Naeemul Hassan

Dr. Naeemul Hassan is an Associate Professor at the Philip Merrill College of Journalism and the College of Information Studies at the University of Maryland, with an affiliate appointment in the Department of Computer Science. He directs the Computational Journalism Lab and focuses on Big Data, Data Science, and Natural Language Processing, particularly in areas like Computational Journalism, Social Sensing, and Misinformation Detection. His research includes developing technologies such as BaitBuster and ClaimBuster to aid fact-checking and combat misinformation. Previously, he was an Assistant Professor at the University of Mississippi and earned his Ph.D. in Computer Science from the University of Texas at Arlington (2016).

Education: Ph.D. in Computer Science, University of Texas at Arlington (2016).

Research Interests: His work spans automated fact-checking, health information credibility, and social media analysis. Key projects include analyzing misinformation in health contexts (e.g., TikTok, Reddit), detecting misleading headlines, and exploring AI-driven solutions like LlamaLens for multilingual news analysis. He also examines societal impacts of digital platforms in contexts like Bangladesh and the U.S.

Lab and Collaborations: Directs the Computational Journalism Lab and collaborates with the Computational Linguistics and Information Processing (CLIP) Lab and the Human-Computer Interaction Lab (HCIL). Recent grants include SaTC: CORE funding for BaitBuster 2.0 and RAISE support for a Credible Open Knowledge Network.

Grants and Projects: Notable funding includes NSF grants for misinformation research and collaborative projects on clickbait mitigation and health information systems.

Currently, he is not accepting new Ph.D. students. His work bridges computer science, journalism, and public health, emphasizing ethical AI applications and societal impacts of digital media.