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For the Inventor, By the Inventor

Toronto, Canada

Sivabalan Manivasagam

USPTO Granted Patents = 16 

Average Co-Inventor Count = 5.7

ph-index = 3

Forward Citations = 19(Granted Patents)


Company Filing History:

goldMedal11 out of 472 
 
Uatc, LLC
 patents
silverMedal5 out of 275 
 
Aurora Operations, Inc.
 patents

Years Active: 2022-2025

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16 patents (USPTO):Explore Patents
1. 12223734 - Systems and methods for training machine-learned models with deviating intermediate representations (2025-02-11),
2. 12222832 - Systems and methods for generating synthetic sensor data via machine learning (2025-02-11),
3. 12214801 - Generating autonomous vehicle testing data through perturbations and adversarial loss functions (2025-02-04),
4. 12141995 - Systems and methods for simulating dynamic objects based on real world data (2024-11-12),
5. 12106435 - Systems and methods for generating synthetic light detection and ranging data via machine learning (2024-10-01),
6. 11989847 - Photorealistic image simulation with geometry-aware composition (2024-05-21),
7. 11797407 - Systems and methods for generating synthetic sensor data via machine learning (2023-10-24),
8. 11760386 - Systems and methods for vehicle-to-vehicle communications for improved autonomous vehicle operations (2023-09-19),
9. 11760385 - Systems and methods for vehicle-to-vehicle communications for improved autonomous vehicle operations (2023-09-19),
10. 11734885 - Systems and methods for generating synthetic light detection and ranging data via machine learning (2023-08-22),
11. 11686848 - Systems and methods for training object detection models using adversarial examples (2023-06-27),
12. 11685403 - Systems and methods for vehicle-to-vehicle communications for improved autonomous vehicle operations (2023-06-27),
13. 11580851 - Systems and methods for simulating traffic scenes (2023-02-14),
14. 11551429 - Photorealistic image simulation with geometry-aware composition (2023-01-10),
15. 11544167 - Systems and methods for generating synthetic sensor data via machine learning (2023-01-03),

Title: The Innovative Mind of Sivabalan Manivasagam

Introduction

Sivabalan Manivasagam is a prominent inventor based in Toronto, Canada. He has made significant contributions to the field of technology, particularly in machine learning and sensor data generation. With a total of 16 patents to his name, his work continues to influence advancements in various industries.

Latest Patents

Among his latest patents are "Systems and methods for training machine-learned models with deviating intermediate representations" and "Systems and methods for generating synthetic sensor data via machine learning." The first patent addresses how an adverse system can obtain sensor data to disrupt a machine-learned model associated with a target system. This innovative approach allows for the training of models to detect modified representations, enhancing their robustness. The second patent focuses on combining physics-based systems with machine learning to generate synthetic LiDAR data that accurately mimics real-world sensor systems. This method utilizes deep neural networks to simulate both the geometry and intensity of LiDAR data, providing a more realistic representation for various applications.

Career Highlights

Sivabalan has worked with notable companies such as UATC, LLC and Aurora Operations, Inc. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking projects in the field of technology.

Collaborations

Throughout his career, Sivabalan has collaborated with esteemed colleagues, including Raquel Urtasun and Shenlong Wang. These partnerships have fostered an environment of innovation and creativity, leading to the development of advanced technologies.

Conclusion

Sivabalan Manivasagam's contributions to the field of technology through his patents and collaborations highlight his innovative spirit and dedication to advancing machine learning and sensor technologies. His work continues to pave the way for future advancements in these critical areas.

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