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For the Inventor, By the Inventor

Cedar Park, TX, United States of America

Vladimir P Zolotov

This inventor holds 83 USPTO granted patents and 3 published patent applications and 1 EPO patent, primarily in Integrated Circuit Design (CPC class G06F17-5081). Top assignees: International Business Machines Corporation, Freescale Semiconductor,inc., Globalfoundries Inc.. Active years: 2004-2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Vladimir P Zolotov. Retrieved from https://idiyas.com/inventor/vladimir-p-zolotov

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

Calculating rank
USPTO Granted Patents = 83 

% Patents Active = 34.9


Average Co-Inventor Count = 4.6

ph-index = 12

Forward Citations = 639(Granted Patents)

Forward Citations (Not Self Cited) = 564(Dec 10, 2025)


Inventors with similar research interests:

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Location History:

  • Austin, TX (US) (2004)
  • Cedar Park, TX (US) (2004 - 2006)
  • Putnum Valley, NY (US) (2013)
  • Yorktown Heights, NY (US) (2014)
  • Putman Valley, NY (US) (2014)
  • Putnam Valley, NY (US) (2007 - 2024)

Company Filing History:

goldMedal74 out of 166,425 
 
International Business Machines Corporation
 patents
silverMedal4 out of 5,491 
 
Freescale Semiconductor,inc.
 patents
bronzeMedal4 out of 5,671 
 
Globalfoundries Inc.
 patents
4. 1 out of 59 
 
Globalfoundries U.S. 2 LLC
 patents

Years Active: 2004-2024

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Areas of Expertise:
Deep Learning
Neural Networks
Statistical Timing Analysis
Integrated Circuits
Noise Analysis
Dynamic Memory Management
Path Traversal
Power Control
Multi-Patterning
Coupling Aware
Parasitic Extraction
Timing Optimization
83 patents (USPTO):Explore Patents
1. 11915147 - Large model support in deep learning (2024-02-27),
2. 11526759 - Large model support in deep learning (2022-12-13),
3. 11521062 - Neural network training using a data flow graph and dynamic memory management (2022-12-06),
4. 11120193 - Analysis of coupled noise for integrated circuit design (2021-09-14),
5. 11113313 - Fast path traversal in a relational database-based graph structure (2021-09-07),
6. 10970448 - Partial parameters and projection thereof included within statistical timing analysis (2021-04-06),
7. 10606970 - Selection of corners and/or margins using statistical static timing analysis of an integrated circuit (2020-03-31),
8. 10489540 - Integrating manufacturing feedback into integrated circuit structure design (2019-11-26),
9. 10460068 - Coupling aware wire capacitance adjust at global routing (2019-10-29),
10. 10394999 - Analysis of coupled noise for integrated circuit design (2019-08-27),
11. 10394982 - Partial parameters and projection thereof included within statistical timing analysis (2019-08-27),
12. 10380289 - Multi-sided variations for creating integrated circuits (2019-08-13),
13. 10380286 - Multi-sided variations for creating integrated circuits (2019-08-13),
14. 10366197 - Coupling aware wire capacitance adjust at global routing (2019-07-30),
15. 10346569 - Multi-sided variations for creating integrated circuits (2019-07-09),

Title: Innovations of Vladimir P. Zolotov: A Deep Learning Pioneer

Introduction

Vladimir P. Zolotov is a notable inventor based in Cedar Park, Texas, who has made significant contributions to the field of deep learning with a remarkable portfolio of 83 patents. His innovative work focuses on techniques that enhance the capabilities of deep neural networks, pushing the boundaries of artificial intelligence and machine learning.

Latest Patents

Among his latest inventions is a groundbreaking patent titled "Large Model Support in Deep Learning." This innovation provides techniques that facilitate model support in deep learning. The system described includes a graphics processing unit (GPU) and a central processing unit (CPU) memory, where the GPU processes data to train the deep neural network. The CPU memory stores a portion of this data, and during a forward pass process, the GPU shares input data for various layers of the neural network with the CPU memory. This innovative approach enhances the training efficiency of deep learning models, showcasing Zolotov's forward-thinking contributions to the field.

Career Highlights

Vladimir's career has seen him work with prominent companies such as IBM and Freescale Semiconductor. His experiences in these well-respected organizations have allowed him to influence the development of advanced technologies in the semiconductor and computing industries. With his extensive background and expertise, Zolotov has become a key player in shaping cutting-edge solutions in deep learning.

Collaborations

Throughout his career, Zolotov has collaborated with esteemed professionals like Chandramouli Visweswariah and Natesan Venkateswaran. These collaborations have fostered an environment of creativity and innovation, resulting in advancements that benefit the broader tech community.

Conclusion

Vladimir P. Zolotov stands out as a pioneer in the realm of deep learning, with a robust portfolio of patents reflecting his innovative spirit. His work on large model support systems has potential far-reaching implications for AI and machine learning, paving the way for more sophisticated and efficient technologies. As he continues to build on his legacy, Zolotov's contributions will undoubtedly inspire future generations of inventors and researchers in the field.

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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