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For the Inventor, By the Inventor

Toronto, Canada

Sergio Casas

USPTO Granted Patents = 19 

Average Co-Inventor Count = 4.4

ph-index = 2

Forward Citations = 40(Granted Patents)


Company Filing History:

goldMedal12 out of 472 
 
Uatc, LLC
 patents
silverMedal7 out of 272 
 
Aurora Operations, Inc.
 patents

Years Active: 2022-2025

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19 patents (USPTO):Explore Patents
1. 12430534 - Systems and methods for generating motion forecast data for actors with respect to an autonomous vehicle and training a machine learned model for the same (2025-09-30),
2. 12387475 - Systems and methods for latent distribution modeling for scene-consistent motion forecasting (2025-08-12),
3. 12350835 - Systems and methods for sensor data packet processing and spatial memory updating for robotic platforms (2025-07-08),
4. 12344279 - Systems and methods for motion forecasting and planning for autonomous vehicles (2025-07-01),
5. 12319319 - Multi-task machine-learned models for object intention determination in autonomous driving (2025-06-03),
6. 12214801 - Generating autonomous vehicle testing data through perturbations and adversarial loss functions (2025-02-04),
7. 12205004 - Systems and methods for training probabilistic object motion prediction models using non-differentiable prior knowledge (2025-01-21),
8. 12037027 - Systems and methods for generating synthetic motion predictions (2024-07-16),
9. 12037025 - Systems and methods for motion forecasting and planning for autonomous vehicles (2024-07-16),
10. 12023812 - Systems and methods for sensor data packet processing and spatial memory updating for robotic platforms (2024-07-02),
11. 12013457 - Systems and methods for integrating radar data for improved object detection in autonomous vehicles (2024-06-18),
12. 12008454 - Systems and methods for generating motion forecast data for actors with respect to an autonomous vehicle and training a machine learned model for the same (2024-06-11),
13. 11842530 - Systems and methods for latent distribution modeling for scene-consistent motion forecasting (2023-12-12),
14. 11836585 - Systems and methods for training probabilistic object motion prediction models using non-differentiable prior knowledge (2023-12-05),
15. 11834069 - Systems and methods for selecting trajectories based on interpretable semantic representations (2023-12-05),

Title: Innovations by Inventor Sergio Casas in Autonomous Vehicle Technology

Introduction: Sergio Casas is a prominent inventor based in Toronto, CA, who has made significant contributions to the field of autonomous vehicle technology. With a remarkable portfolio of 14 patents, he is recognized for his innovative approaches to enhancing the safety and efficiency of autonomous vehicles.

Latest Patents: Sergio's latest patents include groundbreaking techniques for generating autonomous vehicle testing data through perturbations and adversarial loss functions. This invention outlines a system capable of obtaining sensor data that describes various traffic scenarios, with a focus on generating perturbed trajectories for actors in the environment. It leads to the production of simulated sensor data, which is utilized by an autonomous vehicle control system to improve the vehicle's trajectory in real-time.

Another notable patent is focused on systems and methods for training probabilistic object motion prediction models using non-differentiable prior knowledge. This technology allows autonomous vehicles to predict the future positions of various objects within their environment, utilizing non-differentiable representations of prior knowledge, such as traffic states and road geometries.

Career Highlights: Throughout his career, Sergio has held key positions at notable companies in the automotive and technology sectors, including UATC, LLC and Aurora Operations, Inc. His work has not only improved the understanding of autonomous vehicle dynamics but has also contributed to the advancement of machine learning techniques used in vehicle navigation.

Collaborations: Sergio has worked alongside esteemed individuals in the industry, such as Raquel Urtasun and Cole Christian Gulino. These collaborations have played a crucial role in enhancing the scope and impact of his inventions, combining expertise from various fields to push boundaries in autonomous technology.

Conclusion: Sergio Casas continues to be a leading figure in the innovation of autonomous vehicles. His patent contributions reflect a deep understanding of complex traffic scenarios and enhance the capabilities of vehicles to navigate safely. As the industry evolves, his work will undoubtedly serve as a foundation for future developments in autonomous driving technology.

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