Statistical Foundations and Applications of Machine Learning and AI

In celebration of Professor Shaw-Hwa Lo’s 70th Birthday and his longtime collaboration with Professor Herman Chernoff, this symposium includes presentations on the latest advances in statistical research. 

Featuring presentations by Professor Lo’s former students, collaborators, and friends, this symposium will highlight contributions to foundational statistical areas, along with applications in machine learning and artificial intelligence.

A special session on collaboration and interdisciplinary research will feature the virtual participation of Professor Chernoff. 

Shaw-Hwa Lo began his career as a mathematical statistician and his early contributions to the field were in asymptotics theory, survival analysis, and resampling methods. During his 30+ years career at Columbia, he has continuously expanded his research interests to solve some of the most challenging problems posed by big data. In particular, starting in the 1990s, he started a long-lasting and fruitful collaboration with Professor Herman Chernoff at Harvard that has led to innovative statistical methods for deciphering the genetic basis of complex human traits. Lo’s innovations in statistics have contributed to multiple disciplines such as molecular biology, transportation and medicine. In recognition of his life-time achievements the New England Statistics Society (NESS) recently gave him the inaugural Chernoff Excellence in Statistics Award, its highest honor. Read more about Professor Lo’s life and career in this feature article on his Chernoff award

Symposium DetailsTentative Schedule and Program 

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