The 3rd Joint Seminar on Computational Intelligence will be co-locating with NCCIT2017 & IC2IT2017, Arnoma Grand Bangkok, July 6-7, 2017. It will be held on 7 July 2017.
This is a very good opportunity to share and discuss your work with other researchers in the field of computational intelligence. We would like to invite you to participate an one-day event. Click here to register now, https://goo.gl/forms/Fk3GvDsxFCQJhfNs1
If you are interested in presenting your work at this seminar, please register your abstract (maximum 300 words for presentations) before 10 June 2017 at https://goo.gl/forms/Fk3GvDsxFCQJhfNs1
Notification of Acceptance: TBC
|08:30 – 09:00||Registration|
|NCCIT 2017 & IC2IT 2017 Session|
|09:00 – 10:15||Keynote Speech, “Machine Learning Trends for Big Data” by Professor Dr. Prabhas Chongstitvatana, Chulalongkorn University.|
|10:15 – 10:45||Break|
|IEEE Computational Intelligence System Society Thailand Chapter Session|
|Invited Talk 1 (Chair Session: Dr. Kitsuchart Pasupa)|
|10:45 – 12:00||“Computational Intelligence and Big Data Challenges in Computational Epidemiology and Population Health“, by Prof. Dr. Armin R. Mikler, University of North Texas, USA.
Abstract: The development of computational approaches to solving problems in Public Health has commenced only about two decades ago and has led to the emergence of the field of Computational Epidemiology. Its primary goal is to provide health researchers with computational tools that facilitate the prediction and analysis of the progression of diseases in time and space. Whether modeling an Influenza epidemic in Germany or the spread of Dengue Fever in Thailand, computational models must be developed, which are informed by data from disparate sources. The design, implementation, and execution of such models represents a significant scientific challenge as it is often difficult to validate their fidelity. Further, data availability and representation across different geographic regions is inconsistent at best, which necessitates the design of region specific models. In this tutorial, we will introduce Computational Epidemiology as a data-centric example of computational intelligence for which Big Data challenges will have to be addressed by today’s computer and information scientists. We will exemplify the types of data that will have to be integrated to inform model development in an effort to provide computational tools to researchers and practitioners in the domain of Population Health.
|12:00 – 13:00||Lunch|
|IEEE CIS Student Talk 1 (Chair Session: Prof. Armin Mikler)|
|13:00-13:20||Student Talk 1 [KMUTNB]|
|13:20 – 13:40||Student Talk 2 [KMITL]|
|13:40 – 14:00||Student Talk 3 [KMUTT]|
|14:00 – 14:20||Break|
|Invited Talk 2 (Chair Session: Dr. Maleerat Sodanil)|
|14:20 – 15:20||Talk by Prof. Gerald Quirchmayr, University of Vienna, Austria|
|IEEE CIS Student Talk 2 (Chair Session: Prof. Armin Mikler)|
|15:20 – 15:40||Student Talk 4 [KMUTNB]|
|15:40 – 16:00||Student Talk 5 [KMUTL]|
|16:00 – 16:20||Student Talk 6 [KMUTT]|