Updates: you have reached the research webpage of Narayana Santhanam. What follows is a summary of the work I am doing. Some of the research topics below are with my students M. Asadi, A. Esraghi, A. Lee, M. Hosseini, R. Paravi and G. Tobin. For publications, please email me since despite my best efforts, this page is often out of date.

My work---some of which is with my current students: M. Asadi, A. Esraghi, A. Lee, M. Hosseini, R. Paravi and G. Tobin---spans several applications, but are connected by a set of probabilistic and combinatorial approaches. A lot of it---though not all---has to do with high dimensional problems---genetic data in biology, text data, and risk management in large financial instruments such as reinsurance, or rare event detection in very complex systems such as smart grids. Essentially, it is either futile or useless to handle problems involving this sort of data in the traditional sense. Yet, insights gained in one of these problems carry over to others as well, which makes a systematic instead of ad-hoc approach desirable.

A starting point for my personal evolution of ideas has been the following paper on probability estimation that won the prestigious Information Theory Society Paper Award . Since then, I have enjoyed expanding the horizons of undersampled problems using approaches and techniques that have been, at least to me, surprising and elegant.

This is in line with similar observations made by others as well--in the high dimensional domain, one has to typical rework and look at fundamental statistical problems in estimation, classification, and regression in an entirely new light. Practically, the commercial importance of a systematic theory of large alphabet applications cannot be understated in the fields mentioned above. Theoretically, they often force a deeper insight into even the simplest problems, and often involve unexpectedly beautiful mathematical results.

Workshops I have co-organized three workshops in the broad areas of large alphabet information theory and statistics---the first sponsored by the American Institute of Math and the NSF (2009), while the second was at the Banff International Research Station (2011) and a recent one funded by the NSF Center for Science of Information at Honolulu, HI. A total of over 80 researchers attended one or the other of these workshops, from diverse areas including biology, computer science, economics, information theory, mathematics, networking, and statistics.

Navigate below to see a summary of my recent work in various topics. If you are looking for any of my other publications, please email me.

Prediction and risk management

Lossy compression

Estimating channels with memory

Markov Random Fields

Entropy estimation

Bayesian non-parametrics

Large alphabet Markov sources

Other papers

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