Dipali Baviskar

Papers

Total Citations

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About

Dipali Baviskar is a researcher at the forefront of cognitive document processing and bibliometric analysis, with a focused interest in managing the deluge of unstructured data that modern organizations face. Her most-cited work, “A Bibliometric Survey on Cognitive Document Processing” (2020), addresses the critical challenge of handling heterogeneous data—from emails and social media to scanned documents and images—that must be stored and analyzed for extended periods. This survey systematically maps the evolving landscape of cognitive technologies that enable machines to understand, classify, and extract insights from unstructured information, a cornerstone for advancing intelligent automation. While her citation count of 3 reflects the niche and emerging nature of this field, Baviskar’s contribution lies in synthesizing fragmented research, providing a foundational roadmap for scholars and practitioners tackling data complexity. Her work underscores the growing need for scalable, AI-driven solutions in document processing, positioning her as a thoughtful voice in the intersection of information science and cognitive computing. For students and researchers exploring how to tame unstructured data, Baviskar’s survey offers a vital starting point for understanding the tools and trends shaping this domain.