Patent Published: Our AI-driven method for classifying mosquito reproductive stages using computer vision is now officially patented! Read more 

Featured in Reuters: Our AI-powered mosquito trap from USF is spotlighted for its role in advancing public health surveillance and early disease detection. Read the full story  

Check out our latest research publication, which explores the integration of AI-powered tools and citizen science to advance environmental and health monitoring, featured in Citizen Science: Theory and Practice - DOI 

Our paper "Integrating Global Citizen Science Platforms to Enable Next-Generation Surveillance of Invasive and Vector Mosquitoes" has won the 2022 Best Paper Award - July 2024

Our AI-powered mosquito trap developed at USF, featured on Fox 13 News, Spectrum News is revolutionizing malaria prevention with cutting-edge technology in public health! - June 2024 (News Link #1, News Link #2 )

Earned my Master of Science (M.Sc.) in Computer Science from the esteemed University of South Florida - Dec 2023

Published a research paper on 'Classifying stages in the gonotrophic cycle of mosquitoes from images using computer vision techniques' in 'Scientific Reports' [DOI] - Nov 2023

Published a research paper on 'Cardiac anomaly detection in heart sound recordings' in 'Artificial Intelligence in Medicine' [DOI] - Nov 2022

Awarded Kaggle Open Data Research Grant 2020 for heart sound project - Feb 2020