Scholar
Ryutaro Tanno
Google Scholar ID: NiEvNoEAAAAJ
Research Scientist, Google DeepMind
Citations & Impact
Citations
4,040
H-index
28
i10-index
37
Publications
20
Co-authors
13
list available
Publications
Resume (English only)
Academic Achievements
- Published multiple papers in conferences such as NeurIPS, MICCAI, ICLR, and journals like Nature Communications, covering topics including uncertainty quantification in medical image synthesis, methods for segmenting ultra-high resolution images, and neural network repairment.
Research Experience
- Currently a Research Scientist at Google DeepMind. Previously worked in the Healthcare Intelligence group at Microsoft Research Cambridge. Was a PhD student in the Department of Computer Science at UCL. Worked part-time at ThinkSono as one of the starting members, co-developing a real-time deep-learning based system for detecting deep vein thrombosis in ultrasound videos. Spent the summer of 2018 as a research intern at Butterfly Network, a NY-based unicorn developing an intelligent and portable ultrasound probe. Since April 2019, has been consulting for SyntheticGestalt, a drug discovery startup based in Tokyo.
Education
- PhD in Machine Learning (2020), University College London, supervised by Daniel C. Alexander at CMIC UCL and Antonio Criminisi at Amazon Cambridge; MPhil in Computational Neuroscience (2015), University of Cambridge; MASt in Pure Mathematics (2014), University of Cambridge; BSc in Pure Mathematics (2013), Imperial College London.
Background
- Interests: Uncertainty modelling, Interpretability, Robustness. Focus: Developing high-performance machine learning algorithms that are risk-aware, interpretable, and robust for safe use in healthcare applications.
Miscellany
- Co-organizing the workshop on Uncertainty and Safety in Medical Imaging at MICCAI 2022, Singapore.
