Dr. Chadi Helwe is an assistant professor of computer science in the Department of Computer Science and Mathematics at LAU, where he began in January 2026. He earned his PhD in Computer Science with a specialization in artificial intelligence from the Institut Polytechnique de Paris, France, following the completion of his MSc in Computer Science at the American University of Beirut, where he received the Best Computer Science Graduate Student award.

Prior to joining LAU, Dr. Helwe completed two postdoctoral positions. At INRIA Saclay (France), in collaboration with CWI Amsterdam, he was awarded the prestigious INRIA Postdoctoral Fellowship to pursue his postdoctoral research. He then joined KAUST (Saudi Arabia), where his work focused on developing an Arabic large language model (LLM) and advancing reasoning capabilities in LLMs.

Research Interests

Dr. Helwe’s primary research interest lies in Natural Language Processing (NLP), with a focus on improving the reasoning abilities of large language models (LLMs). Through his doctoral and postdoctoral work, he has assessed the limitations of current models in logical reasoning, fallacy detection and belief revision, while developing benchmarks and tools to evaluate and improve their reasoning performance. Additionally, his research extends to Arabic NLP, studying biases in LLMs and AI applications in healthcare.

Selected Publications

1. Chadi Helwe, Oana Balalau, and Davide Ceolin. “Navigating the Political Compass: Evaluating Multilingual LLMs across Languages and Nationalities”. In: Findings of the Association for Computational Linguistics: ACL 2025 (2025).
2. Chadi Helwe, Sultan AlRashed, and Francesco Orabona. “ReviseQA: A Benchmark for Belief Revision in Multi-Turn Logical Reasoning”. In: ICML 2025 Workshop on Assessing World Models (2025). 
3. Chadi Helwe, Tom Calamai, Pierre-Henri Paris, Chloé Clavel, and Fabian Suchanek. “MAFALDA: A Benchmark and Comprehensive Study of Fallacy Detection and Classification”. In: Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL) (2024). 
4. Chadi Helwe, Simon Coumes, Chloé Clavel, and Fabian Suchanek. “TINA: Textual Inference with Negation Augmentation”. In: Findings of the Association for Computational Linguistics: EMNLP 2022 (2022). 
5. Chadi Helwe, Chloé Clavel, and Fabian Suchanek. “LogiTorch: A PyTorch-based library for logical reasoning on natural language”. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP): System Demonstrations (2022).
6. Chadi Helwe, Shady Elbassuoni, Ahmad Dhaini, Lily Chacra, and Shady Awwad. “A Deep Learning Approach to Detect the Demarcation Line in OCT Images”. In: Annual Conference on Medical Image Understanding and Analysis (2020).
7. Chadi Helwe and Shady Elbassuoni. “Arabic named entity recognition via deep co-learning”. In: Artificial Intelligence Review (2019).
8. Mohammed Elrazzaz, Shady Elbassuoni, Khaled Shaban, and Chadi Helwe. “Methodical evaluation of arabic word embeddings”. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (2017).

Academic Degrees

• PhD in Computer Science (Specializing in Artificial Intelligence), Institut Polytechnique de Paris, 2024.
• MSc in Computer Science, American University of Beirut, 2017.
• BSc in Computer Science, Notre Dame University-Louaize, 2014.