Abdulaziz Alhamadani
Abdulaziz Alhamadani is a Ph.D. student in the Department of Computer Science. His advisor is Chang-Tien Lu.
Alhamadani’s research interests mainly focus on developing efficient and applicable methods of training machine learning models for real-world applications such as pandemic prediction and drug overdose crises. His additional research areas include natural language processing, such as text classification and building large corpora for low-resource languages, machine learning ethics, and event detection.

Publications
Jianfeng He, Xuchao Zhang, Shuo Lei, Zhiqian Chen, Fanglan Chen, Abdulaziz Alhamadani
In Proceedings of the Empirical Methods in Natural Language Processing, (pp 8362–8372),
Citatations: BibTeX
Kaiqun Fu, Abdulaziz Alhamadani, Taoran Ji
In Special Interest Group on Spatial Information, 11 2: 16-25, 12/2019
Citatations: BibTeX