School of Medicine

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  • Jia Li

    Jia Li

    AI Fellow, Clinical Excellence Research Center (CERC)

    BioI hold the position of AI Fellow and Adjunct Professor at Stanford University in the School of Medicine. In Healthcare, I am interested in how AI could improve the outcomes of individual patients as well as hospitals. I was the Head of R&D of Google Cloud AI, President of the Google AI China Center. At Google Cloud AI, our mission is to democratize AI and advance AI. My org focus on both research innovation to solve real world problems and developing the full stack of AI products on Google Cloud to power solutions for diverse industries. Before joining Google, I was the Head of Research at Snap, leading the research innovation effort. Before Snap, I led the Visual Computing and Learning Group at Yahoo! Labs. In 2014, I was selected to receive the Super Star award at Yahoo!, the highest award at the company. I was also awarded the Master Inventor Award for my innovations in AI/ML. I received my Ph.D. degree from the Computer Science Department at Stanford University. I was the leader of the OPTIMOL team, which won the first prize in the Semantic Robotics Vision Challenge sponsored by NSF and AAAI in 2007. I served as the Program Chair of ACM Multimedia 2017, Area Chair of ICCV 2017, Industry Relationship Chair of CVPR 2016 and Volunteers Chair of CVPR 2010. I am serving the The Computer Vision Foundation Industrial Advisory Board and the Associate Editor of the Visual Computer: International Journal of Computer Graphics by Springer. My work has been reported in the media including: MIT Technology Review, CNBC, TechCrunch, New Scientist, Forbes and more in recent years.

  • Ron Li

    Ron Li

    Fellow in Stanford Center for Clinical Informatics
    Resident in Stanford Center for Clinical Informatics

    BioI am an internist and clinical informatics fellow with an interest that bridges clinical medicine, data analytics, and enterprise operations. My interest is to develop, implement, and evaluate next generation informatics technologies that aim to improve healthcare. Current areas of focus include mining electronic health record (EHR) audit trail data to understand clinician usage patterns of EHR embedded clinical decision support and order sets, implementation and evaluation of machine learning algorithms for clinical and operational use cases, leveraging standard APIs such as FHIR to build and implement interoperable clinical apps that integrate with the EHR, and enterprise implementation of an EHR integrated clinical communication system.