Biographical sketches of authors

Yixin Diao   IBM Research Division, Thomas J. Watson Research Center, P.O. Box 704, Yorktown Heights, New York 10598 (electronic mail: diao@us.ibm.com). Dr. Diao is a postdoctoral Fellow at the Thomas J. Watson Research Center. He received his Ph.D. degree in electrical engineering from Ohio State University in 2000. He has conducted research on fault tolerant control system design using an adaptive fuzzy/neural approach, intelligent reasoning for robust fault diagnosis, and nonlinear dynamic system modeling with hierarchical learning structure and multivariate statistical methods. He joined IBM Research in 2001. His work involves increasing the adaptive and learning abilities of computing systems to unknown and time-varying environments by exploiting techniques from control theory, machine learning, and distributed agents. In particular, he is working with ABLE to develop generic adaptive agents for automated server tuning. Dr. Diao has authored around 20 technical papers, and his research interests include computer performance management, intelligent systems and control, adaptive systems, and stability analysis.

Joseph L. Hellerstein   IBM Research Division, Thomas J. Watson Research Center, P.O. Box 704, Yorktown Heights, New York 10598 (electronic mail: hellers@us.ibm.com). Dr. Hellerstein manages the Systems Management Research Department with projects such as event mining, event prediction, intelligent probing, automated diagnosis, and generic adaptive control. He received his Ph.D. degree in computer science from the University of California at Los Angeles in 1984. He has taught at Columbia University and has published approximately 70 papers.

Sujay Parekh   IBM Research Division, Thomas J. Watson Research Center, P.O. Box 704, Yorktown Heights, New York 10598 (electronic mail: sujay@us.ibm.com). Mr. Parekh is a research associate at the Thomas J. Watson Research Center. He received his B.S. degree in computer science and B.A. in mathematics at Cornell University in 1993, and his M.S. degree in computer science at the University of Washington in 1996. His research interests revolve around automating computing systems, both simple and complex, and his previous work has included projects in AI planning, machine learning, computer architecture, scheduling algorithms, and feedback-driven control.