Sara Hooker is a computer scientist who works in the field of artificial intelligence (AI). She is known for her work on model efficiency at scale, large language models and areas of research on algorithmic bias and fairness in machine learning. In 2025, she co-founded Adaption, a startup focused on creating AI systems capable of continuous real-time learning and efficient adaptation.
Hooker previously served as the Vice President of Research at Cohere, where she led the company's research arm, Cohere For AI. As VP of Research at Cohere, she launched the Cohere For AI scholars program.Prior to Cohere, she built large systems in computer vision and NLP at Google Deepmind. Her work has been featured in mainstream news outlets including Techcrunch, New York Times, Washington Post, Axios, MIT Technology, The Atlantic.
In 2023, Hooker was listed as one of AI's top 13 innovators by Fortune. In 2024, she was in TIME's 2024 list of the most influential people in AI.
Sara Hooker is on Kaggle's ML Advisory Research Board and the World Economic Forum council on the Future of Artificial Intelligence. She is also a member of the MLC research group.
Sara Hooker was born in Dublin, Ireland. At four years old, her parents moved to Lesotho. She grew up in South Africa, Mozambique, Lesotho, Eswatini and Kenya until she was 19.
Hooker earned her computer science PhD as a Doctor of Philosophy in Computer Science from Mila - Quebec AI Institute.
In 2014, she founded Delta Analytics, which develops technical capacity for non-profits.
Hooker joined Google Brain (now Google DeepMind) in 2017 as a research scientist. During her tenure, she focused on model interpretability and the Hardware Lottery a concept she pioneered regarding how hardware constraints shape the direction of AI research. She was also a founding member of GoogleâÂÂs first AI research office in Accra, Ghana.
In April 2022, Hooker joined the AI startup Cohere to lead Cohere Labs, the research arm of Cohere
The lab launched several initiatives including:
In 2025, she co-founded Adaption with Sudip Roy, a startup focused on developing adaptable and efficient AI systems capable of continuous real-time learning.She leads a large team of AI researchers and engineers that build extremely efficient, adaptable systems.
HookerâÂÂs research has been published in peer-reviewed scientific venues, including Nature, and major machine learning conferences such as NeurIPS, ICML, ACL, ICLR, EMNLP, and MLSys. She has received recognition including the ACL Best Paper Award for her scholarly contributions in natural language processing and machine learning.