Sample projects

Detected wildlife in images and videos—automatically and at scale—by building the winning algorithm from a DrivenData competition into an open source python package and a web application running models in the cloud.

Built solutions using LLMs for multiple real-world applications, across tasks including semantic search, summarization, named entity recognition, and multimodal analysis. Work has spanned research on state-of-the-art models tuned for specific use cases to production ready retrieval-augmented AI applications.

Used satellite imagery to identify crop extent, crop types and climate risks to agriculture in Yemen, informing World Bank development programs in the country after years of civil war.

Analyzed millions of mobile money records to uncover patterns in behavior, and then combined these insights with human-centered design to shape new approaches to delivering mobile money to low-income populations in Tanzania.

Built a real-time, interactive map to visualize attacks on the Ukrainian health care system since the Russian invasion began in February of 2022. The map will support partner efforts to provide aid, hold aggressors accountable in court, and increase public awareness.

Automated recognition of agricultural entities (such as crops, pests, diseases, and chemicals) in WhatsApp and Telegram messages among plant doctors, enabling new ways to surface emerging trends and improve science-based guidance for smallholder farmers.

Used machine learning to match students with higher education programs where they are more likely to get in and graduate based on their unique profile, with a focus on backgrounds traditionally less likely to attend college or apply to more competitive programs.

Visualized the flow of fair trade coffee products from the farms where they are grown to the stores where they are sold, connecting the nodes in supply chain transactions and increasing transparency for customers and auditors.

Analyzed repayment behaviors across dozens of pay-as-you-go (PAYG) solar energy companies serving off-grid populations throughout Africa, and developed KPIs to facilitate standardized reporting for PAYG portfolios.

Mapped out the probabilistic patient journeys through hospitals based on tens of thousands of patient experiences, giving hospitals a better view into the timing of the activities in their departments and how they relate to operational efficiency.

Flagged public health risks at restaurants by combining Yelp reviews with open city data on past inspections. An algorithmic approach discovers 25% more violations with the same number of inspections.

Built algorithms that put apples-to-apples labels on school budget line items so that districts understand how their spending stacks up and where they can improve, saving months of manual processing each year.

Aided anti-trafficking efforts at border crossings and airports by combining data across locations and surfacing insights that give interviewers greater intelligence about the right questions to ask and how to direct them.

Translated advances in machine learning research to practical software for clinical settings, building an open source application through a new kind of data challenge.

Developed online, white-label data science competitions for students to synthesize their learnings and test their skills on applied challenges. Each capstone features a real-world dataset that focuses on an important issue in the social sector.