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Donny Cheung
Healthcare and Life Sciences AI Lead at Google Cloud
Donny Cheung is the Healthcare and Life Sciences AI Lead at Google Cloud, based in Toronto, Ontario, Canada. He has been in this role since October 2012, where he is responsible for developing AI product portfolios in healthcare, including generative AI applications like Google’s MedLM. Cheung is dedicated to leveraging advanced healthcare data analytics and machine learning to promote healthier living and sustainability.
He holds a PhD in Mathematics from the University of Waterloo, with a research focus on quantum computing. Prior to his position at Google, Cheung worked as a senior scientist at Tornado Medical Systems, where he specialized in medical imaging device design and image reconstruction algorithms. He also served as a postdoctoral research fellow at the University of Calgary in the Institute for Quantum Information Science.1
In addition to his technical expertise, Cheung is currently an MBA candidate at the University of Toronto's Rotman School of Management, indicating his commitment to both technical and business acumen in the healthcare technology sector.1
Highlights
Last week, I had an opportunity to return to my quantum computing roots! I was invited to join a panel discussion on Quantum and Business as part of the Quantum Connections 2024 conference at the Institute for Quantum Computing. It was interesting to think about the parallels between the Quantum Tech and the Healthcare AI ecosystems in terms of nurturing innovation and supporting connections between academia and industry.
Thanks to the moderator Jane Klugman and my co-panelists Rafal Janik, Lisa Lambert and Anindya Sen for a fantastic discussion!
Continuing our innovations on exploring the medical capabilities of Google's Gemini models, our Google DeepMind and Google Research teams are sharing a new preprint focusing on three new Med-Gemini research models, focusing on 2D medical imaging (radiology, pathology, dermatology, retinal), 3D medical imaging, and genomic data. These models push the boundaries of what is possible using large multimodal models, with state-of-the-art performance on multiple benchmarks.
My team and I in Google Cloud are excited to continue to build on these advances in collaboration with these teams to advance the uses of AI in Healthcare and Life Sciences.
The paper is available on arXiv here: https://lnkd.in/gsknV4Mx
Congratulations to Shekoofeh Azizi, Daniel Golden, Shravya Shetty and many many others!
