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2024 Statistical Frontiers in the AI Era Conference, Taipei
Invited

Speakers

(in order of presentation)

Distinguished Professor

Jane-Ling Wang

Department of Statistics, University of California, Davis, U.S.A.

Professor

George Michailidis

Department of Statistics, University of California, Los Angeles, U.S.A.

Senior Fellow

Fabrizio Ruggeri

Institute for Applied Mathematics and Information Technologies (IMATI), CNR, Italy

Professor and Harold L. Moses Chair in Cancer Research

Yu Shyr

Department of Biostatistics, Vanderbilt University Medical Center, U.S.A.

Stephen R. Pierce Family Goldman Sachs Professor in Science and Human Health

Wing-Hung Wong

Department of Statistics, Stanford University, U.S.A.

Panelists

Professor

Ching-Shui Cheng

Department of Statistics, University of California, Berkeley, U.S.A.

Professor

Tomoyuki Higuchi

Department of Industrial and Systems Engineering, Chuo University, Japan

Michael B. Woodroofe Collegiate Professor of Statistics

Tailen Hsing

Department of Statistics, University of Michigan, U.S.A.

Professor

Ker-Chau Li

Department of Statistics and Data Science, University of California Los Angeles, U.S.A.

Distinguished Professor

Regina Y. Liu

Department of Statistics, Rutgers University, U.S.A.

H.G.B. Alexander Professor of Econometrics and Statistics

Ruey S. Tsay

Booth School of Business, University of Chicago, U.S.A.

Professor and Coca-Cola Chair in Engineering Statistics

Chien-Fu Jeff Wu

Georgia Institute of Technology, U.S.A.

Activity

Friday

July 5

13:00-13:10

Opening Remarks

Group photo

Hsin-Chou Yang

13:10-14:10

Feature Talk by Newly Elected Academician

Chair: Hsin-Chou Yang

Jane-Ling Wang

Statistics in the Age of AI
14:10-14:30 Coffee Break
14:30-16:10

Distinguished Lectures

Chair: Chun-houh Chen

Wing-Hung Wong

Applications of AI methods
in mainstream statistics

(Webex Online)

George Michailidis

A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity

Chair: Yen-Tsung Huang

Fabrizio Ruggeri

Is there a future for traditional stochastic models in business and industry in the AI and ML era?

Yu Shyr

Omics Data in the AI Era: Unveiling Statistical Advances and Challenges
16:10-16:30 Coffee Break
16:30-17:50

Panel Discussion

What Can AI do for Statistics and What Can Statistics Do for AI?

Moderator:Ruey S. Tsay

Interactive discussion with audience Q&A

Ching-Shui Cheng, Tomoyuki Higuchi, Tailen Hsing, Ker-Chau Li,
Regina Y. Liu, Jane-Ling Wang, Chien-Fu Jeff Wu
George Michailidis, Fabrizio Ruggeri, Yu Shyr

17:50-18:00

Closing Remarks

Hsin-Chou Yang

VENUE

中央研究院 人文館 國際會議廳

International Conference Hall (3F)

Humanities and Social Sciences Building,
Academia Sinica

Map of Academia Sinica