9th Bayesian, Fiducial, and Frequentist (BFF) Conference
May 12, 2025 - 7:00 AM Eastern Time
May 14, 2025 - 6:00 PM Eastern Time
Location: IUI University Tower 850 W Michigan St University Indianapolis, IN 46202
The BFF9 on May 12-14, 2025 is hosted by the Department of Statistics in Purdue Indy. The event will be held at the Tower Ballroom Foyer.
We are still finalizing the details. More information will be available soon. Thank you for your patience!
- Poster Session
- Banquet Information
Important Links:
Poster presentations are available for students and junior researchers. Travel support is provided for selected student and junior presenters.
About BFF:
The Bayesian, Fiducial, and Frequentist (BFF) community began in 2014 to facilitate scientific exchange among data scientist and scholars in related fields that develop new methodologies and within the foundational principles of data science. The community encourages and promotes research activities to bridge foundations on data-based decisions to facilitate objective and replicable scientific learning, and to develop analytic and computing methodologies for data analysis.
Over the last 10 years, BFF conferences have served as a venue to bring together researchers and practitioners from Bayesian analysis, fiducial statistics, and frequentist statistics with interest important open problems in both theory and implementation, and most importantly discuss future directions of such research. The diversity of the conference attendees has created a dynamic, in-depth exchange of thoughts and ideas like no other conference in data science.
Keynote Speakers
Xihong Lin, Harvard University
Karen Lynn Price, Eli Lilly
Banquet Speaker
Xiaoli Meng, Harvard University
Invited Speakers
Antik Chakraborty, Department of Statistics, Purdue University
Armine Bagyan, Department of Statistics, Penn State University
Bill Prucka, Eli Lilly
Bryon Aragam, Chicago Booth School of Business, University of Chicago
Daniel Alabi, Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign
Faming Liang, Purdue University
Fang Liu, University of Notre Dame
Guanyu Hu, The university of Texas Health Science Center at Houston
Hui Zou, School of Statistics, U of Minnesota
James Bailie, Department of Statistics, Harvard University
Jan Hannig, Department of Statistics and Operations Research, University of North Carolina at Chapel Hill
Jianwei Chen, San Diego State University
Jing Lei, Carnegie Mellon University
Kyle Cranmer, Department of Physics, University of Wisconsin
Leonardo Cella, Wake Forest University
Li Wang, Abbvie
Lingsong Zhang, Purdue Unversity
Linjun Zhang, Department of Statistics, Rutgers University
Marco Avella-Medina, Department of Statistics, Columbia University
Minge Xie, Department of Statistics, Rutgers University
Nicole Pashley, Rutgers University
Peter Song, Department of Statistics, University of Michigan
Ping Ma, University of Georgia
Quan Zhou, Texas A&M Unversity
Razieh Nabi, Rollins School of Public Health, Emory University
Richard Payne, Eli Lilly
Run Zhang, Unlearn AI
Sally Paganin, Department of Statistics, Ohio State University
Sherry Xinlei Wang, The University of Texas at Arlington
Thomas Lee, UC Davis
Veronika Rockova, Chicago Booth School of Business, University of Chicago
Weijie Su, University of Pennsylvania
Weixin Yao, Department of Statistics, UC-Riverside
Xiaoli Meng, Harvard University
Xiaotong Shen, School of Statistics, U of Minnesota
Xinran Li, University of Chicago
Xiwei Tang, University of Texas at Dallas
Ya'acov Ritov, Department of Statistics, University of Michigan
Yazhen Wang, University of Wisconsin- Madison
Yichen Cheng, Georgia State University
Ying Nian Wu, Department of Statistics, UCLA
Ying Nian, University of California, Los Angeles
Yves Atchadé, Department of Mathematics and Statistics, Boston University
Zhanyu Wang, Research Scientist, Meta