Ranjitha Prasad

Title: Ranjitha Prasad: Innovator in Neural Network Learning

Introduction

Ranjitha Prasad is a notable inventor based in Gurgaon, India. He has made significant contributions to the field of artificial intelligence, particularly in the area of neural networks. His innovative work focuses on enhancing the efficiency and effectiveness of machine learning models.

Latest Patents

Ranjitha Prasad holds a patent for his invention titled "Sparsity constraints and knowledge distillation based learning of sparser and compressed neural networks." This patent describes implementations that build a Bayesian student network using knowledge acquired from a complex pre-trained teacher network. The invention employs sparsity induced by variational parameters in the student network, enhancing its learning capabilities. The student network is trained using a variational lower bound based loss function, which is constrained by hints from the teacher and the block-sparsity of weights.

Career Highlights

Ranjitha Prasad is currently employed at Tata Consultancy Services Limited, where he applies his expertise in machine learning and neural networks. His work at TCS has allowed him to collaborate with other talented professionals in the field, contributing to various innovative projects.

Collaborations

Some of Ranjitha's coworkers include Srinidhi Hegde and Ramya Hebbalaguppe. Their collaboration fosters a creative environment that encourages the development of cutting-edge technologies.

Conclusion

Ranjitha Prasad is a distinguished inventor whose work in neural network learning has the potential to transform the landscape of artificial intelligence. His contributions, particularly through his patent, demonstrate his commitment to advancing technology and improving machine learning processes.