https://statsupai.org/. Click or tap if you trust this link." data-auth="NotApplicable" href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstatsupai.org%2F&data=05%7C02%7Cpanpan.zhang%40vumc.org%7Cf52ce30924794cd41c0408de5ed3257f%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C639052458146686187%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=iqHaK4dALm13Lwa9R7LT6ToNoIfgmH6gjeX3y4se%2BWs%3D&reserved=0" data-linkindex="7" data-olk-copy-source="MessageBody" target="_blank" rel="noopener">Stats Up AI presents a groundbreaking perspective article capturing a
candid town hall discussion from featuring leaders in statistics, biostatistics and data science (in alphabetic order): David L. Donoho (Stanford University), Jian Kang (University of Michigan), Xihong Lin (Havard University), Bhramar Mukherjee (Yale University), Dan Nettleton (Iowa State University), Rebecca Nugent (Carnegie Mellon University), Abel Rodriguez (UC Santa Cruz), Eric P. Xing (MBZUAI), Tian Zheng (Columbia University), and Hongtu Zhu (UNC--Chapel Hill).
This piece is not just another academic summary, but a snapshot of a field at a crossroads, confronting the urgent questions that will define the next decade of research and practice:
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How should statisticians adapt when empirical performance outpaces theory?
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What strategic shifts are vital for relevance and impact?
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How do we move from isolated methods to real-world systems and solutions?
This article highlights the following insights:
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Why statistics must embrace end-to-end problem solving in AI systems.
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The elevation from an auxiliary task to core scientific contributions.
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The need for statisticians to engage deeply with modern empirical modeling.
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A bold, new training with communication, collaboration, and computation at its heart.
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How statistics' unique strengths (e.g, uncertainty quantification, causal reasoning, bias analysis) are essential for trustworthy AI.
Whether you're a student, researcher, industry practitioner, or educator, this article challenges you to rethink what it means to be a statistician in today's AI-driven world.
Read the full article
https://statsupai.org/quarto_web/site/posts/perspective_paper.html. Click or tap if you trust this link." data-auth="NotApplicable" href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fstatsupai.org%2Fquarto_web%2Fsite%2Fposts%2Fperspective_paper.html&data=05%7C02%7Cpanpan.zhang%40vumc.org%7Cf52ce30924794cd41c0408de5ed3257f%7Cef57503014244ed8b83c12c533d879ab%7C0%7C0%7C639052458146699394%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=1xRdZrfs5ybPqOI6i84AF7ZJk7JsS%2F%2Bqd2270UmKICg%3D&reserved=0" data-linkindex="8" target="_blank" rel="noopener">here. You are all welcome to join the conversation to shape the future of statistics and AI.
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Panpan Zhang
Assistant Professor
Vanderbilt University Medical Center
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