YEQT XIII : "Data-Driven Analytics and Optimization for Stochastic Systems"
Oct 16 - Oct 18
The Young European Queueing Theorists (YEQT) workshops are organized on a yearly basis, and this year the 13th edition of the workshop will take place in October 2019. The aim of these workshops is to bring together young researchers, PhD students or recently appointed lecturers and assistant professors, and world-leading experts in order to share and discuss research related to queueing theory, operations research, applied probability and related areas. This event provides an excellent opportunity for developing researchers to interact and exchange ideas in an informal, friendly, yet research-focused setting. The workshop program will consist of presentations from young researchers and several keynote presentations and tutorials by prominent researchers.
The theme for the YEQT workshop this year is "Data-Driven Analytics and Optimization for Stochastic Systems". The workshop will focus on combining theoretical stochastic modelling and optimization together with modern statistical techniques in order to tackle important problems that are prevalent today in various domains.
In many applications of queueing theory, such as healthcare, transportation systems, service operations, and communication networks, there is inherent uncertainty in the system behavior which calls for stochastic modelling, and an abundance of data which calls for smart statistical techniques that enable improving the understanding and ultimately the performance optimization of the system. There is often a gap between research focused on the former (i.e. stochastic/statistical modelling) and research focused on the latter (i.e. optimization techniques). However, the increasing availability of real-time data offers new opportunities for not only statistical analysis, and optimization of decision making but especially their integration. In fact, because all modern systems generate their own data, it is now possible to integrate and tailor statistical methods and optimization to individual systems, where before these steps were typically separate, leading to so-called data-driven analytics and optimization.
|Mark van der Boor||TU Eindhoven|
|Collin Drent||TU Eindhoven|
|Liron Ravner||University of Amsterdam|
|Mor Armony||New York University|
|Noah Gans||Pennsylvania University|
|Peter Glynn||Stanford University|
|Ger Koole||VU Amsterdam|
|Michel Mandjes||University of Amsterdam|
|John Tsitsiklis||Massachusetts Institute of Technology|
Information on travel, location etc. : INFORMATION