Vilnius, Lithuania

Mantas Briliauskas

This inventor holds 50 USPTO granted patents and 9 published patent applications, primarily in Malware Detection. Top assignees: Uab 360 It, Oxylabs, Uab, Metacluster Lt, Uab. Active years: 2022-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mantas Briliauskas. Retrieved from https://idiyas.com/inventor/mantas-briliauskas

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

USPTO Granted Patents = 50 

% Patents Active = 98.0

Average Co-Inventor Count = 1.9

ph-index = 3

Forward Citations = 43(Granted Patents)


Company Filing History:


Years Active: 2022-2026

Loading Chart...
Areas of Expertise:
Malware Detection
Machine Learning
Data Optimization
Dynamic Analysis
Binary Segmentation
Adversarial Learning
URL Filtering
Federated Learning
Malware Classification
Behavior Detection
Content Analysis
Data Preprocessing
50 patents (USPTO):Explore Patents

Title: Mantas Briliauskas: A Serial Innovator Reinventing Cybersecurity

Introduction:

Mantas Briliauskas, a renowned inventor based in Vilnius, LT, has made remarkable contributions in the field of cybersecurity. With an impressive portfolio of 21 patents to his name, Briliauskas has proven himself as a leading figure in the dynamic and ever-evolving domain of combating harmful content online. This article aims to shed light on some of his latest patents, career highlights, notable collaborations, and his overall impact on the field of innovation.

Latest Patents:

Briliauskas's recent patents highlight his expertise in developing cutting-edge methods to detect and mitigate harmful content online. One of his recent inventions involves dynamic analysis for detecting harmful content. This method empowers user devices by configuring them to receive harmful patterns and clean patterns, allowing for the identification of malicious content. Another notable invention by Briliauskas is an optimized analysis for detecting harmful content, which focuses on determining patterns associated with traits in given data and assessing whether it includes malicious content. These patents showcase Briliauskas's commitment to improving online security and protecting users from harmful digital threats.

Career Highlights:

Throughout his career, Briliauskas has worked with prominent companies like UAB 360 IT and Metacluster LT. While the specifics of his contributions to these organizations remain undisclosed, his collaborations with industry leaders testify to his expertise and recognition within the cybersecurity community. Briliauskas's commitment to advancing the field of online security has solidified his reputation as a pioneering innovator in the domain.

Collaborations:

During his professional journey, Briliauskas has had the opportunity to collaborate with talented individuals who share his passion for cybersecurity. Notable coworkers include Dainius Razinskas and Martynas Juravicius. Their collaborative efforts have likely contributed to the successful development and implementation of Briliauskas's innovative solutions. While further details about these collaborations are not available, it is evident that Briliauskas values teamwork and thrives in collective problem-solving environments.

Conclusion:

Mantas Briliauskas has emerged as a formidable force in the field of cybersecurity with his numerous patents, career achievements, and collaborations with industry peers. His groundbreaking inventions in dynamic and optimized analysis for detecting harmful content demonstrate his dedication to safeguarding users from digital threats. As the digital landscape evolves, experts like Briliauskas play a crucial role in shaping the future of secure and trustworthy online environments. His continuous efforts undoubtedly make a significant impact in the world of innovations and patents related to cybersecurity.

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]
Loading…