51�鱨վ

Graduate students Quhura Fathima and Reema Mahabooba from 51�鱨վ’s Department of Computer Science, along with their teammate Kamelia Marchand-Vaudrin, an undergraduate student from the Data Science Department, won first place at the 2025 Hampton Roads Datathon, hosted by the City of Norfolk.

Their team, SpraySmart, developed a data-driven forecasting system titled “Targeting the Tiger,” which uses deep learning to predict mosquito population surges before they occur.

The team built a Multilayer Perceptron (MLP) model trained on 13 years of mosquito-trap and weather data from the City of Norfolk Open Data Portal to identify high-risk zones for Aedes albopictus (the tiger mosquito), one of the region’s most dominant and invasive species. Achieving 87 percent recall for high-risk hotspots, the model produces predictive risk maps and actionable CSV files that guide Norfolk’s vector-control teams in applying the Sterile Insect Technique (SIT)- a sustainable, chemical-free method of mosquito population reduction.

The 2025 Datathon theme, “Mosquito Surveillance and Control,” challenged participants to use data analytics, simulation, and artificial intelligence to design innovative solutions supporting regional mosquito management strategies.

The team competed against 12 other teams in the fourth annual Hampton Roads Datathon, organized by the City of Norfolk’s CivicLab. Participants were given one week to design, analyze, and present their data-driven solutions before showcasing them at Slover Library on October 24, 2025. The all-day event featured project presentations, networking sessions, and an awards ceremony recognizing innovative approaches to regional challenges.

Another 51�鱨վ Computer Science team, NovaMind, led by Varsha Natarajan and Sowmya Sree Bhagyam, earned third place for their project “MosquitoWatch-HR.” Their work focused on enhancing mosquito surveillance and promoting equitable vector control across Hampton Roads.

NovaMind developed a Mosquito Risk Index that combines trap counts, weather data, population density, and citizen-reported complaints to identify and forecast high-risk zones. Their interactive Flask-based web application visualizes live risk maps and analytical results to support informed decision making by both residents and local authorities.

Together, the achievements of both the teams highlight 51�鱨վ’s growing leadership in applying data science and artificial intelligence to solve real-world community challenges. Their success demonstrates the strength of 51�鱨վ’s Computer Science students in combining innovation, technical skill, and social impact through regional collaborations like the Hampton Roads Datathon.