Publications
Dam, R., Mponzi, W., Msaky, D., Mwandyala, T., Kaindoa, E.W., Sinka, M.E., Kiskin, I., Herreros-Moya, E., Messina, J., Shah, S.G.S., Roberts, S., Willis, K.J., 2023: What incentives encourage local communities to collect and upload mosquito sound data by using smartphones? A mixed methods study in Tanzania. Global Health Research and Policy 8, 18 (2023). https://doi.org/10.1186/s41256-023-00298-y
Kiskin I., Sinka M., Cobb A.D., Rafique W., Wang L., Zilli D., Gutteridge B., Dam R., Marinos T., Li Y., Msaky D., Kaindoa E., Killeen G., Herreros-Moya E., Willis K.J., Roberts S.J., 2021: HumBugDB: A Large-scale Acoustic Mosquito Dataset. Preprint available on https://arxiv.org/abs/2110.07607
Kiskin I., Cobb A.D., Wang L., Sinka M., Willis K., Roberts S, 2021: Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks. In ECML PKDD 2021: Machine Learning and Knowledge Discovery in Databases. https://doi.org/10.1007/978-3-030-86514-6_22.
Sinka M.E., Zilli D., Li Y., Kiskin I., Kirkham D., Rafique W., Wang L., Chan H., Gutteridge B., Herreros-Moya E., Portwood H., Roberts S., Willis K.J., 2021: HumBug – An Acoustic Mosquito Monitoring Tool for use on budget smartphones. In Methods in Ecology and Evolution June 2021. https://doi.org/10.1111/2041-210X.13663
Sinka M.E., Pironon S., Massey N.C., Longbottom J., Hemingway J., Moyes C. L., Willis K.J., 2020: A new malaria vector in Africa: Predicting the expansion range of Anopheles stephensi and identifying the urban populations at risk. In PNAS Sep 2020, 202003976; DOI: 10.1073/pnas.2003976117
Kiskin I., Cobb A.D., Wang L., Li Y., Zilli D., Sinka M., Willis K., Roberts S., 2020: HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset. Best paper award at NeurIPS 2019 Workshop: Machine Learning For the Developing World. arXiv:2001.04733
Kiskin I., Zilli D., Li Y., Sinka M., Willis K., Roberts S., 2020: Bioacoustic detection with wavelet-conditioned convolutional neural networks. In Neural Computing and Applications 32 (4), 915-927. https://doi.org/10.1007/s00521-018-3626-7
Li Y., Kiskin I., Sinka M. , Zilli D, Chan H., Herreros-Moya E., Chareonviriyaphap T., Tisgratog R., Willis K., Roberts S., 2018: Fast mosquito acoustic detection with field cup recordings: an initial investigation. In Detection and Classification of Acoustic Scenes and Events; Tampere University of Technology 2018: 153-157. http://www.tut.fi/tutcri
Li Y., Zilli D., Chan H., Kiskin I., Sinka M., Roberts S., Willis K., 2017: Mosquito detection with low-cost smartphones: data acquisition for malaria research. In NIPS 2017 Workshop on Machine Learning for the Developing World 2017. arXiv:1711.06346
Li Y., Kiskin I., Zilli D., Sinka M., Chan H., Willis K., Roberts S, 2017.: Cost-sensitive detection with variational autoencoders for environmental acoustic sensing. Presented at the NIPS 2017 Workshop on Machine Learning for Audio Signal Processing. arXiv:1712.02488
Kiskin I., Orozco B.P., Windebank T., Zilli D., Sinka M., Willis K, Roberts S., 2017: Mosquito detection with neural networks: the buzz of deep learning. In ArXiv 2017. arXiv:1705.05180
Kiskin I., Zilli D., Roberts S.: Autonomous Machines and Intelligent Systems (AIMS) Centre for Doctoral Training project. https://pdfs.semanticscholar.org/7702/2f00821d0fde32ac75f69337adc4a3c8c8e4.pdf
Press
"New Asian mosquito could bring malaria to African cities, warn scientists" The Guardian (14/09/2020)
"How an invasive mosquito could bring malaria to Africa’s cities" BBC News World Service (09/10/2020) - Interview to Dr Marianne Sinka
