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Research Engineer
Shahbaz is a Research Engineer with a PhD in Computer Science and expertise in Natural Language Processing (NLP). He is passionate about developing and implementing human-centered AI applications, particularly those leveraging Large Language Models (LLMs) to address real-world challenges.
Group Involvement, NEC Laboratories Europe
Human-Centric AI
Research Interests
- Text Summarization
- LLM Application Development
- Human-Computer Interfaces for Explainable AI
Publications
- Shahbaz Syed, Dominik Schwabe, Khalid Al-Khatib, Martin Potthast. Indicative Summarization of Long Discussions. (EMNLP 2023)
- Shahbaz Syed, Ahmad Dawar Hakimi, Khalid Al-Khatib, Martin Potthast. Citance-Contextualized Summarization of Scientific Papers. (EMNLP 2023)
- Shahbaz Syed, Timon Ziegenbein, Philipp Heinisch, Henning Wachsmuth, and Martin Potthast. Frame-oriented Summarization of Argumentative Discussions. (SIGDIAL 2023)
- Shahbaz Syed, Dominik Schwabe, and Martin Potthast. Summary Workbench: Unifying Application and Evaluation of Text Summarization Models. (Demo, EMNLP 2022)
- Shahbaz Syed, Tariq Yousef, Khalid Al-Khatib, Stefan Jänicke, and Martin Potthast. SUMMARY EXPLORER: Visualizing the State of the Art in Text Summarization. (Demo, EMNLP 2021)
- Shahbaz Syed, Khalid Al-Khatib, Milad Alshomary, Henning Wachsmuth, and Martin Potthast. Generating Informative Conclusions for Argumentative Texts. (ACL 2021)
- Wei-Fan Chen, Shahbaz Syed, Benno Stein, Matthias Hagen, and Martin Potthast. Abstractive Snippet Generation. (WWW 2020)
- Henning Wachsmuth, Shahbaz Syed, and Benno Stein. Retrieval of the Best Counterargument without Prior Topic Knowledge. (ACL 2018)
- Michael Völske, Martin Potthast, Shahbaz Syed, and Benno Stein. TL;DR: Mining Reddit to Learn Automatic Summarization. (NewSumm Workshop, EMNLP 2017)
Connections
- Google Scholar: https://scholar.google.com/citations?user=eGe86TEAAAAJ&hl=en
- LinkedIn: https://www.linkedin.com/in/sshabsy