About
As Statistics and Data Science continue to evolve in the big data era, we face new challenges that call for novel interdisciplinary research combining statistics, machine learning, econometrics, computer science, and biology. This 3-day conference brings together leading researchers from these various fields. They will offer new perspectives and methodologies, and address the opportunities and challenges of 21st century Data Science.
Organizers
Zheng Tracy Ke (Harvard University)
Weichen Wang (University of Hong Kong)
Confirmed Speakers
Krishnakumar Balasubramanian (University of California, Davis)
Jelena Bradic (University of California San Diego)
Tony Cai (University of Pennsylvania)
Yuejie Chi (Carnegie Mellon University)
David Choi (Carnegie Mellon University)
Edgar Dobriban (University of Pennsylvania)
Simon Du (University of Washington)
Philip Ernst (Rice University)
Jianqing Fan (Princeton University)
Yingying Fan (University of Southern California)
Yang Feng (New York University)
Yuqi Gu (Columbia University)
Lucas Janson (Harvard University)
Adel Javanmard (University of Southern California)
Jiashun Jin (Carnegie Mellon University)
Mladen Kolar (University of Chicago)
Eric Laber (Duke University)
Hongzhe Lee (University of Pennsylvania)
Jason D. Lee (Princeton University)
Runze Li (Penn State University)
Jun S. Liu (Harvard University)
Regina Liu (Rutgers University)
Jinchi Lv (University of Southern California)
Tengyu Ma (Stanford University)
Arian Maleki (Columbia University)
Rajarshi Mukherjee (Harvard University)
Peter XK Song (University of Michigan)
Weijie Su (University of Pennsylvania)
Stanislav Volgushev (University of Toronto)
Mengdi Wang (Princeton University)
Wanjie Wang (National University of Singapore)
Anru Zhang (Duke University)
Chunming Zhang (University of Wisconsin-Madison)
Cun-Hui Zhang (Rutgers University)
Heping Zhang (Yale University)
Hongyu Zhao (Yale University)
Ji Zhu (University of Michigan)
Agenda
Program
Links to these pages in progress...
Titles and Abstracts
Schedule
Graduate Students
The conference cordially invites the participation of students at the conference and hope students can benefit from the talks and networking opportunities. We have invited about 45 leading researchers covering a broad range of topics in statistics, biostatistics, machine learning and econometrics. A discounted registration fee is being offered to students. Please contact the organizers (weichenw@hku.hk) for the promotion code.
In addition, we would like to hold a poster session for students to present their interesting work. We plan to give out the NASDS Best Poster Award for students with excellent research contributions. This could be a good opportunity for students to present their interesting work. For those who are interested in participating, please fill out this application form (https://forms.gle/7agGxXiDZK17qnQP8) to apply for a poster presentation opportunity.
Event Type
- Affiliate Award Fund Eligible
- NISS Sponsored
Sponsor
Cost
Location
Policy
