Zainab Akhtar

Zainab Akhtar is a Climate Change and AI Specialist at Open Development & Education, where she leads the end-to-end development of AI-driven predictive models for indoor temperature in schools. Her work integrates geospatial analytics, machine learning, and data science to inform climate adaptation strategies and improve learning environments.

She holds a Bachelor’s degree in Information Systems from Carnegie Mellon University and is currently pursuing her Master’s in Computer Science at Georgia Institute of Technology. Alongside her role at Open Development & Education, she also serves as a Geospatial Analyst with ACLED, supporting the Data Science team with spatial analysis, mapping, and system development.

Previously, Zainab worked as a Research Assistant at the Qatar Computing Research Institute, where she led the research and development of the patented Flood Insights system. This innovation was recognized at leading conferences (WWW’23 and AAAI’24 – Best Deployed Application Award), shortlisted for the World Summit Awards 2023, and applied during a real-world flood response – Pakistan Floods 2022. She has presented her work to UNDP and UNDPPA, was spotlighted in the ISPRS SC newsletter, named the Geospatial Rising Star (2024), and invited as a Réseau Associate in recognition of her contributions to geospatial research.

Passionate about leveraging GeoAI for social good and sustainable development, Zainab continues to drive innovation at the intersection of climate, data, and technology. SELECTED PUBLICATIONS

Akhtar, Z., Ofli, F., & Imran, M. (2021). Towards using remote sensing and social media data for flood mapping: 18th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2021. ISCRAM 2021 – Proceedings, 536–551. https://docs.opendeved.net/lib/22E9FFXY?referrer=/lib

Akhtar, Z., Qazi, U., El-Sakka, A., Sadiq, R., Ofli, F., & Imran, M. (2024). Flood Insights: Integrating Remote and Social Sensing Data for Flood Exposure, Damage, and Urgent Needs Mapping. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 22716–22724. https://doi.org/10.1609/aaai.v38i21.30305

Akhtar, Z., Qazi, U., El‐Sakka, A., Sadiq, R., Ofli, F., & Imran, M. (2024). Fusing remote and social sensing data for flood impact mapping. AI Magazine, 45(4), 486–501. https://doi.org/10.1002/aaai.12196

Akhtar, Z., Qazi, U., Sadiq, R., El-Sakka, A., Sajjad, M., Ofli, F., & Imran, M. (2023). Mapping Flood Exposure, Damage, and Population Needs Using Remote and Social Sensing: A Case Study of 2022 Pakistan Floods. Proceedings of the ACM Web Conference 2023, 4120–4128. https://doi.org/10.1145/3543507.3583881

Akhtar, Z., Sajjad, M., Imran, M., & Ofli, F. (2023). Risk Mapping in Managing Flood Vulnerability in Disaster Management. In International Handbook of Disaster Research (pp. 743–776). Springer Nature. https://doi.org/10.1007/978-981-19-8388-7_177

Imran, M., Sadiq, R., & Akhtar, Z. (2023). Remote sensing and social sensing for flood mapping (United States Patent No. US20230368524A1). https://patents.google.com/patent/US20230368524A1/en

Ofli, F., Akhtar, Z., Sadiq, R., & Imran, M. (2022, May). Triangulation of remote sensing, social sensing, and geospatial sensing for flood mapping, damage estimation, and vulnerability assessment: EGU General Assembly 2022.

Sadiq, R., Akhtar, Z., Imran, M., & Ofli, F. (2022). Integrating remote sensing and social sensing for flood mapping. Remote Sensing Applications: Society and Environment, 25, 100697. https://doi.org/10.1016/j.rsase.2022.100697

Sadiq, R., Akhtar, Z., Peterson, S., Keegan, K., El-Sakka, A., Imran, M., & Ofli, F. (2023). Towards fine-grained object-level damage assessment during disasters. Frontiers in Earth Science, 11. https://doi.org/10.3389/feart.2023.990930