Assistant Professor
Paul G. Allen School of Computer Science and Engineering
University of Washington

Research Fellow
Allen Institute for AI

Email: hannaneh [at] cs [dot] washington [dot] edu


Hanna Hajishirzi is an Assistant Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington and a Research Fellow at the Allen Institute for AI. Her research spans different areas in NLP and AI, focusing on developing machine learning algorithms that represent, comprehend, and reason about diverse forms of data at large scale. Applications for these algorithms include question answering, reading comprehension, representation learning, knowledge extraction, and conversational dialogue. Honors include the Sloan Fellowship, Allen Distinguished Investigator Award, SigDial best paper award, and several industry research faculty awards. Hanna received her PhD from University of Illinois and spent a year as a postdoc at Disney Research and CMU.

My lab (H2lab) mainly publishes at NLP (ACL, NAACL, EMNLP), AI and ML conferences (AAAI, ICLR) across these areas:

Representation learning for multimodal data: (a) Integrating neural and structured representations to encode diverse forms of data into knowledge-aware dense vectors, (b) learning efficient neural network architectures for representing textual and visual data.

Question Answering and Reasoning: Developing interpretable and efficient reasoning algorithms for (a) general-purpose multi-hop, multi-modal, and knowledge-aware question answering, (b) addressing questions about textbooks and math word problems.

Knowledge Graphs: Information extraction about entities, relations, and events from web data, news articles, and scientific articles.

NLP Applications: Open-domain question answering, information extraction, and conversational dialogs.


    Office: Paul Allen Center 654
    Phone: (206) 221-3921
    Email: hannaneh [at] cs [dot] washington [dot] edu