Marta Arias received her bachelor's degree in Computer Science from the Polytechnic University of Catalunya (Barcelona, Spain) in 1998. After that she worked for a year at Incyta S.A. (Barcelona, Spain), a company specializing in software products for Natural Language Processing applications. She then enrolled in the graduate student program at Tufts University, recieving her PhD in Computer Science in 2004. That same year she joined the Center for Computational Learning Systems of Columbia University as an Associate Research Scientist. Dr. Arias' research interest include the theory and application of machine learning.

Dr. Sally Goldman is the Edwin H. Murty Professor of Engineering at Washington University in St. Louis and the Associate Chair of the Department of Computer Science and Engineering. She received a Bachelor of Science in Computer Science from Brown University in December 1984. Under the guidance of Dr. Ronald Rivest at the Massachusetts Institute of Technology, Dr. Goldman completed her Master of Science in Electrical Engineering and Computer Science in May 1987 and her Ph.D. in July 1990. Dr. Goldman's research is in the area of algorithm design and analysis and machine learning with a recent focus on applications to the area of content-based image retrieval. Dr. Goldman has received many teaching awards and honors including the Emerson Electric Company Excellence in Teaching Award in 1999, and the Governor's Award for Excellence in Teaching in 2001. Dr. Goldman and her husband, Dr. Ken Goldman, have just completed a book titled, A Practical Guide to Data Structures and Algorithms using Java.

Nina Mishra is an Associate Professor in the Computer Science Department at the University of Virginia. Her research interests are in data mining and machine learning algorithms as well as privacy. She previously held joint appointments as a Senior Research Scientist at HP Labs, and as an Acting Faculty member at Stanford University. She was Program Chair of the International Conference on Machine Learning in 2003 and has served on numerous data mining and machine learning program committees. She also serves on the editorial Boards of Machine Learning, IEEE Transactions on Knowledge and Data Engineering, IEEE Intelligent Systems and the Journal of Privacy and Confidentiality. She is currently on leave in Search Labs at Microsoft Research. She received a PhD in Computer Science from UIUC.

Kiri L. Wagstaff is a senior researcher at the Jet Propulsion Laboratory in Pasadena, CA. She is a member of the Machine Learning and Instrument Autonomy group, and her focus is on developing new machine learning methods that can be used for data analysis on-board spacecraft. She has applied these techniques to data being collected by the EO-1 Earth-orbiting spacecraft, Mars Odyssey, and Mars Pathfinder. She has also worked on crop yield prediction from orbital remote sensing observations, the fault protection system for the MESSENGER mission to Mercury, and automatic code generation for the Electra radio used by the Mars Reconnaissance Orbiter and the Mars Science Laboratory. She is very interested in issues such as robustness (developing fault-tolerant machine learning methods for high-radiation environments) and infusion (how can machine learning be used to advance science?). She holds a Ph.D. in Computer Science from Cornell University and is currently working on an M.S. in Geology from the University of Southern California.