2025-26 AY PT Research Fellowship: Computer Vision, Drones, & Dengue
The Stanford King Center on Global Development’s Academic Year Part-Time Research Fellowship Program connects King Center faculty affiliates and affiliated researchers with undergraduate students committed to providing research support during autumn, winter, and spring quarters.
Students have the opportunity to engage in world-class research that has real-world impact. Undergraduate student research fellows are paid $19/hour*. Students must be enrolled full-time to participate and must be able to commit to research 8-10 hours per week.
*Students must attend orientation and submit an I-9 form to verify employment and receive payment.
Research Project Description:
Dengue fever is a viral disease that can cause life-threatening infections and is rapidly increasing globally, propelled by the dual crisis of climate change and pollution. It is spread by Aedes aegypti mosquitoes which often lay their eggs in discarded trash that gets filled with rain or flood water. We are mapping these breeding sites using high resolution drone imaging in order to better understand local transmission dynamics and test interventions to interrupt transmission. This project is taking annotated, high resolution drone images and applying deep learning models to identify the trash sites in our maps.
Primary Research Mentor: Joelle Rosser, Assistant Professor, SoM - Medicine Department
Stanford undergraduate students in good academic standing and enrolled full-time are eligible to apply. Co-term students must have undergraduate student status; if co-terms are in graduate billing status (after 12 quarters) they are ineligible to participate.
All majors are welcome!
Students Responsibilities:
- Work with our team to develop, test, and iteratively improve AI-algorithms to identify trash sites in high-resolution drone imaging.
Students qualifications:
- Computer science background with experience coding in R and Python.
- Experience with developing and applying different deep learning models to image classification problems.
- Experience with a mapping software (ArcGIS and/or QGIS).
Time Commitment:
The time commitment is 8-10 hours per week (equivalent to a 3-unit course) each academic quarter. The expectation is that students will work the full academic year with their mentor (Autumn, Winter, and Spring quarters). Students planning on studying abroad are not eligible.
To Apply:
Along with the application, applicants are asked to submit:
- a cover letter
- resume or CV
- unofficial Stanford transcript (first quarter frosh do not need to submit transcripts for autumn quarter applications)
Research Mentor Questions for Applicants: Do you have experience with any of the following, if so please describe:
- Coding in R and Python.
- Developing and applying different deep learning models to image classification problems.
- Using a mapping software (e.g. ArcGIS and/or QGIS).
- Using Stanford's Sherlock system
