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Kang Li is a distinguished professor and researcher, currently affiliated with Johns Hopkins University, primarily in the Department of Computer Science and often associated with the Malone Center for Engineering in Healthcare. His work is highly interdisciplinary, focusing on the intersection of computer vision, machine learning, artificial intelligence, and medical image analysis. Professor Li is recognized for developing innovative algorithms and systems to enhance medical diagnosis, guide surgical procedures (computer-assisted surgery), and improve overall healthcare outcomes. His research often involves creating novel techniques for 3D reconstruction, image registration, segmentation, and data analytics applied to various medical imaging modalities. He is committed to translating technological advancements from the lab into clinical practice to address real-world healthcare challenges.
Kang Li's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Holds a full professorship at a world-renowned research institution, leading cutting-edge research in medical AI and computer vision.
Has made significant contributions to the development of algorithms for medical image processing, surgical navigation, and AI-driven diagnostic tools.
Successfully secured and led numerous research grants from prestigious funding bodies like the National Institutes of Health (NIH), underscoring the impact and potential of his work.
Authored and co-authored a substantial number of highly cited papers in leading journals and conferences in computer science, medical imaging, and biomedical engineering.
Actively involved in mentoring PhD students and postdoctoral researchers, fostering the next generation of innovators in AI and healthcare technology.
Y Combinator - Year 2018
Nanyang Technological University Singapore - Year 2007
Zhejiang University - Year 2003
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iLab Solutions, now part of Agilent Technologies, provides a comprehensive, web-based core facility management software. It helps research institutions, universities, and hospitals streamline operations for shared research resources by managing service requests, equipment reservations, billing, and reporting. The platform aims to improve administrative efficiency, enhance collaboration among researchers, and optimize resource utilization within core facilities and shared labs.
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