I recently got my Ph.D. in Computer Science from Columbia University where I was part of the natural language processing group . My Ph.D. research advisor was Smaranda Muresan. My dissertation was on Computational Models of Argument Structure and Argument Quality for Understanding Misinformation [ link ].

Prior to Columbia, I worked as a Research Associate at the Center for Complex Engineering Systems (CCES) that is held jointly at the King Abdulaziz City for Science and Technology (KACST) and the Massachusetts Institute of Technology (MIT).

Email:   tariq [at] cs [dot] columbia [dot] edu
Resume: Full Resume, Short 1-page Resume

Research Interests

My research is in natural language understanding and machine learning. I am interested in studying how can models of Argument Structure and Argument Quality (Fallacy) improve our understanding of Misinformation and our ability to automate the fact-checking pipeline. I work on problems across the full fact-checking pipeline that include: check-worthiness detection, evidence retrieval, and claim verification. I mainly work on complimenting pre-trained language models with external knowledge relevant to these tasks (e.g. discourse information for argumentation mining, argumentation for check-worthiness detection, and instruction-based prompts for detecting fallacies). I also work on analyzing the robustness of these models under adversarial attacks.

Selected Publications

Other Work

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