Wojciech Czarnecki

This inventor holds 13 USPTO granted patents and 6 published patent applications and 8 EPO patents. Top assignees: Deepmind Technologies Limited, Gdm Holding LLC. Active years: 2020-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Wojciech Czarnecki. Retrieved from https://idiyas.com/inventor/wojciech-czarnecki

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

USPTO Granted Patents = 13 (Patent Applications = 6)

% Patents Active = 100.0

EPO Patents = 8 (Patent Applications = 11)

Average Co-Inventor Count = 4.3

ph-index = 3

Forward Citations = 42(Granted Patents)

Company Filing History:

12 out of 313

Deepmind Technologies Limited

Years Active: 2020-2026

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13 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12743627 - Reinforcement learning with auxiliary tasks (2026-09-22),

2. 12314856 - Population based training of neural networks (2025-05-27),

3. 12020164 - Neural networks for scalable continual learning in domains with sequentially learned tasks (2024-06-25),

4. 11983634 - Multi-task neural network systems with task-specific policies and a shared policy (2024-05-14),

5. 11941527 - Population based training of neural networks (2024-03-26),

6. 11842281 - Reinforcement learning with auxiliary tasks (2023-12-12),

7. 11842261 - Deep reinforcement learning with fast updating recurrent neural networks and slow updating recurrent neural networks (2023-12-12),

8. 11715009 - Training neural networks using synthetic gradients (2023-08-01),

9. 11604985 - Population based training of neural networks (2023-03-14),

10. 11132609 - Multi-task neural network systems with task-specific policies and a shared policy (2021-09-28),

11. 11113605 - Reinforcement learning using agent curricula (2021-09-07),

12. 10956820 - Reinforcement learning with auxiliary tasks (2021-03-23),

13. 10872293 - Deep reinforcement learning with fast updating recurrent neural networks and slow updating recurrent neural networks (2020-12-22),

Title: Wojciech Czarnecki: Innovator in Neural Network Technologies

Introduction

Wojciech Czarnecki is a prominent inventor based in London, GB, known for his significant contributions to the field of neural networks. With a total of 12 patents to his name, he has been at the forefront of developing innovative methods and systems that enhance machine learning capabilities.

Latest Patents

Czarnecki's latest patents include groundbreaking work on "Population based training of neural networks." This patent outlines methods, systems, and apparatus for training neural networks using an iterative process that optimizes network parameters and hyperparameters. Another notable patent is focused on "Neural networks for scalable continual learning in domains with sequentially learned tasks." This invention addresses the challenges of training neural networks on new tasks while retaining knowledge from previous tasks, showcasing his commitment to advancing machine learning technologies.

Career Highlights

Czarnecki is currently employed at DeepMind Technologies Limited, a leading company in artificial intelligence research. His work at DeepMind has positioned him as a key player in the development of advanced neural network methodologies. His innovative approaches have not only contributed to the company's success but have also influenced the broader field of artificial intelligence.

Collaborations

Throughout his career, Czarnecki has collaborated with notable colleagues, including Maxwell Elliot Jaderberg and Razvan Pascanu. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Wojciech Czarnecki's contributions to neural network technologies exemplify his innovative spirit and dedication to advancing the field of artificial intelligence. His patents and work at DeepMind continue to shape the future of machine learning, making him a significant figure in the industry.

Profile summary based on public USPTO records.