Berlin, Germany

Aravindh Mahendran

USPTO Granted Patents = 1 

Average Co-Inventor Count = 9.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Aravindh Mahendran: Innovator in Conditional Object-Centric Learning

Introduction

Aravindh Mahendran is a notable inventor based in Berlin, Germany. He has made significant contributions to the field of machine learning, particularly in the area of video processing and sequential data analysis. His innovative approach has led to the development of a unique patent that enhances the understanding of object-centric learning.

Latest Patents

Aravindh holds a patent titled "Conditional object-centric learning with slot attention for video and other sequential data." This method involves obtaining first and second feature vectors that represent the contents of two image frames from an input video. The process includes generating first slot vectors based on the first feature vectors, which represent the attributes of corresponding entities in the first image frame. Furthermore, it predicts slot vectors that illustrate the transition of these attributes to the second image frame. The method culminates in generating second slot vectors that represent the attributes of the entities in the second image frame, ultimately determining an output based on these vectors. He has 1 patent to his name.

Career Highlights

Aravindh is currently employed at Google Inc., where he continues to push the boundaries of innovation in artificial intelligence and machine learning. His work is instrumental in developing advanced algorithms that improve the efficiency and accuracy of video analysis.

Collaborations

Throughout his career, Aravindh has collaborated with talented individuals such as Thomas Kipf and Gamaleldin Elsayed. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of groundbreaking technologies.

Conclusion

Aravindh Mahendran is a pioneering inventor whose work in conditional object-centric learning is shaping the future of video processing. His contributions to the field are invaluable, and his innovative spirit continues to inspire others in the realm of technology.

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