Preetam Dammu

PhD Candidate, University of Washington, Seattle.

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Hello! I’m a PhD Candidate at the University of Washington, Seattle, advised by Prof. Chirag Shah.

My research focuses on generative models for multimodal information access, spanning IR, NLP, and CV. I study how modern AI systems retrieve, reason over, and generate content, and how these capabilities can be evaluated and deployed reliably in real-world settings.

More broadly, I am interested in building robust and responsible AI systems, with an emphasis on evaluation, explainability, and practical scalability across applications.

News

Jan 15, 2026 New tutorial – Information Seeking in the Age of Agentic AI accepted at CHIIR 2026! Looking forward to presenting it in March 2026.
Jul 15, 2025 New paper on Dynamic-KGQA — a scalable framework for generating adaptive question answering datasets — accepted at SIGIR 2025!
Jun 1, 2025 Started internship at AWS AI as Applied Scientist II Intern, working on dynamic evaluations of agentic systems.
Mar 1, 2025 New paper on a shopping agent for addressing subjective product needs accepted at WSDM 2025!
May 8, 2024 New paper on covert harms in LLM-generated conversations accepted at EMNLP 2024!

Selected Publications

  1. DynamicKGQA_figure.png
    Dynamic-KGQA: A Scalable Framework for Generating Adaptive Question Answering Datasets
    Preetam Prabhu Srikar Dammu, Himanshu Naidu, and Chirag Shah
    In 48th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025), 2025
  2. ClaimVer_figure.png
    ClaimVer: Explainable Claim-Level Verification and Evidence Attribution of Text Through Knowledge Graphs
    Preetam Prabhu Srikar Dammu, Himanshu Naidu, Mouly Dewan, and 4 more authors
    In Findings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP 2024 Findings), 2024