Bengaluru, India

Shayan Ghosh

USPTO Granted Patents = 1 

Average Co-Inventor Count = 5.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):

Title: Innovations of Shayan Ghosh in Machine Learning

Introduction

Shayan Ghosh is an innovative inventor based in Bengaluru, India. He has made significant contributions to the field of machine learning, particularly in the area of signal processing. His work focuses on developing methods and apparatuses that enhance the capabilities of machine-learning models.

Latest Patents

Shayan Ghosh holds a patent for an "Apparatus (and/or method) of training a machine-learning model to generate determinations using mismatched-channel signals." This invention involves a sophisticated apparatus designed to train machine-learning models to make determinations from mismatched channel signals. The apparatus includes a processor and memory that are communicatively connected. The memory contains instructions that configure the processor to receive a first set of signals using a first number of channels. It processes these signals to simulate a second set from a different number of channels. The invention trains a signal conversion model using both sets of signals and outputs a set of converted signals.

Career Highlights

Shayan Ghosh is currently employed at Anumana, Inc., where he continues to push the boundaries of technology in machine learning. His work is characterized by a commitment to innovation and excellence. He has successfully developed methods that improve the efficiency and accuracy of machine-learning applications.

Collaborations

Shayan collaborates with talented individuals such as Yash Gupta and Shashi Kant. Together, they work on advancing the field of machine learning and exploring new frontiers in technology.

Conclusion

Shayan Ghosh's contributions to machine learning through his innovative patent demonstrate his expertise and commitment to advancing technology. His work at Anumana, Inc. and collaborations with skilled professionals highlight his role in shaping the future of machine learning.

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