Data Science
Data Science's Honors Program awards Honors or High Honors to student research projects. (Note: Prior to the 2022-2023 academic year Data Science awarded Highest Honors as well.) The projects listed below have been defended successfully, and a copy of the thesis deposited in Swem Library.
Key:
- Student, "Thesis" (Honors level)
Committee Chair + Other Committee Members
2023-2024
- Kaitlyn Margaret Crowley, "Roads and Corresponding Travel Time to Markets: Assessing Climate Vulnerability in Nepal" (High Honors)
Dan Runfola + Jennifer Swenson, Alexander Nwala
2022-2023
- Sarah Jean Larimer, "A Satellite Imagery Approach to Estimating Migratory Flows in Guatemala Using Convolutional Neural Networks" (Honors)
Dan Runfola + Anthony Stefanidis, Alex Nwala
- Zoe Anne Metzger, "Identifying Social Media Users that are Susceptible to Phishing Attacks" (Honors)
Alexander Nwala + Dan Runfola, Salvatore Saporito
- Joseph David O'Brien, "Seeing What We Can't: Evaluating implicit biases in deep learning satellite imagery models trained for poverty prediction" (Honors)
Dan Runfola + Matt Haug, Jaime Settle
- Kayla Ann Seggelke, "Predicting Respiratory Illness in Belize" (High Honors)
Dana Willner + Alex Nwala, Margaret Saha, Kristy Murray
- Suditi V. Shyamsunder, "Modeling Perinatal Outcomes in Disaggregated Asian American Subgroups" (High Honors)
Dana Willner + Ron Smith, Dan Cristol, Adrian Bacong
- Lydia Rae Troup, "Considering the Accuracy of Fiat Boundaries: Ontology and Quantification" (High Honors)
Dan Runfola + Anthony Stefanidis, Carrie Dolan
2021-2022
- John Hennin, "The Pandemic From Above: Estimating COVID-19 Cases Using Deep Learning and Satellite Imagery" (Highest Honors)
Dan Runfola + Tony Stefanidis, Carrie Dolan - Maeve Naughton-Rockwell, "Using Deep Learning with Satellite Imagery to Estimate Deforestation Rates" (Highest Honors)
Daniel Miller-Runfola + Tony Stefanidis, Robert Rose - Sean Murphy, "Evaluating the Efficacy of Convolutional Neural Networks to Dectect Floating Plastic Debris" (Honors)
Daniel Miller-Runfola + Tony Stefanidis, Eric Walters - Soheb Osmani, "Machine Learning in Healthcare: Improving the Diagnosis of Pulmonary Embolism in COVID-19 Patients" (Honors)
Daniel Vasiliu + Dr. Dana Willner, Dr. Ashleigh Queen, Jeffrey Soloman
