Reza Zafarani

Reza Zafarani is an Associate Professor in the Department of Electrical Engineering and Computer Science at Syracuse University, where he directs the Data Lab. He holds a Ph.D. from Arizona State University. His research focuses on the intersection of data mining, machine learning, and social sciences, particularly in analyzing large-scale networks and social media data. Key areas of interest include big data analytics, social network analysis, and behavior modeling.

He has authored influential works such as the textbook Social Media Mining: An Introduction (Cambridge University Press, 2014) and pioneered research in fake news detection, network robustness, and graph representation learning. Notable awards include the NSF CAREER Award (2020) and NVIDIA/Google education grants.

His work spans theoretical advancements (e.g., spectral network analysis) and applied solutions (e.g., noise-enhanced machine learning). Recent research highlights include higher-order network models, adversarial graph attacks, and interpretable network representations. He advises students like Shengmin Jin and Xinyi Zhou, whose work addresses critical challenges in network science and misinformation detection.

Reza Zafarani actively contributes to the academic community through tutorials (e.g., WWW/SDM conferences) and open-source datasets like CHECKED, enabling reproducible research in misinformation studies.