Beliz Gunel

Beliz Gunel

Beliz Gunel is a Senior Research Scientist at Google DeepMind working on large language models and machine learning systems.1 She recently graduated with a PhD in Machine Learning from Stanford University, where she was advised by Prof. John Pauly.2

Education and Experience

• PhD in Machine Learning, Stanford University (2017-2022)
• BS in Electrical Engineering and Computer Science, UC Berkeley (2013-2017)
• Research Scientist, Google DeepMind (October 2022 - Present)
• PhD Candidate, Stanford University (September 2017 - August 2022)
• Research Intern, Google Brain, Facebook AI, Microsoft Research, Amazon Lab126 (2019-2021)

Research Interests

Beliz's research focuses on developing machine learning methods for natural language processing and healthcare that leverage the structure of the underlying data and domain knowledge. She is particularly interested in building data-efficient and robust machine learning systems.2

Throughout her PhD, she collaborated with researchers across Google AI, Google Brain, Facebook AI, and Microsoft Research as a research intern. She also worked with Prof. Christopher Ré on projects related to non-Euclidean machine learning.2

Recent News and Achievements

• Paper accepted to MIDL 2022 conference as an Oral presentation
• Papers accepted to ISMRM 2022, NeurIPS Deep Inverse 2021, KDD-DI 2021, NAACL 2021, VLDB 2021, ICLR 2021
• Gave invited talks at Stanford AIMI, Jane Street, Google Ads AI, IBM Research
• Served as Program Committee on Graph Neural Networks and Systems Workshop at MLSys 2021

In summary, Beliz Gunel is an accomplished machine learning researcher who recently joined Google DeepMind after completing her PhD at Stanford. Her work focuses on advancing natural language processing and healthcare applications using novel deep learning techniques.