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For the Inventor, By the Inventor

Kansas City, MO, United States of America

Babak Poorebrahim Gilkalaye

This inventor holds 21 USPTO granted patents and 8 published patent applications, primarily in Privacy-Preserving AI. Top assignees: Tripleblind, Inc., Tripleblind Holding Company, Triplelind Holdings, Inc.. Active years: 2021-2024.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Babak Poorebrahim Gilkalaye. Retrieved from https://idiyas.com/inventor/babak-poorebrahim-gilkalaye

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

Calculating rank
USPTO Granted Patents = 21 

% Patents Active = 100.0

Average Co-Inventor Count = 3.6

ph-index = 2

Forward Citations = 19(Granted Patents)


Location History:

  • Kansas City, CA (2022 - 2023)
  • Kansas City, MO (US) (2021 - 2024)

Company Filing History:

goldMedal18 out of 20 
 
Tripleblind, Inc.
 patents
silverMedal2 out of 2 
 
Tripleblind Holding Company
 patents
bronzeMedal1 out of 1 
 
Triplelind Holdings, Inc.
 patent

Years Active: 2021-2024

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Areas of Expertise:
Federated Learning
Secure Multi-Party Computation
Neural Networks
Data Encryption
Privacy Preservation
Marketplace Algorithms
Decentralized Data
Artificial Intelligence
Quantum-Proof Key Exchange
Modified Loss Functions
Error Systems
Private Data Computations
21 patents (USPTO):Explore Patents
1. 12088565 - Systems and methods for privacy preserving training and inference of decentralized recommendation systems from decentralized data (2024-09-10),
2. 12026219 - Systems and methods for efficient computations on split data and split algorithms (2024-07-02),
3. 12019704 - Systems and methods for encrypting data and algorithms (2024-06-25),
4. 12019703 - Systems and methods for providing a marketplace where data and algorithms can be chosen and interact via encryption (2024-06-25),
5. 11991156 - Systems and methods for secure averaging of models for federated learning and blind learning using secure multi-party computation (2024-05-21),
6. 11973743 - Systems and methods for providing a systemic error in artificial intelligence algorithms (2024-04-30),
7. 11895220 - Systems and methods for dividing filters in neural networks for private data computations (2024-02-06),
8. 11843587 - Systems and methods for tree-based model inference using multi-party computation (2023-12-12),
9. 11843586 - Systems and methods for providing a modified loss function in federated-split learning (2023-12-12),
10. 11792646 - Systems and methods for providing a multi-party computation system for neural networks (2023-10-17),
11. 11625377 - Systems and methods for enabling two parties to find an intersection between private data sets without learning anything other than the intersection of the datasets (2023-04-11),
12. 11599671 - Systems and methods for finding a value in a combined list of private values (2023-03-07),
13. 11582203 - Systems and methods for encrypting data and algorithms (2023-02-14),
14. 11539679 - Systems and methods for providing a quantum-proof key exchange (2022-12-27),
15. 11531782 - Systems and methods for finding a value in a combined list of private values (2022-12-20),

Title: **Babak Poorebrahim Gilkalaye: Innovator in Data Privacy**

Introduction

Babak Poorebrahim Gilkalaye is a prominent inventor based in Kansas City, MO, with an impressive portfolio of 12 patents to his name. His inventions focus primarily on enhancing data privacy and efficiency in computational processes.

Latest Patents

Among his recent contributions, Babak holds patents for innovative systems and methods aimed at efficient computations on split data and split algorithms. The disclosed concepts provide a privacy-oriented approach for data processed by algorithms, ensuring that sensitive information remains secure during operations. Specifically, one method involves receiving two subsets of algorithms and corresponding data, generating shares of mathematical sets, and subsequently transmitting these shares between entities to produce combined output subsets.

Another significant patent relates to systems and methods for encrypting data and algorithms. This invention describes a comprehensive framework that allows for privacy in both the data and the algorithm involved. By splitting the algorithm and data into distinct subsets, the system can ensure that each segment is processed by separate entities, culminating in a combined result while maintaining the integrity and confidentiality of the information.

Career Highlights

Babak has worked with notable companies, including TripleBlind, Inc. and TripleBlind Holding Company. In these roles, he has contributed to pioneering projects aimed at addressing crucial issues around data privacy in computing.

Collaborations

His innovative journey has seen him collaborate with esteemed colleagues such as Greg Storm and Riddhiman Das, contributing to a dynamic environment focused on advancing technology and security in data processing.

Conclusion

Babak Poorebrahim Gilkalaye continues to push the boundaries of innovation in the field of data privacy. His inventions reflect a deep understanding of the complexities surrounding data security and computational efficiency, making him a valuable asset to the tech community. As technologies evolve, his work will undoubtedly play a critical role in shaping the future of secure data handling.

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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