Researchers

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Yidi Sun, Bioinformatics, CAS Su-In Lee, U of Washington Scott Lundberg, MSR Christoph Molnar, U of Munich

• Interpretable machine learning: https://christophm.github.io/book/

Andrew Ng

• CS229a
• CS229: http://cs229.stanford.edu/syllabus-spring2021.html
• CS230

Jerome H. Friedman(https://statweb.stanford.edu/~jhf/)

• The element of Statistical Learning
• Gradient Boost

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Rachel Lea Ballantyne Draelos-Duke

• PhD student in Computer Science and Medicine
• Deep learning in medicine, art and many funs: https://glassboxmedicine.com/category/machine-learning/

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Eric Topol

• paper: THE CARE OF THE PATIENT https://jamanetwork-com.stanford.idm.oclc.org/journals/jama/fullarticle/245777
• GE mobile US: https://www3.gehealthcare.com/~/media/documents/us-global/products/ultrasound/clinical%20product%20information/vscan/gehc-user-manual_vscan-1-2.pdf

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Manolis Kellis, MIT, Computational Biology

• Algorithms for Computational Biology
• Bioinformatics and Proteomics: An Engineering-Based Problem Solving Approach

Michael Beer, JHU, Computational regulatory genomics and machine learning

Anshul Kundaje, Stanford

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沈定刚， UNC

• https://bme.shanghaitech.edu.cn/2021/0205/c8204a59374/page.htm
• MICS： https://www.mics2021.com/sponsor.htm