Swati Jindal

Title: Swati Jindal: Innovator in Chromosome Classification Technology

Introduction

Swati Jindal is a prominent inventor based in Gurgaon, India. She has made significant contributions to the field of chromosome classification through her innovative work. Her dedication to advancing technology in this area has led to the development of a unique patent that enhances the accuracy of chromosome classification.

Latest Patents

Swati Jindal holds a patent for a "Method and system for automatic chromosome classification." This innovative system, also known as a Residual Convolutional Recurrent Attention Neural Network (Res-CRANN), utilizes the properties of band sequences of chromosome bands for effective classification. The Res-CRANN is an end-to-end trainable system that extracts a sequence of feature vectors from the feature maps produced by convolutional layers of Residual neural networks (ResNet). These feature vectors correspond to visual features representing chromosome bands in a chromosome image. The sequence of feature vectors is then processed by Recurrent Neural Networks (RNN) augmented with an attention mechanism. This approach allows the RNN to learn the sequence of feature vectors while the attention module focuses on specific Regions-of-Interest (ROIs) that are relevant to the class label of chromosomes. The Res-CRANN has demonstrated higher classification accuracy compared to existing state-of-the-art methods.

Career Highlights

Swati Jindal is currently employed at Tata Consultancy Services Limited, where she continues to work on innovative projects. Her expertise in the field of technology and her commitment to research have positioned her as a valuable asset to her organization.

Collaborations

Swati collaborates with talented individuals such as Monika Sharma and Lovekesh Vig, who contribute to her projects and research endeavors.

Conclusion

Swati Jindal's contributions to chromosome classification technology through her innovative patent exemplify her commitment to advancing scientific research. Her work not only enhances the accuracy of chromosome classification but also showcases the potential of technology in the field of genetics.