I explore fundamental research in generative AI and NLP to create solutions with real-world impact, advancing a future of AI that is open, transparent, and scientifically grounded. My goal is to build open-science AI solutions that endure, helping researchers accelerate discovery, democratize access, and build public trust.
I co-lead the open language model and reasoning projects OLMo and Tulu, demonstrating that with the right scientific and engineering approaches, it is possible to build state-of-the-art models that rival proprietary systems—while sharing algorithms, datasets, and models openly. My team's research spans:
- Large language and reasoning models — developing pioneering methods, data technologies, and architectures to make these systems more powerful, efficient, and effective.
- Open AI initiatives — building some of the first truly open models, such as OLMo and Tulu. We release state-of-the-art systems, datasets, training resources, and tools to the public to ensure traceability, reproducibility, and accessibility.
- Science of AI and evaluation — systematically examining the capabilities, limitations, and behaviors of AI systems to better understand how large models learn, reason, and make decisions.
- AI for science — creating systems that interpret scientific text and data, with a focus on integrating tools and intelligent agents to accelerate discovery.
My work is regularly published at leading AI, ML, and NLP conferences (NeurIPS, ICLR, ICML, ACL, EMNLP, NAACL). The full list of publications is available on my Google Scholar and Semantic Scholar. Our open-source data, code, and models are hosted on Hugging Face and GitHub. As of 2025, our models have been downloaded over 10 million times.
Honors & Awards
- Co-PI of $152M NSF-NVIDIA infrastructure grant to develop fully open AI
- Paper awards at ACL 2025, CVPR 2025, ACL 2024, ACL 2024, CVPR 2022, AKBC 2020, SigDial 2012.
- Uncommon thinker award by GeekWire, 2024
- VentureBeat Women of AI award finalist, 2024, 2025
- Innovation of the year award by GeekWire, 2024
- UIUC CS Career Academic Achievement Alumni Award, 2023
- Torode Family Career Development Professorship, 2022
- NSF CAREER award, 2021
- Intel Rising Star faculty award, 2020
- Sloan Fellowship, 2020
- Allen Distinguished Investigator Award, 2014
Team and Mentorship
My current team consists of research scientists, research engineers, predoctoral young investigators, and Young Investigators at Ai2 working on OLMo and Tulu, along with my students and postdocs at H2Lab.
As of 2025, I have successfully graduated 14 PhD students (now at UC Berkeley, CMU, UT Austin, KAIST, Meta AI, Google Research, etc.) and 10 PostDocs (now at UIUC, UMD, Johns Hopkins, UC San Diego, etc.). For the full list of my current and past students and postdocs visit the students tab.
Hiring and Recruiting
I am always looking to hire talented research engineers and scientists at Ai2 (check the active calls) and students and postdocs at H2Lab. If you are an undergraduate student and want to work with my lab, please fill out this questionnaire.
Short Bio
Hanna Hajishirzi is a Professor of Computer Science at the University of Washington and a Senior Director of AI at AI2. Her research spans generative AI and natural language processing, with a focus on building pioneering, open-science AI solutions. She co-leads the OLMo and Tulu projects, advancing fully open language and reasoning models to accelerate the science of AI, empower the research community, and champion openness as a driver of innovation. These models have been downloaded more than 10 million times as of 2025 and were recognized with GeekWire's Innovation of the Year award. She is a co-PI of a $152M NSF- and NVIDIA-supported grant to develop the next generation of open multimodal models.
She is a recipient of the Sloan Fellowship (2021), the Uncommon Thinker Award (2025), the NSF CAREER Award (2021), Torode family Career development professorship (2022), the Allen Distinguished Investigator Award (2014), the UIUC Alumni Award (2024), and was a finalist for the VentureBeat Women in AI Award (2024, 2025). Her research has earned recognition at leading venues, with papers receiving or being finalists for awards at ACL 2025, CVPR 2025, ACL 2024 (Best Paper and Best Resource Paper), CVPR 2022, AKBC 2020, and SIGDIAL 2012.
Her work has been widely featured in leading magazines and newspapers. She has delivered keynote talks at premier venues including the White House, EMNLP, COLM, PyTorch, and Linux.