Bengaluru, India

Srinivas Sridharan

This inventor holds 25 USPTO granted patents and 9 published patent applications and 4 EPO patents, primarily in Distributed Machine Learning. Top assignee: Intel Corporation. Active years: 2020-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Srinivas Sridharan. Retrieved from https://idiyas.com/inventor/srinivas-sridharan

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

Calculating rank
USPTO Granted Patents = 25 

% Patents Active = 96.0

 

Average Co-Inventor Count = 4.1

ph-index = 5

Forward Citations = 76(Granted Patents)


Company Filing History:


Years Active: 2020-2026

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Areas of Expertise:
Distributed Machine Learning
Machine Learning Accelerator
Dynamic Precision Management
Communication Optimizations
Data Parallelism
Fine-Grain Compute Execution
Scalable Frameworks
Hardware Acceleration
Abstraction Layers
Class of Service Management
Training Optimization
Integer Deep Learning
25 patents (USPTO):Explore Patents

Title: Innovator Spotlight: Srinivas Sridharan

Introduction

Srinivas Sridharan, based in Bengaluru, India, is a prominent inventor with an impressive portfolio of 19 patents. His work primarily revolves around advancements in machine learning and distributed computing systems, showcasing his vital contributions to the field of technology.

Latest Patents

Srinivas's latest patents demonstrate his innovative approach to enhancing deep learning systems. One notable patent is titled "Data parallelism and halo exchange for distributed machine learning." This invention presents a method for transmitting data across multiple compute nodes in a distributed system, enabling efficient training of convolutional neural networks. The method focuses on multi-dimensional partitioning of feature map data and parallel convolution operations, optimizing the training process to incorporate data dependencies effectively.

Another significant patent is "Fine-grain compute communication execution for deep learning frameworks via hardware accelerated point-to-point primitives." This system is designed to configure distributed training of neural networks by facilitating the transmission of data associated with trainable parameters. It utilizes a library stored in memory, enabling a general-purpose processor and graphics processor to work in unison, thereby interleaving compute operations with data transmission efficiently.

Career Highlights

Srinivas is currently employed at Intel Corporation, where he drives innovations in computing and machine learning technologies. His role at this prestigious company allows him to collaborate with some of the best minds in the industry and contribute to transformative projects that push the boundaries of what is possible with technology.

Collaborations

Throughout his career, Srinivas has collaborated with significant talents in the field, including coworkers such as Dipankar Das and Dheevatsa Mudigere. These collaborations have been crucial in fostering an environment of shared knowledge and innovation, resulting in groundbreaking advancements in machine learning frameworks.

Conclusion

Srinivas Sridharan's contributions to the realm of technology, specifically in the areas of distributed computing and machine learning, are noteworthy. His array of patents not only highlights his inventive spirit but also emphasizes the importance of collaborative innovation in achieving significant technological advancements. As technology continues to evolve, pioneers like Srinivas will undoubtedly play a crucial role in shaping the future of machine learning and computational efficiency.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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