Contact information
LinkedIn: https://www.linkedin.com/in/irfhana/
Irfhana Zakir Hussain is a dedicated researcher specializing in the intersection of Artificial Intelligence and Public Health. With a background in Computer Science and Engineering, Irfhana has honed her expertise in developing innovative solutions to address pressing global health challenges. Currently pursuing her Joint Ph.D. Public Health Sciences and Systems Design Engineering at the University of Waterloo, she focuses on developing a next-generation Public Health Surveillance system for real-time monitoring and prediction of Extreme Heat Events. With a strong foundation in big data ecosystem design and development, machine learning and deep learning techniques, coupled with her experience in data analytics and IoT technologies, Irfhana has contributed significantly to various research projects, including health misinformation detection and prediction, air quality prediction and monitoring, and extreme heat event monitoring. Her passion for leveraging technology to improve public health outcomes underscores her commitment to creating impactful solutions for communities worldwide.
Education
Joint Ph.D. Public Health Sciences and Systems Design Engineering — University of Waterloo — 2023-Present
B.Tech Computer Science and Engineering, Big Data Analytics — SRM Institute of Science and Technology, Chennai, India — 2018-2022.
Research Interests
- AI, IoT and Big Data in Health
- Climate and Health Action
- Next Generation Public Health Surveillance
- Interpretable AI
- Infodemics and Infoveillance
Selected Publications
Full List of Publications: ResearchGate
Morita, P.*, Zakir Hussain, I.*, Kaur, J.*, Lotto, M., & Butt, Z. (2023). Tweeting for Health Using Real-time Mining and Artificial Intelligence–Based Analytics: Design and Development of a Big Data Ecosystem for Detecting and Analyzing Misinformation on Twitter. Journal of Medical Internet Research, 25, e44356.
*Shared first authorship & contributed equally
Zakir Hussain, I., Kaur, J., Lotto, M., Butt, Z., & Morita, P. (2023). Infodemics surveillance system to detect and analyze health misinformation using big data and AI. European Journal of Public Health, 33(Supplement\_2), ckad160–163.
Lotto, M., Zakir Hussain, I., Kaur, J., Butt, Z., Cruvinel, T., & Morita, P. (2023). Exploring fluoride-free content on Twitter: A topic modeling analysis. European Journal of Public Health, 33(Supplement_2), ckad160–601.
Lotto, M., Zakir Hussain, I., Kaur, J., Butt, Z., Cruvinel, T., & Morita, P. (2023). Analysis of Fluoride-Free Content on Twitter: Topic Modeling Study. Journal of Medical Internet Research, 25, e44586.
Lotto, M., Sa Menezes, T., Zakir Hussain, I., Tsao, S.F., Ahmad Butt, Z., P Morita, P., & Cruvinel, T. (2022). Characterization of false or misleading fluoride content on Instagram: infodemiology study. Journal of Medical Internet Research, 24(5), e37519.
S. Salim, I. Zakir Hussain, J. Kaur and P. P. Morita, "An Early Warning System for Air Pollution Surveillance: An IoT Based Big Data Framework to Monitor Risks Associated with Air Pollution," 2023 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), Dubai, United Arab Emirates, 2023, pp. 148-152, doi: 10.1109/GCAIoT61060.2023.10385123.