.
I conducted spatial and data analysis, data visualization, and GIS mapping to analyze the spatial distribution of small businesses and street commerce in Beirut.

This project is developed for 11.220 Quantitative Reasoning class at MIT in fall 2022. I investigated the health insurance inequality in NYC using data from the American Community Survey (ACS) 2015 - 2019.

Developed this project website for MIT's 11.138 Crowd Sourced City class, taught by Professor Sarah Williams in Fall 2022. I collaborated with three other students, taking charge of front-end development, web design, and project management. The Philly Energy Relief Hub aims to be a one-stop shop for low income households to discover public benefit programs in Philadelphia to reduce the share of their income spent on energy, both in the short-term and long-run, and ease the process of determining eligibility and applying for programs that meet their needs.

Redesigned the MIT Energy & Climate Club website to improve user experience and visual design.

During NYC Open Data Week's prestigious Data Through Design exhibition, our team at Blockparty was honored to be selected as one of ten exhibiting artist teams, showcasing innovative applications of open data for public good. We created a compelling art installation that visually mapped housing inequality across New York City, integrating data analytics results from our AI NLP platform.

Architectural design projects from 2015 to 2020, from generative design, community engagement, to urban tech.