Pleasanton, CA, United States of America

Rishabh Anup Nair


Average Co-Inventor Count = 8.0

ph-index = 1


Company Filing History:


Years Active: 2024

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Rishabh Anup Nair: Innovator in Electric Vehicle Charging Optimization

Introduction

Rishabh Anup Nair is a notable inventor based in Pleasanton, CA (US). He has made significant contributions to the field of electric vehicle technology, particularly in optimizing charging systems. His innovative approach utilizes predictive analytics and machine learning to enhance the efficiency of electric vehicle charging.

Latest Patents

Rishabh holds 1 patent for his invention titled "Electric vehicle charging optimization based on predictive analytics utilizing machine learning." This method focuses on managing charging resources for plug-in electric vehicles (PEVs). The system includes a central recording center with a tracking database that initiates charging sessions based on the detection of a PEV being plugged into a charging station. The charging session is associated with a user and a PEV profile, ensuring that the vehicle is charged according to specific information. The system monitors and stores charging session data, and a machine learning model is generated from collective charging data to predict the charge completion time for the vehicle.

Career Highlights

Rishabh is currently employed at International Business Machines Corporation (IBM), where he continues to develop innovative solutions in technology. His work focuses on enhancing the efficiency of electric vehicle charging systems, which is crucial for the growing market of electric vehicles.

Collaborations

Rishabh collaborates with talented professionals in his field, including Ronald Jason Barber and Chad Eric DeLuca. Their combined expertise contributes to the advancement of electric vehicle technologies and optimization methods.

Conclusion

Rishabh Anup Nair is a pioneering inventor whose work in electric vehicle charging optimization showcases the potential of machine learning and predictive analytics. His contributions are vital to the evolution of sustainable transportation solutions.

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