Date(s) - 02/12/2019 - 05/12/2019
As you may be aware Hong Kong is going through a tough time now, and we understand that this arouses much concern and worry from many of you, especially for those who will be travelling to Hong Kong. In view of this fluid situation, it is decided that the 11th IASC-ARS Conference will be CANCELLED. Above all, your safety is our top priority. Please allow us to have some time to handle the follow-up issues. Please also help to relay the message and inform your speakers if you are session organisers.
Thank you for your support to the event and understanding. We believe this is the best decision we could make under current situation.
Philip L.H. Yu
Chairman, Local Organising Committee
The 11th IASC-ARS Conference
The 11th IASC-ARS Conference (https://saasweb.hku.hk/conference/iasc-ars2019/) will be held at the University of Hong Kong, China, on 2-5 December 2019. The theme of the conference is “Statistical Computing for AI and Big Data”. The aim of the conference is to provide a forum for the discussion and exchange of ideas, new concepts and recent methods in statistics. Philip Leung-ho Yu from the Department of Statistics and Actuarial Science of the University of Hong Kong will be the General Chair of the conference.
The Local Organizing Committee of the IASC-ARS 2019 invites submissions of Invited Session Proposals. An invited session proposal includes a session title, general description of the session, list of speakers, and tentative talk titles. Submissions may be made by email to firstname.lastname@example.org. The submission deadline is 28 February 2019. The organizers will be notified of the review committee’s decision by 31 March 2019. Click here for the poster of Call for Invited Session Proposals for the details.
Keynote Speakers: Wolfgang Karl Hӓrdle, Jun Liu, and Qiwei Yao
Local organizer: Department of Statistics and Actuarial Science, The University of Hong Kong
We look forward to seeing you in Hong Kong!
For more information: https://saasweb.hku.hk/conference/iasc-ars2019/