3rd International Conference on Performance Evaluation Methodologies and Tools

Increase font size Decrease font size

Invited plenary speakers

There will be 4 invited plenary speakers:



Université Paris Diderot, Paris 7, France.

Jean Mairesse obtained the Engineer degree from Ecole Polytechnique, France, in 1991, and from Ecole Nationale de la Statistique et de l'Administration Economique, France, in 1993. He received the Docteur en Sciences degree in Applied Mathematics from Ecole Polytechnique in 1995. Since 1996, he has been working for CNRS, now with the grade of Directeur de Recherche. His laboratory is LIAFA (Laboratoire d'Informatique et d'Algorithmique: Fondements et Applications), Université Paris 7, France. His main reseach interests are discrete event systems, combinatorial (semi)group theory, and random walks on algebraic structures.
Jean Mairesse's homepage.

Title: "Random walks on algebraic structures and discrete event systems"

Abstract: We study several models of Discrete Event Systems from which emerges the notion of random walks on groups or semigroups. First example, stochastic event graphs which correspond to random walks on semigroups of max-plus matrices. Second example, Tetris heap models which correspond to random walks on partially commutative groups or semigroups. Last example, zero-automatic queues which are markovian queues with a buffering mechanism evolving like a random walk on some infinite group. We are interested in the performance evaluation of these different models with a focus on getting explicit computational results.

Avishai (Avi) MANDELBAUM

William Davidson Faculty of Industrial Engineering and Management
Technion - Israel Institute of Technology, Haifa, Israel.


Prof. Avishai (Avi) Mandelbaum has a B.Sc. in Mathematics and Computer Science and an M.A. in Statistics, both summa cum laude from Tel-Aviv University. His Ph.D. is in Operations Research, from Cornell University. After graduation, in 1983, he joined the Graduate School of Business at Stanford University. He left the U.S.A., in 1991, to assume a position at the Technion, the Faculty of Industrial Engineering and Management (IEM). This faculty, as well as his current interests, constitute a convex-hull of all the areas that he has been in volved with.
At the Technion, Prof. Mandelbaum has been teaching courses in probability, stochastic processes and service engineering. In IE&M, he served as the coordinator of IE&M graduate studies and was the Associate Dean for Research; he is a past member of the Technion Academic Development Committee and a present member of the Prize committee of the Applied Probability Society. Since 1995, he has been the faculty advisor for IE&M outstanding students.
Prof. Mandelbaum's teaching has been acknowledged by the Technion Mani Award for Excellence in Teaching, 1999; the Technion Excellence in Teaching Award, 2000 (for the course Service Engineering); and the inaugural Meir Rosenblatt Prize for teaching, 2004. His research contributions have been acknowledged by the ORSIS Yosef Levy prize, 2001; the Mitchner Prize for Quality Sciences and Qaulity Management, 2003; and the inaugural Markov Lecture of the Applied Probability Society , INFORM 2005
Avishai Mandelbaum's homepage

Title: "QED Queues: Quality- and Efficiency-Driven Call Centers"

Abstract: Through examples of Service Operations, with a focus on Telephone Call Centers, I review empirical findings that motivate or are motivated by (or both) interesting research questions. These findings give rise to features that are prerequisites for useful service models, for example customers' (im)patience, time-varying demand, heterogeneity of customers and servers, over-dispersion in Poisson arrivals, generally-distributed (as opposed to exponential) service- and patience-durations, and more. Empirical analysis also enables validation of existing models and protocols, either supporting or refuting their relevance and robustness.
The mathematical framework for my models is asymptotic queueing theory, where limits are taken as the number of servers increases indefinitely, in a way that maintains a delicate balance against the offered-load. Asymptotic analysis reveals an operational regime that achieves, under already moderate scale, remarkably high levels of both service quality and efficiency. This is the QED Regime, discovered by Erlang and characterized by Halfin & Whitt. (QED = Quality- and Efficiency-Driven).
My main data-source is a unique repository of call-centers data, designed and maintained at the Technion's SEE Laboratory (SEE = Service Enterprise Engineering). The data is unique in that it is transaction-based: it details the individual operational history of all the calls handled by the participating call centers. (For example, one source of data is a network of 4 call centers of a U.S. bank, spanning 2.5 years and covering about 1000 agents; there are 218,047,488 telephone calls overall, out of which 41,646,142 where served by agents, while the rest were handled by answering machines.) To support data analysis, a universal data-structure and a friendly interface have been developed, under the logo DataMOCCA = Data MOdels for Call Centers Analysis. (I shall have with me DataMOCCA DVD's for academic distribution).
Background Reading
Gans, N., Koole, G., Mandelbaum, A. "Telephone Call Centers: Tutorial, Review and Research Prospects." Invited review paper by Manufacturing and Service Operations Management (M&SOM), 5 (2), 79141, 2003.
Brown, L., Gans, N., Mandelbaum, A., Sakov, A., Zeltyn, S., Zhao, L. and Haipeng, S. "Statistical Analysis of a Telephone Call Center : A Queueing-Science Perspective." Journal of the American Statistical Association (JASA), 100, 36-50, 2005.



National & Capodistrian University of Athens, Department of Physics, Division of Applied Physics, Athens, Greece

Aris Moustakas received a B.S. degree in physics from Caltech in 1990 and M.S. and Ph.D. degrees in theoretical condensed matter physics from Harvard University in 1992 and 1996, respectively. In 1998, he joined Bell Labs, Lucent Technologies, NJ, first in the Physical Sciences Division and then also in the Wireless Advanced Technology Laboratory. Since 2005 he is an assistant professor at the Physics Dept. of the National Capodistrian University of Athens. His current research interests lie in the areas of multiple antenna systems and the applications of game theory and statistical physics to the theory of communications and networks.
Aris Moustakas homepage.

Title: "Statistical Physics and Communications: Two unlikely partners"

Abstract: In the last few years, methods and ideas from the field of statistical physics have been applied in the communications theory community. I will make a brief overview of such methods, specifically random matrix theory and replica field theory, applied in the context of multi-antenna communications. Focusing on more recent results, I will also try to argue how these methods might be applicable in the context of wireless networks.



Massachusetts Institute of Technology Cambridge, MA, U.S.A.

John N. Tsitsiklis received the B.S. degree in Mathematics (1980),  and the B.S. (1980), M.S.  (1981) and Ph.D. (1984) degrees in  Electrical Engineering, all from M.I.T., where he is currently a  Clarence J Lebel Professor of Electrical Engineering. He has also  served as  a co-director of the MIT Operations Research Center (2002-5).
His research interests are in the fields of systems, optimization,  communications, control, and operations research. He has coauthored  four books and more than a hundred journal papers in these areas. His  awards include an Outstanding Paper Award by the IEEE Control Systems  Society (1986), the M.I.T. Edgerton Faculty Achievement Award (1989),  the Bodossakis Foundation Prize (1995), and the INFORMS/CSTS prize  (1997). He is a Fellow of IEEE and INFORMS, a member of the National  Academy of Engineering, and has been a member of the National Council  on Research and Technology in Greece.
John Tsitsiklis homepage.

Title: "Gossiping, Herding, Flocking, and Consensus"

Abstract: Motivated by a variety of contexts, including distributed  optimization, multiagent coordination, economics, sociology, and  animal behavior, there has been much recent activity on consensus  algorithms whereby a set of agents keep forming convex combinations  of their own tentative decisions with those of their neighbors. We  overview the history of such methods, application contexts, and  results on convergence and speed of convergence to a common decision.