Diana Palsetia

I am a Ph.D. student under the supervision of Prof. Alok Choudhary, in the Department of Electrical Engineering and Computer Science(EECS) at Northwestern University. I am a member of the Center for Ultra-scale Computing and Information Security(CUCIS) group. I received my bachelors in Computer Engineering from Michigan Technological University and masters in Electrical Engineering from University of Wisconsin-Madison. Prior to joining Northwestern University, I was teaching in the Department of Computer and Information Science(CIS) at the University of Pennsylvania.

My research interests are in the areas of High-Performance Computing, Data Mining, and Parallel and Distributed Computing. My current research focuses on building scalable and efficient data mining applications. Data mining or knowledge discovery systems today consist essentially of repackaged versions of traditional machine-learning algorithms for classification and clustering. However they are intensive in terms of both computation and I/O. Also, most algorithms are irregular i.e. they are highly dependent on input data. Therefore there is strong motivation for the development of new paradigms, programming environments, and parallel algorithms that support scalable and efficient applications. My current work focuses on designing data mining algorithms for semi-structured, graph and scientific datasets.


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