Farhat Binte Azam

Selected publications

  • Classifying stages in the gonotrophic cycle of mosquitoes from images using computer vision techniques. Scientific Reports (Nature Portfolio), 2023.
  • Cardiac anomaly detection considering an additive noise and convolutional distortion model of heart sound recordings. Artificial Intelligence in Medicine, 2022.
  • Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes. Insects, 2022. (Best Paper Award)
  • Artificial intelligence and community science as a solution for enhanced global surveillance of invasive malaria mosquito Anopheles stephensi: Madagascar case study. Insects, 2025.

Full list

Journal articles

  • Farhat Binte Azam et al. “Artificial intelligence and community science as a solution for enhanced global surveillance of invasive malaria mosquito Anopheles stephensi: Madagascar case study.” Insects 16(11):1098, 2025.
  • Farhat Binte Azam et al. “GLOBE Observer: A case study in advancing Earth system knowledge with AI-powered citizen science.” Citizen Science: Theory and Practice, 2024.
  • Farhat Binte Azam. “Classifying stages in the gonotrophic cycle of mosquitoes from images using computer vision techniques.” Scientific Reports (Nature Portfolio), 2023.
  • Farhat Binte Azam et al. “Evaluation of bactericidal effects of silver hydrosol nanotherapeutics against Enterococcus faecium 1449 drug resistant biofilms.” Frontiers in Cellular and Infection Microbiology, 2023.
  • Farhat Binte Azam et al. “Integrating global citizen science platforms to enable next-generation surveillance of invasive and vector mosquitoes.” Insects 13(8):675, 2022.
  • Farhat Binte Azam. “Cardiac anomaly detection considering an additive noise and convolutional distortion model of heart sound recordings.” Artificial Intelligence in Medicine 133, 2022.

Conference proceedings

  • Farhat Binte Azam. “Deep Learning-Based Classification of Anopheles stephensi Adult Mosquitoes with Enhanced Solutions for Data Imbalance.” IEEE EMBC, 2025.

Preprints / under review

  • Farhat Binte Azam et al. “SMART Trap: Digitizing Mosquito Surveillance Leveraging Artificial Intelligence.” IEEE Journal of Biomedical and Health Informatics, 2025 (submitted).
  • Farhat Binte Azam et al. “BUET Multi-disease Heart Sound Dataset: A Comprehensive Auscultation Dataset for Developing Computer-Aided Diagnostic Systems.” arXiv:2409.00724, 2024.

Thesis

  • Farhat Binte Azam. Mosquito Classification and Explainability from Image Data via Deep Learning Techniques. Ph.D. Thesis, 2025.