Manjira Sinha

Title: Manjira Sinha: Innovator in Transferable Feature Representations and Stance Classification

Introduction

Manjira Sinha is a prominent inventor based in Bengaluru, India. She has made significant contributions to the fields of machine learning and data classification. With a total of 5 patents to her name, her work focuses on developing methods that enhance the understanding and processing of data across various domains.

Latest Patents

One of her latest patents is titled "Method and system for learning transferable feature representations from a source domain for a target domain." This invention illustrates a domain adaptation method that enables the learning of transferable feature representations. The method involves receiving input data that includes labeled instances from a source domain and unlabeled instances from a target domain. It aims to learn a common representation shared between both domains, allowing for effective labeling and classification of data.

Another notable patent is "Stance classification of multi-perspective consumer health information." This invention provides a method, system, and apparatus for automatic stance classification. It involves collecting propositions relevant to a query and classifying their stance based on whether they support, oppose, or are neutral regarding the query. This classification can be achieved using approaches such as SVM-Based Stance Classification and Neural Network Stance Classification.

Career Highlights

Throughout her career, Manjira has worked with reputable companies, including Conduent Business Services and Xerox Corporation. Her experience in these organizations has contributed to her expertise in the field of data science and machine learning.

Collaborations

Manjira has collaborated with talented individuals such as Shourya Roy and Himanshu Sharad Bhatt. These collaborations have likely enriched her work and led to innovative solutions in her projects.

Conclusion

Manjira Sinha is a remarkable inventor whose work in transferable feature representations and stance classification has made a significant impact in the field of machine learning. Her contributions continue to advance the understanding of data processing and classification techniques.