Natalie Harris
Natalie is a research engineer in Google Research and a member of the Brain Health Research team. She joined Google in 2014, since then working in the Kirkland/Seattle, Zurich and London offices. She has previously worked on multiple teams across Google and Deepmind, most recently working on continuous prediction of adverse events using Electronic Health Records. Currently her focus is Machine Learning for Healthcare, with a particular interest in Fairness & Ethics. She earned her BS in Computer Science from the University of Washington.
Authored Publications
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Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
Jessica Schrouff
Sanmi Koyejo
Eva Schnider
Krista Opsahl-Ong
Alex Brown
Diana Mincu
Christina Chen
Silvia Chiappa
Proceedings of Neural Information Processing Systems 2022 (2022)
Multi-task prediction of organ dysfunction in the ICU using sequential sub-network routing
Diana Mincu
Eric Loreaux
Anne Mottram
Jessica Schrouff
Hugh Montgomery
Ali Connell
Nenad Tomašev
Martin Seneviratne
Journal of the American Medical Informatics Association (JAMIA) (2021)
Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records
Nenad Tomašev
Sebastien Baur
Anne Mottram
Xavier Glorot
Jack William Rae
Michal Zielinski
Harry Askham
Andre Saraiva
Valerio Magliulo
Clemens Meyer
Suman Venkatesh Ravuri
Alistair Connell
Cían Hughes
Julien Cornebise
Hugh Montgomery
Geraint Rees
Christopher Laing
Clifton R. Baker
Thomas Osborne
Ruth Reeves
Demis Hassabis
Dominic King
Mustafa Suleyman
Trevor John Back
Christopher Nielsen
Martin Gamunu Seneviratne
Shakir Mohamad
Nature Protocols (2021)
