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There is a dramatic shift in the world economy towards services. Because the services transcend across heterogeneous organizations, technologies, processes and people, there is an associated need for a vast amount of information processing. In spite of impressive gains, there are still many technological challenges that cannot be tackled by the computational prowess alone. I will describe some of these challenges in the context of Information Mining and Services Research through specific examples from widely different domains like search engines, imaging and software engineering. On the surface, traditional information theoretic considerations do not offer solutions. Accordingly, researchers looking for conventional solutions would have difficulty in solving these problems. I will describe how alternative formulations based on statistical underpinnings have played a critical role in addressing these challenges.

Siddhartha Dalal is a Vice President at Xerox. Sid’s industrial research career began at Math Research Center at Bell Labs followed by Bellcore/Telcordia Technologies. His recent contributions have concentrated on comprehending systems’ complexity through applied statistical and computer science technologies and developing information and network services. He has co-authored seventy publications, several patents and two NRC reports covering the areas of risk analysis, statistical and econometrics modeling, stochastic optimization, data/document mining, software engineering and Bayesian methods.