Shoubhik Debnath

Title: Shoubhik Debnath: Innovator in Scene Graph Generation

Introduction

Shoubhik Debnath is a prominent inventor based in Sunnyvale, CA. He has made significant contributions to the field of scene graph generation, particularly in the context of unlabeled data. With a total of 2 patents, his work is paving the way for advancements in transfer learning and machine learning techniques.

Latest Patents

Debnath's latest patents focus on innovative approaches for training and utilizing scene graph generators. His techniques aim to decompose domain gaps into individual types of discrepancies, which may relate to appearance, label, and prediction discrepancies. By aligning the corresponding latent and output distributions using gradient reversal layers (GRLs), these discrepancies can be reduced. Furthermore, he addresses label discrepancies through self-pseudo-statistics collected from target data. His methods utilize pseudo statistic-based self-learning and adversarial techniques, allowing for effective management of discrepancies without the need for costly supervision from real-world datasets.

Career Highlights

Shoubhik Debnath is currently employed at Nvidia Corporation, a leading company in the field of graphics processing and artificial intelligence. His work at Nvidia has allowed him to explore and implement cutting-edge technologies in machine learning and computer vision.

Collaborations

Some of his notable coworkers include Aayush Prakash and Jean-Francois Lafleche, who contribute to the innovative environment at Nvidia Corporation.

Conclusion

Shoubhik Debnath's contributions to scene graph generation and his innovative approaches to machine learning are noteworthy. His work continues to influence the field and drive advancements in technology.