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The Tenth International Conference on Matrix-Analytic Methods in Stochastic Models (MAM10)

13 – 15 February 2019, University of Tasmania, Hobart

Hobart

Matrix-Analytic Methods in Stochastic Models (MAM) conferences aim to bring together researchers working on the theoretical, algorithmic and methodological aspects of matrix-analytic methods in stochastic models and the applications of such mathematical research across a broad spectrum of fields, which includes computer science and engineering, telephony and communication networks, electrical and industrial engineering, operations research, management science, financial and risk analysis, bio-statistics, and evolution.

The conference will provide an international forum for:
  • Presenting recent results on theory, algorithms and applications concerning matrix-analytic methods in stochastic models;
  • Discussing methodologies and the related algorithmic analysis;
  • Improving collaborations among researchers in applied probability, engineering and numerical analysis;
  • Tracing the current state of the art and the lines of the future research, pointing out the main topics of interest.

Keynote speakers:

Paper submission:

The organising committee is currently negotiating with the publishers of Stochastic Models, with a view to reserve a Special Issue of the journal to papers associated with MAM10. Research results presented at the conference can be submitted to that Special Issue, which will undergo an independent evaluation process according to the regular standards of Stochastic Models.

For details of conference registration and conference abstract/extended abstract submission, see here.


Information for delegates with parenting responsibilites in: 

pdf

  

Organising Committee:

Conference Chair:      
Program Co-Chairs:   
Local organisation:     


Steering Committee:

Attahiru S. Alfa, University of Manitoba, Canada, and University of Pretoria, South Africa
Guy Latouche, Universite Libre de Bruxelles, Belgium
Miklós Telek, Technical University of Budapest, Hungary
Peter Taylor, University of Melbourne, Australia
Qi-Ming He, University of Waterloo, Canada
V. Ramaswami, Statmetrics, LLC, United States

Program Committee:

Sřren Asmussen, Aarhus University, Denmark
Nigel Bean, Adelaide University, Australia
Peter Braunsteins, University of Melbourne, Australia
Peter Buchholz, Technische Universität Dortmund, Germany
Giuliano Casale, Imperial College London,
UK Srinivas Chakravarthy, Kettering University, United States
Tuğrul Dayar, Bilkent University, Turkey
Mark Fackrell, University of Melbourne, Australia
Qi-Ming He, University of Waterloo, Canada
Andras Horvath, Universitŕ di Torino, Italy
Gábor Horváth, Budapest University of Technology and Economics, Hungary
Udo Krieger, IEEE, Germany
Barbara Margolius, Cleveland State University, United States
Stefano Massei, École Polytechnique Fédérale de Lausanne, Switzerland
Beatrice Meini, University of Pisa, Italy
Masakiyo Miyazawa, Tokyo University of Science, Japan
Yoni Nazarathy, University of Queensland, Australia
Giang Nguyen, Adelaide University, Australia
V. Ramaswami, Statmetrics, LLC, United States
Rotislav Razumchik, Russian Academy of Sciences, Russia
Alexander Rumyantsev, Russian Academy of Sciences, Russia
Evgenia Smirni, College William & Mary, United States
Aviva Samuelson, University of Tasmania, Australia
Mark Squillante, IBM, United States
Tetsuya Takine, Osaka University, Japan
Peter Taylor, University of Melbourne, Australia
Miklós Telek, Technical University of Budapest, Hungary
Erik van Doorn, University of Twente, Netherlands
Benny van Houdt, University of Antwerp, Belgium
Eleni Vatamidou, University of Lausanne, Switzerland