Holder： Guang Cheng（UCLA）
Time：2023-11-23 14:00-15:00
Location：Tencent Meeting: 830-899-630
Abstract:
Embark on a journey into the heart of Generative Data Science, the cornerstone of the evolving landscape of Generative AI. The talk centers on a meticulous statistical evaluation of generative data, specifically addressing three critical dimensions: the extent of privacy preservation, the optimization of utility in downstream tasks, and the reinforcement of fairness through generative data methodologies. Time permitting, a brief introduction to the UCLA Trustworthy AI Lab will be offered, providing a statistical perspective on "Generative Data Science" and its profound impact on shaping the trustworthy landscape of artificial intelligence.
About the Speaker:
Guang Cheng is a Gradudate Vice Chair, Professor of Statistics and Data Science at UCLA, and also leading the Trustworthy AI Lab (https://www.stat.ucla.edu/~guangcheng/). He received his BA in Economics from Tsinghua University in 2002, and PhD in Statistics from University of Wisconsin-Madison in 2006. His research interests include generative data science, statistical machine learning and deep learning. Cheng is an Institute of Mathematical Statistics Fellow, Simons Fellow in Mathematics, NSF CAREER awardee and was also a member in the Institute for Advanced Study, Princeton.
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