Irina Rish, Ph.D., is a research staff member at IBM® T. J. Watson Research Center. She received an M.S. in applied mathematics from Moscow Gubkin Institute, Russia, and a Ph.D. in computer science from the University of California, Irvine. Dr. Rish""s primary research interests are in the areas of probabilistic inference, machine learning, and information theory. In particular, she has been working on approximate inference in probabilistic graphical models, information-theoretic experiment design, active learning, and their applications to automated management of complex distributed systems. Dr. Rish also taught several machine learning courses at the Electrical Engineering and Computer Science departments of Columbia University as an adjunct professor.

Natalia Odintsova worked at IBM T. J. Watson Research Center on algorithms and software for problem diagnosis in distributed systems and was one of the primary developers of RAIL tool and demonstration as well as tools for network topology analysis and cost-efficient probe selection. Mrs. Odintsova holds an M.S. in physics from Lomonosov University in Moscow, Russia, and an M.S. in computer science from Polytechnic University, N.Y. Her research interests include machine learning, distributed systems management, and graph visualization algorithms.

Genady Grabarnik, Ph.D., works in the Distributed Computing Department at the IBM T. J. Watson Research Center in Hawthorne, N.Y. He received his Ph.D. from the Mathematical Institute of the Academy of Science, Uzbekistan. Dr. Grabarnik's research interests include operator algebras, automated planning, data mining, and management of computer systems.

The team would like to thank Shang Guo and David Loewenstern for further extending the functionality of RAIL, as well as Mark Brodie, Alina Beygelzimer, and Shang Ma for contributing their ideas at various stages of the project. The team would especially like to thank Herb Lee and his EPP team, particularly Mariusz Sabath and Jeff Perry, for helping to combine RAIL with the EPP measurement tool, and for multiple other contributions at various stages of their joint project, from putting together the RAIL/EPP demonstration to maintaining the production version in multiple customer environments.