Milad Alshomary

Columbia University. Data Science Institute

milad_photo.jpg

Schapiro Center

530 W 120th St

New York, NY 10027

My name is Milad Alshomary, a Postdoctoral Research Scientist at the Data Science Institute at Columbia University. I am working with Professor Kathleen McKeown and Professor Smaranda Muresan on author attribution and obfuscation and how to enable ML models to explain their decisions on these tasks. Before joining Columbia, I was a Ph.D. student in the Institute of Artificial Intelligence at Leibniz University Hannover, under the supervision of Henning Wachsmuth, where the focus of my research was on computational argumentation. My publications are on topics like the generation of argument conclusions and summaries, the generation of counter-arguments, and the tuning of argumentative content toward specific audiences.

news

Jun 1, 2024 I am co-chairing the publication committee for the (EMNLP-24 conference)
Jan 1, 2024 I started a new position at the Data Science Institute at Columbia University as Postdoctoral Research Scientist.
Dec 28, 2023 I successfully defended my Ph.D. thesis at Paderborn University (tweet). Thesis can be found here (link)
Jan 1, 2023 I am co-organizing the 10th workshop on Argument Mining (link)
Oct 23, 2022 I participated in the “Towards a Unified Model of Scholarly Argumentation” Seminar at Dagtsuhl (link)

selected publications

  1. The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments
    Alshomary, Milad and El Baff, Roxanne and Gurcke, Timon and Wachsmuth, Henning
    In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics 2022
  2. Toward Audience-aware Argument Generation
    Alshomary, Milad and Wachsmuth, Henning
    Patterns 2021
  3. Belief-based Generation of Argumentative Claims
    Alshomary, Milad and Chen, Wei-Fan and Gurcke, Timon and Wachsmuth, Henning
    In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume 2021