Lei Xing
@lx2015
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J. Haimson & S. S. Donaldson Professor, Director of Med. Phys. Division, Depts of Radiation Oncology, Elec. Eng. & ICME (adjunct), Stanford Univ.
Joined February 2014
We are thrilled with the tremendous success of the AI Medicine Symposium at Stanford! The extraordinary caliber of the speakers and the exceptional level of audience engagement were truly phenomenal. Sincere thanks to every speaker, our administrative staff, & our vendor sponsors
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We are thrilled with the tremendous success of the Proton Therapy Symposium at Stanford! The extraordinary caliber of our speakers & the exceptional level of audience engagement were truly phenomenal. Sincere thanks to every speaker, our administrative staff, & vendor sponsors!
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Learn more about our upcoming AI Medicine Symposium (September 26-27) https://t.co/QMoz1Wp0vt and Modern Proton Therapy Symposium (September 27) https://t.co/LoK16KO4YP Register early online!
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Just a friendly reminder: The early registration deadline for our upcoming AI Medicine Symposium (September 26-27) and Modern Proton Therapy Symposium (September 27) is July 25. Be sure to pre-register here: https://t.co/FFLjpfCJs0
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Here is the URL for registration of our CME symposia. The first symposium will focus on AI Foundation Models and Agentic AI for Radiation Oncology and Healthcare. The second, held exclusively on Saturday, will cover Modern Proton Radiation Therapy https://t.co/FFLjpfCJs0
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We're thrilled to announce that our Medical Physics PhD and Certificate Programs have been granted CAMPEP accreditation! Huge kudos to our faculty and staff for their diligent commitment in achieving this significant milestone in medical physics education. https://t.co/zQ42fIytCJ
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A symposium focusing on AI foundation models, generative models, and agentic AI will be held on Stanford campus before ASTRO annual meeting in SF. Please mark your calendars; detailed program and registration website for the symposium will be made available online soon.
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A symposium on Modern Proton Therapy will be held on Stanford campus before ASTRO annual meeting in SF. Please mark your calendars for this unique opportunity; detailed program and registration website for the symposium will be made available online soon.
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The ICME Research Symposium on Tue, May 20, 2025 from 10:00 AM to 5:00 PM at the Jen-Hsun Huang Engineering Center at Stanford for a day filled with exciting research presentations and discussions. Don't miss this opportunity to learn, and collaborate with experts in the field.
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Congratulations to our newly matched residents, Megan Clark and Jeffrey Zabel! Please join us in welcoming them to the Stanford family!
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Thank you to the NIH and the National Academies of Sciences, Engineering, and Medicine for organizing this timely and informative symposium. It's an honor to discuss our multi-omics and imaging integration research for precision medicine!
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Honored and grateful to receive a grant from @StanfordHAI(Human-Centered Artificial Intelligence). Our project promises to advance personalized neuroscience through AI. Kudos to Drs. Zixia Zhou and Md Tauhidul Islam for spearheading the research. https://t.co/MXAKTIield
hai.stanford.edu
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NIH slashes overhead payments for research, sparking outrage | Science | AAAS
science.org
Move to cut indirect cost rate to 15% could cost universities billions of dollars
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We have a few openings for medical physics faculty! Please see the link for more details: https://t.co/6zGmofiwqH.
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Pleased to provide a high-performance and broadly applicable AI solution for solving bionetwork & other graph problems @ScienceAdvances. A big shout-out to R. Yan and @tauhid_stanford! Be an early adopter of this AI technique— https://t.co/vJdl0DKAbP
science.org
A strategy preserves complex networks in lower dimensions with discriminative node representation, enhancing PPI network analysis.
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Deep representation learning of protein-protein interaction networks for enhanced pattern discovery @ScienceAdvances 1. Introducing DNE (Discriminative Network Embedding), a self-supervised learning framework that redefines protein-protein interaction (PPI) network analysis by
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SCI member @lx2015 & others found that reconfiguring tabular data into 2D topographic maps (TabMaps) enhanced predictive performance and interpretability across multiple biomedical applications, outperforming traditional methods. #DeepLearning
https://t.co/MMHEEv7k8e
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