This workshop will bring together active researchers in our region with a strong interest in Applied Probability. Leading international invited speakers will present challenging topics and latest results in the frontier. New theoretical and methodological contributions to Applied Probability will be discussed, along with interesting applications of new and existing techniques to fields such as epidemiology, ecology, finance, and queueing systems and networks, amongst many others.

Invited speakers:

A/Prof. Ton Dieker (Georgia Institute of Technology)

A/Prof. Ton Dieker is a leader in the international Applied Probability community, with expertise in stochastic networks and stochastic analysis of algorithms. A/Prof. Dieker has achieved major breakthroughs in several challenging problems, most notably in the conjecture about the convergence rate to stationarity in Markov chains. His significant contributions were recognized through the Goldstine Fellowship from IBM Research, a CAREER Award from the National Science Foundation, and the Erlang Prize from the INFORMS Applied Probability Society (2012). He serves on the editorial boards of Operations Research and Mathematics of Operations Research. A/Prof. Dieker obtained an MS (Operations Research) (2002) from the Vrije Universiteit Amsterdam, and a PhD in Mathematics (2006) from the University of Amsterdam. He joined Georgia Institute of Technology in 2008, where he is the Fouts Family Associate Professor in the Milton School of Industrial and System Engineering.

A/Prof. Mariana Olvera-Cravio (Columbia University)

A/Prof. Mariana Olvera‐Cravioto has made major contributions in the asymptotic analysis involving heavy‐tailed distributions. Her current work is focused on the analysis of information ranking algorithms and their large‐scale behavior, which is closely related to the study of the asymptotic properties of solutions to certain stochastic recursions, in particular, weighted branching processes. A/Prof. Olvera­‐Cravioto obtained an MS (Statistics) (2004) and a PhD (2006) from Stanford University. She has been at Columbia University since 2006.

Prof. Kavita Ramanan (Brown University)

Kavita Ramanan works on probability theory, stochastic processes and their applications. Her focus has been to develop basic mathematical tools for the study of stochastic processes that arise in applications, especially those modeling stochastic networks. In recognition of her fundamental work on reflected processes and large deviations, she was awarded the Erlang prize in 2006 for “outstanding contributions to applied probability” by the INFORMS Applied Probability Society. In addition, she has contributed to a number of other areas such as Gibbs measures, phase transitions and measure valued processes. She was also granted several patents for applied work that she carried out while at Bell Laboratories.

Recent Posts