Shaden Shaar
PhD Candidate @ Cornell University
I'm a PhD Candidate in Computer Science at Cornell, advised by Claire Cardie, working on long-form generation in multi-modal settings — specifically long-form video QA and narrative understanding and clinical NLP, with a focus on the semantic coherence that makes extended reasoning possible.
Before Cornell, I spent two years at QCRI on automated fact-checking and claim detection, COVID-19 misinformation, and propaganda and persuasion detection, co-organizing several editions of the CLEF CheckThat! shared-task series — work that shaped how I think about machines reading carefully, at scale.
Awards
- Aug 2021Started as a PhD student at Cornell, supported by a Cornell University Fellowship.
- Jul 2020Prta received an Honorable Mention for Best Demo at ACL 2020.
- Aug 2015Awarded a 50% Academic Merit Scholarship to attend Carnegie Mellon University.
Work Experience
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May 2025 — Aug 2025
Applied Scientist InternZillow Group · Remote -
Jan 2025 — May 2025
Machine Learning Research Engineer InternScale AI · Remote -
May 2022 — Aug 2022
AI/ML Research InternApple · Cupertino, CA -
Jul 2019 — Aug 2021
Research AssistantQatar Computing Research Institute, HBKU · Doha, Qatar -
May 2018 — Aug 2018
Research InternRobotics Institute, Carnegie Mellon University · Pittsburgh, PA -
May 2017 — Jun 2018
Part-Time Research AssistantCarnegie Mellon University · Doha, Qatar
Selected Publications
See all 33 publications →Selected recent and impactful publications. Full list on the publications page or Google Scholar.
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J. Frye, Shaden Shaar, C. Cardie, E. DeFilippis, D. Estrin, G. Sayer, N. Uriel, et al.JHLT · 2026 · JournalUses an LLM to perform thematic analysis of accepted exception requests for heart transplant candidates, surfacing the clinical rationales that drive decisions in a setting where manual review at scale is infeasible.
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Shaden Shaar, B. Thymes, S. Chaixanien, C. Cardie, B. HariharanCVPR · 2026 · ConferenceAn open-ended video-QA benchmark built from movie recaps that stress-tests whether models can reason over long-form narrative, not just short clips. Paired with baselines that expose a large gap between human and model performance on grounded, cross-modal questions.
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Shaden Shaar, W. Chen, M. Chatterjee, B. Wang, W. Zhao, C. CardieTACL · 2025 · Journal · 2 citationsRevisits a long-standing assumption in event extraction — that explicit trigger annotations are required — and shows that trigger-free formulations can match or exceed trigger-based pipelines at the document level.
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Shaden Shaar, N. Georgiev, F. Alam, G. Da San Martino, A. Mohamed, P. NakovEMNLP · 2022 · Findings · Conference · 45 citationsScales fact-checked-claim detection from isolated sentences to full documents, where each claim must be located and matched jointly. Introduces a document-level dataset and retrieval+ranking system tuned for real fact-checker workflows.
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G. Da San Martino, Shaden Shaar, Y. Zhang, S. Yu, A. Barrón-Cedeño, P. NakovACL · 2020 · Conference · 93 citationsAn end-to-end system for highlighting 18 propaganda techniques in news articles, paired with a public web interface. Recognized with an Honorable Mention for Best Demo at ACL 2020.
- ACL 2020Shaden Shaar, G. Da San Martino, N. Babulkov, P. NakovACL · 2020 · Conference · 241 citations
Formalizes "previously fact-checked claim detection" as a ranking task and releases the first dataset for it, showing that reusing existing fact-checks is a practical alternative to verifying every claim from scratch.
Education
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2021 — present
PhD, Computer ScienceCornell University · Ithaca, NYMinor: Applied Mathematics -
2021 — 2024
M.S., Computer ScienceCornell University · Ithaca, NY -
2015 — 2019
B.S., Computer ScienceCarnegie Mellon University · Doha, QatarMinor: Mathematics · University Honors
Teaching
Cornell University
- Fall 2022CS 4740: Natural Language Processing
- Spring 2022Introduction to Machine Learning
Carnegie Mellon University
- Fall 2018 & Spring 201911-785: Introduction to Deep Learning
- Spring 2018 & Spring 201915-251: Great Theoretical Ideas in Computer Science
- Fall 201715-213: Introduction to Computer Systems
- Fall 2016 & Fall 201715-112: Fundamentals of Programming
- Spring 201621-127: Concepts of Mathematics
Contact
Happy to hear from potential collaborators or anyone curious about the work.
The best way to reach me is by email:
sshaar31@gmail.com.
A printable CV is available at /cv.