Sanjeeb Dash IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598 (sanjeebdus.ibm.com). Dr. Dash is a Research Staff Member. He received a Ph.D. degree in computational and applied mathematics from Rice University in 2001 and worked as a Postdoctoral Fellow at Princeton University before joining the IBM Research Division in 2002. His research interests lie in the area of discrete optimization, especially mixed-integer programming. He has worked on many aspects of cutting-plane techniques for solving mixed-integer programming problems. Dr. Dash is a coauthor of the linear programming solver QSopt, and of QSopt_ex, an exact linear programming solver.

Jayant Kalagnanam IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598 (jayantus.ibm.com). Dr. Kalagnanam is a research manager in the Mathematical Sciences Department. He holds a Ph.D. degree from Carnegie Mellon University and joined the IBM Research Division in 1996. The focus of his research is manufacturing sciences. He has worked with various steel companies to develop and deploy optimization and scheduling solutions for daily plant operations. Dr. Kalagnanam has more than 20 journal publications and more than ten patents and filings.

Chandra Reddy IBM Research Division, Thomas J. Watson Research Center, P.O. Box 218, Yorktown Heights, New York 10598 (creddyus.ibm.com). Dr. Reddy joined IBM in 1998 after receiving a Ph.D. degree in computer science from Oregon State University. Since then, he has been developing solutions to several optimization and scheduling problems arising in the steel industry. Several of these solutions have been successfully deployed and are in production at two of the world's leading steel makers. His research prior to joining IBM focused on both theoretical and practical aspects of machine learning of compact hierarchical control knowledge for planning and problem solving. Dr. Reddy's research interests include scheduling and optimization, machine learning for planning and classification, data mining, and artificial intelligence.

Sang Hwa Song Graduate School of Logistics, University of Incheon, Gyeonggi Province, Korea (songshincheon.ac.kr). Professor Song received a Ph.D. degree from the Department of Industrial Engineering at the Korea Advanced Institute of Science and Technology in 2003. He worked for the IBM Korea Technology Laboratory and IBM Business Consulting Services as a senior software engineer and senior consultant. Professor Song's research interests include supply chain management and an application of optimization theories in real-world business problems.