Kolkata, India

Arpita Kundu

USPTO Granted Patents = 2 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

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2 patents (USPTO):Explore Patents

Title: Arpita Kundu - Innovator in Technical Question Generation

Introduction

Arpita Kundu is a notable inventor based in Kolkata, India. He has made significant contributions to the field of Natural Language Processing (NLP) through his innovative work. His research focuses on enhancing the generation of technical questions from document structures, which has implications for educational technology and automated learning systems.

Latest Patents

Arpita holds a patent titled "Method and system for document structure based unsupervised long-form technical question generation." This patent describes a method for generating long-form technical questions from textbook documents. The system begins by receiving a textbook document and extracting PDF metadata using NLP techniques. It identifies various structures within the document based on this metadata. Subsequently, the system generates a range of long-form technical questions using predefined templates, which are evaluated through multiple metrics. This innovative approach aims to finetune a supervised question generation model, ultimately improving the quality of questions derived from document structures. He has 1 patent to his name.

Career Highlights

Arpita Kundu is currently employed at Tata Consultancy Services Limited, where he applies his expertise in NLP and question generation. His work at TCS allows him to collaborate with other talented professionals in the field, contributing to advancements in technology and education.

Collaborations

Some of his coworkers include Subhasish Ghosh and Indrajit Bhattacharya, who work alongside him in various projects at Tata Consultancy Services Limited.

Conclusion

Arpita Kundu's innovative contributions to technical question generation highlight the potential of NLP in transforming educational tools. His work not only enhances the learning experience but also sets a foundation for future advancements in automated question generation.

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