Ke Yan
Senior Algorithm Expert at Alibaba DAMO Academy
Chaoyang District, Beijing, China
Summary
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Senior🎓
Top SchoolKe Yan is a Senior Algorithm Expert with 11 years of experience specializing in deep learning, computer vision, and medical image analysis. Currently at Alibaba DAMO Academy after research roles at Ping An AI Institute and a NIH postdoc, he focuses on applying 3D CNNs and lesion detection/classification methods to clinical imaging problems. His PhD from Tsinghua yielded an award-winning dissertation on non-invasive disease screening, reflecting a strong blend of hardware-driven sensing and ML-driven analysis. On GitHub he has contributed practical tooling for medical CT preprocessing and integration of models like LesaNet and 3DCE, showing hands-on engineering to move research into reproducible code. Colleagues value him for bridging rigorous research with production-minded algorithms that improve diagnostic workflows. Based in Chaoyang District, Beijing, he combines academic honors with industry impact in medical AI.
11 years of coding experience
4 years of employment as a software developer
The High School Affiliated to Renmin University of ChinaBachelor of Engineering, Electronic Engineering, Bachelor of Engineering, Electronic Engineering at Tsinghua University
Chinese, English
Github Skills (11)
mxnet10
machine-learning10
computer-vision10
medical-image-analysis10
python10
scripting9
image-preprocessing9
shell9
script9
sh9
deep-learning8
Programming languages (2)
Github contributions (5)
rsummers11/CADLab
Jul 2018 - Oct 2019
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory
Role in this project:
ML Engineer
ML EngineerContributions:32 commits, 32 pushes, 27 comments in 1 year 2 months
Contributions summary:Ke primarily contributed to the development of a medical imaging analysis project, evident through modifications to an image loader class and the addition of shell scripts for training and testing. The code changes focus on loading and preprocessing medical images, especially those from CT scans, and organizing them for use in a 3D convolutional neural network, named 3DCE. This includes adjusting image spacing, windowing, and resizing. Additionally, the user appears to be integrating a LesaNet model for medical image analysis, introducing new related files.
computer-aided-diagnosisbiomarkerslaboratoryimagingdiagnosis
viggin/viggin.github.com
Mar 2015 - Jul 2023
Contributions:51 pushes, 1 branch in 8 years 5 months
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