Janahan Mathuran Ramanan

Title: Innovations of Janahan Mathuran Ramanan

Introduction

Janahan Mathuran Ramanan is a notable inventor based in Toronto, Canada. He has made significant contributions to the field of machine learning and predictive analytics. With a total of 3 patents, Ramanan is recognized for his innovative approaches to technology and data processing.

Latest Patents

One of his latest patents is the "K-LSTM architecture for purchase prediction." This system receives transaction data over time and creates structured data based on the received transaction data. Purchase transactions associated with a purchase category are identified in the structured data and labeled. A recurrent neural network, specifically a long short-term memory (LSTM) network, is trained to build a model that predicts the likelihood of a purchase transaction.

Another significant patent is the "System and method for time-dependent machine learning architecture." This technical solution focuses on the decomposition of time as an input for machine learning. It describes various mechanisms and data structures that improve machine learning outcomes, including accuracy and convergence speed. A vector representation of continuous time is utilized to enhance the tracking of periodic behavior in features, thereby modifying time inputs in machine learning architectures.

Career Highlights

Janahan Mathuran Ramanan currently works at the Royal Bank of Canada, where he applies his expertise in machine learning and data analytics. His work has contributed to advancements in predictive modeling and data processing techniques.

Collaborations

Ramanan collaborates with talented individuals such as Jaspreet Sahota and Yuanqiao Wu. Their combined efforts in research and development have led to innovative solutions in their respective fields.

Conclusion

Janahan Mathuran Ramanan is a distinguished inventor whose work in machine learning and predictive analytics has garnered attention. His patents reflect a commitment to advancing technology and improving data processing methodologies.