Narayana Prasad Santhanam is a Professor in the Department of Electrical Engineering at the University of Hawaii, College of Engineering. His research spans theoretical and practical aspects of information theory, statistical learning, and signal processing, with particular focus on high-dimensional and complex problems that cannot be addressed by traditional statistical methods. Santhanam maintains an active research program funded by the National Science Foundation and teaches courses including Probability and Statistics, Linear Algebra and Machine Learning, and Information Theory. Santhanam's research interests center on the intersection of statistical learning and information theory, particularly in high-dimensional settings. His work addresses fundamental questions about when learning is possible, how to characterize non-uniform learning, and how to interpret data from complex sources like slow mixing Markov processes. He has made significant contributions to understanding the limitations of statistical methods in large alphabet scenarios, where traditional approaches fail. His research has important applications in diverse fields including genetic data analysis, risk management, smart grids, and text processing. His recent publications reveal a consistent focus on theoretical foundations with practical applications. Santhanam's work often explores the connections between seemingly disparate fields, bringing combinatorial and probabilistic approaches to bear on complex problems. A notable trend is his development of frameworks for pointwise convergence rather than uniform convergence in statistical estimation, which has significant implications for handling large alphabet problems where traditional methods break down. 2006 IEEE Information Theory Society Best Paper Award 2003 Capocelli Prize Santhanam has successfully secured significant research funding as Principal Investigator on an NSF award of approximately $1.1 million to examine the interplay of statistics and information theory, with applications to document classification and genetic analysis. He has also served as co-PI on multiple NSF awards totaling roughly $800,000 for research on channels with memory and smart grid organization. His research group includes students M. Asadi, A. Esraghi, A. Lee, M. Hosseini, R. Paravi, and G. Tobin, who contribute to projects spanning statistical learning, information theory, and their applications to biological and engineering problems. Santhanam has co-organized three major workshops on large alphabet information theory and statistics, bringing together over 80 researchers from diverse disciplines including biology, computer science, economics, information theory, mathematics, networking, and statistics.
