Our Research
Vectech partners with mosquito control districts, NGOs, and research institutions around the world to solve entomological problems with engineering and computer science. If you have a challenge you’d like us to work on, get in touch with us!
Our Research is Supported By
Publications
Our work has been published in industry leading journals and presented at national conferences. Read more about the science behind our technology.
Mosquito species identification accuracy of early deployed algorithms in IDX, A vector identification tool
2024
Citation: Khushi Anil Gupta, Vasiliki N. Ikonomidou, Margaret Glancey, Roy Faiman, Sameerah Talafha, Tristan Ford, Thomas Jenkins, Autumn Goodwin (2024). Mosquito species identification accuracy of early deployed algorithms in IDX, A vector identification tool. Acta Tropica, 260.
An Ordered Sample Consensus (ORSAC) Method for Data Cleaning Inspired by RANSAC: Identifying Probable Mislabeled Data
2024
Citation: Jenkins, Thomas; Talafha, Sameerah; Goodwin, Autumn (2023). An Ordered Sample Consensus (ORSAC) Method for Data Cleaning Inspired by RANSAC: Identifying Probable Mislabeled Data. TechRxiv, 13, 9.
The Remote Emerging Disease Intelligence—NETwork
2022
Citation: Achee, N. L. (2022). The Remote Emerging Disease Intelligence—NETwork. Frontiers in Microbiology, 3382.
Modified Mosquito Programs’ Surveillance Needs and An Image-Based Identification Tool to Address Them
2022
Citation: Brey, J., Sai Sudhakar, B. M. M., Gersch, K., Ford, T., Glancey, M., West, J., ... & Goodwin, A. (2022). Modified Mosquito Programs’ Surveillance Needs and An Image-Based Identification Tool to Address Them. Frontiers in Tropical Diseases, 2, 73.
Mosquito species identification using convolutional neural networks with a multitiered ensemble model for novel species detection
2021
Citation: Goodwin, A., Padmanabhan, S., Hira, S., Glancey, M., Slinowsky, M., Immidisetti, R., ... & Acharya, S. (2021). Mosquito species identification using convolutional neural networks with a multitiered ensemble model for novel species detection. Scientific reports, 11(1), 1-15.
Aedes aegypti in Maryland: The need for elevated vector surveillance at the face of a dynamic climate
2024
Faiman, R., Goodwin, A., Cave-Stevens, J., Schultz, A., Brey, J., & Ford, T. (2023). Aedes aegypti in Maryland: The need for elevated vector surveillance at the face of a dynamic climate. bioRxiv, 2023-10.
Development of a low-cost imaging system for remote mosquito surveillance
2020
Citation: Goodwin, A., Glancey, M., Ford, T., Scavo, L., Brey, J., Heier, C., ... & Acharya, S. (2020). Development of a low-cost imaging system for remote mosquito surveillance. Biomedical Optics Express, 11(5), 2560-2569.
