San Jose, CA, United States of America

Aditya Mandal

USPTO Granted Patents = 4 

Average Co-Inventor Count = 4.0

ph-index = 2

Forward Citations = 18(Granted Patents)


Company Filing History:


Years Active: 2020-2022

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4 patents (USPTO):Explore Patents

Title: Innovations by Aditya Mandal in Machine Learning Applications

Introduction

Aditya Mandal is an accomplished inventor based in San Jose, California. He has made significant contributions to the field of machine learning, particularly in the automotive industry. With a total of four patents to his name, Mandal's work focuses on enhancing the performance and reliability of internal combustion engines.

Latest Patents

Mandal's latest patents include innovative systems and methods for detecting faults in cylinder intake and exhaust valves during engine operation. One of his notable inventions utilizes machine learning to identify when these valves do not open or close as intended, generating alerts for such faults. Another significant patent addresses cylinder misfire detection in vehicles with dynamic firing level modulation controlled engines. This invention differentiates between cylinder misfires and intentional skips by analyzing exhaust manifold pressure. Additionally, it employs a neural network to predict expected pressure levels, allowing for accurate misfire predictions.

Career Highlights

Aditya Mandal is currently employed at Tula Technology, Inc., where he continues to develop cutting-edge technologies that improve engine efficiency and performance. His expertise in machine learning has positioned him as a key player in the advancement of automotive technologies.

Collaborations

Mandal collaborates with talented colleagues such as Shikui Kevin Chen and Li-Chun Chien, contributing to a dynamic team focused on innovation and excellence in engineering.

Conclusion

Aditya Mandal's work exemplifies the intersection of machine learning and automotive engineering. His patents reflect a commitment to improving engine performance and reliability through innovative technology.

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