Dengue & Nipah Virus Eco-Epidemiology in Bangladesh
Project leader:
Johnny Uelmen, (uelmen@wisc.edu)
Project description:
Our research integrates artificial intelligence, computer vision, and One Health principles to enhance biosurveillance and ecological forecasting. The project focuses on two interrelated efforts: (1) developing automated image detection models to identify bats in photographs and video frames for abundance, behavior, and conservation studies, and (2) using high-resolution macro imagery of medically important arthropods (e.g., mosquitoes, ticks) captured via Cognysis StackShot equipment to generate 3D reconstructions. These technologies support public health education, citizen-science engagement, and predictive modeling of zoonotic spillover risks such as Nipah virus in Bangladesh. The current research leverages field and remote sensing data streams within an established international collaboration between the University of Wisconsin–Madison, the University of Pécs, and CVASU Bangladesh, aimed at enhancing rapid detection and ecological modeling capacities.
Interns will contribute to:
Training and validating deep-learning image detection models (e.g., YOLOv8, ResNet, or Detectron2) for identifying bat species and behaviors.
Annotating and curating datasets of bat imagery and thermal video frames.
Processing macro-stacked imagery and creating photogrammetric 3D meshes for arthropod morphology libraries.
Supporting open-source documentation and code repositories for reproducibility and community use.
Integrating detection outputs into existing forecasting dashboards that link wildlife ecology to zoonotic disease risk.
Intern needs:
Python or R programming for data analysis and machine learning.
Computer vision / deep learning (PyTorch, TensorFlow, or similar frameworks).
Image processing and annotation tools (LabelImg, CVAT, Roboflow).
Familiarity with ecology, wildlife biology, or public health data is beneficial but not required.
A strong interest in open-source collaboration, reproducibility, and interdisciplinary science.
Application Requirements:
Review the available projects by visiting the various project pages.
Interns should apply through the UW Student Jobs portal. Applicants who are not currently admitted or enrolled as a UW-Madison Student or without a UW NetID can login as well as create an account. Please note, you must apply to each project individually that you want to be considered for.
Application materials submitted through the UW Student Jobs portal should include:
A one-page cover letter that highlights your qualifications based on skills identified in the project listing and your interest in open source broadly.
A resume that includes your name, school email address, phone number, field(s) of study (major, minor, degree, certificate), relevant coursework, extracurricular activities, expected graduation date, relevant sample work (ex: GitHub link, personal website, etc.) and any relevant work or research experience.
The names and contact information of three references.
Submit a resume, cover letter, and three references as part of your application.
Interviews will be arranged for selected candidates on a rolling basis after applications close.
