Dr. Sanjukta Bhowmick
University of Nebraska at Omaha

Title:
Novel Applications of Graph Embedding Techniques

Abstract:
Force-directed graph embedding algorithms, like the Fruchterman-Reingold method, are typically used to generate aesthetically pleasing graph layouts. At a fundamental level, these algorithms are based on manipulating the structural properties of the graph to match them to certain spatial requirements. This relation between structural and spatial properties is also present in other areas beyond graph visualization. In this talk, I will discuss how graph embedding can be used  in diverse areas such as (i) improving the accuracy of unsupervised clustering, (ii) creating good quality elements in unstructured meshes and (iii) identifying perturbations in large-scale networks.

Bio:
Dr. Sanjukta Bhowmick is an Assistant Professor in the College of Information Science and Technology at the University of Nebraska at Omaha.  She received her Bachelor of Technology degree from the Haldia Institue of Technology, West Bengal, India and her Ph.D. in Computer Science (with a minor in High Performance Computing) from the Pennsylvania State University and after her Ph.D. held a joint postdoctoral research position between Columbia University and Argonne National Laboratory.  Dr. Bhowmick’s  core research area  involves the development of high performance computing algorithms for large scale combinatorial and numerical problems arising in varied applications such as social networks, computational fluid dynamics, datamining and bioinformatics. Her recent research includes large scale data analysis using combinatorial algorithms such as force-directed graph embedding methods and parallel algorithms for community detection in large dynamic networks.

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