Hi, I’m Hamzeh! I recently graduated with honors from Harvard University, where I studied Computer Science and Statistics. My passion lies at the intersection of data science and artificial intelligence, where I strive to build impactful solutions that address real-world challenges.
I develop software applications that leverage artificial intelligence to solve complex problems, aiming to create tools that are both innovative and practical. I also engage in data-driven research projects that uncover insights into pressing issues.
Through this website, I aim to share my projects, insights, and the journey of applying AI and data science to make a meaningful difference.
Degree: Harvard University, A.B. in Computer Science and Statistics (Honors), Minor in Mathematics
Graduation Date: May 2025
Thesis Title: Cross-Market Signals: Economic Spillovers Across Markets
Thesis Description: This thesis investigates the interconnectedness of the U.S. and Chinese stock markets, analyzing how macroeconomic factors from one country affect the equity returns of the other. Using statistical and machine learning models on the Jensen, Kelly, and Pedersen Global Factors dataset, the study finds strong spillover effects from the U.S. to China, but minimal effects in the reverse direction.
View Thesis
Consulting on Business and the Environment
Machine Intelligence Community
Undergraduate Foreign Policy Initiative
All cover artwork is generated using Dall-E.
Based on Raj Chetty's Opportunity Atlas, this tool helps parents assess demographics and opportunities in their zipcodes, exploring local community and school options.
Comprehensive analysis of BTC and ETH price movements using time series analysis, machine learning models, and deep learning architectures.
Analysis of stock price movements using financial and economic indicators with statistical learning and machine learning techniques.
Analysis of baseball metrics to understand and predict team performance, providing insights for team management and betting strategies.
Modeling when coaches should go for two-point attempts versus extra points based on game situations and analytics.
Estimating player value and team performance using Monte Carlo simulations with high school baseball statistics.
Provides methods for assessing company similarity using specified sub-sections of 10-K filings. Uses cosine similarity of BERT embeddings for similarity.
A model of firm behavior under a duopoly using classical microecnonimic multivariate maximization and game theory.
An explanation of how ChatGPT works from the ground up. Topics include basic neural networks, recurrent neural networks, and long short-term memory networks.
A tract-level correlational analysis of economic growth factors, such as education and employment rate, on income, separated by gender and race.
An explanation of basic computer graphics. Includes discussions on transformations in 2D and 3D space, quaternions, perspective projections, and shadow mapping.