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About

Abhijit Guha is a researcher specializing in intelligent document processing, computer vision, and the application of artificial intelligence to automate complex business workflows. His work sits at the intersection of machine learning and Robotic Process Automation (RPA), with a particular focus on solving real-world challenges in the title insurance domain. Guha's most influential contribution, "Hybrid Approach to Document Anomaly Detection," has garnered 70 citations since its 2020 publication, demonstrating significant community interest in his novel framework for identifying irregularities in business-critical documents. Building on this foundation, his 2022 paper on multi-modal digital document stream segmentation addresses the practical challenge of organizing heterogeneous scanned document packages, accumulating 21 citations in a short period. His work on IIRM introduces an innovative one-shot training paradigm using computer vision for structured document retrieval, pushing the boundaries of efficient model training with minimal labeled data. Collectively, Guha's research makes meaningful strides toward automating document-heavy industries, reducing human error, and enabling scalable intelligent automation pipelines — contributions that are increasingly relevant as organizations worldwide accelerate their digital transformation efforts.