Company Filing History:
Years Active: 2023
Title: Subhodeep Moitra: Innovator in Sparse Graph Neural Networks
Introduction
Subhodeep Moitra is a prominent inventor based in St-Jerome, Canada. He has made significant contributions to the field of computer science, particularly in optimizing sparse graph neural networks for dense hardware. His innovative approach has garnered attention in the tech community, showcasing his expertise and creativity.
Latest Patents
Subhodeep Moitra holds 1 patent for his work titled "Optimizing sparse graph neural networks for dense hardware." This patent describes a computer-implemented method for computing node embeddings of a sparse graph that serves as input for a sparse graph neural network. The method involves several steps, including receiving an adjacency matrix that represents edges of the sparse graph and a weight matrix that indicates the influence of neighboring nodes. The process also includes initializing node embeddings, transforming the adjacency matrix, and generating a message propagation matrix to update the node embeddings using an encoder neural network.
Career Highlights
Subhodeep Moitra is currently employed at Google Inc., where he continues to push the boundaries of technology through his research and development efforts. His work is instrumental in advancing the capabilities of neural networks, particularly in handling sparse data efficiently.
Collaborations
Some of his notable coworkers include Daniel S. Tarlow and Matej Balog, who have collaborated with him on various projects, contributing to the innovative environment at Google Inc.
Conclusion
Subhodeep Moitra's contributions to the field of sparse graph neural networks exemplify the impact of innovative thinking in technology. His work not only enhances computational methods but also paves the way for future advancements in artificial intelligence.