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Saving lives one cough at a time.
We used hierarchical clustering to match vendors with potential clients and governmental agencies
We use an iterative agglomerative clustering algorithm to group similar agencies and match to potential vendors.
Agencies in DC contract with thousands of vendors each year. With so many options, how should these agencies optimally choose which vendors to work with? The answer lies in collaborative filtering.
Figuring out what are the factors that positively and negatively impact college matriculation for Texas high school graduates.
Cessession uses machine learning to find correlations between smoke shops and poverty to propose actionable policy decisions to better our community.
Lift off is a reddit-based stock trend analysis platform using sentiment analysis machine learning models.
A study on the relationship between poverty level and recreational land use in Houston.
A research toolkit for understanding how misinformation flows through a social network using dynamic system simulation and graph neural networks
