Velehrad, Czechia

Ondrej Svec

This inventor holds 1 USPTO granted patent. Top assignees: Avast Software S.r.o., Ustav Informatiky Av Cr, V.v.i.. Active years: 2022.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ondrej Svec. Retrieved from https://idiyas.com/inventor/ondrej-svec

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


% Patents Active = 100.0

Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2022

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1 patent (USPTO):Explore Patents

Title: Ondrej Svec: Innovator in Malware Classification

Introduction

Ondrej Svec is a notable inventor based in Velehrad, Czech Republic. He has made significant contributions to the field of cybersecurity, particularly in the area of malware detection. His innovative approach utilizes advanced neural network architectures to enhance the security of executable files.

Latest Patents

Ondrej Svec holds a patent for "Malware classification of executable files by convolutional networks." This patent describes a convolutional deep neural network architecture that can detect malicious executable files by reading the raw sequence of bytes. This method eliminates the need for domain-specific feature extraction or preprocessing, making it a groundbreaking advancement in malware detection.

Career Highlights

Throughout his career, Ondrej has worked with prominent companies in the tech industry. He has been associated with Avast Software, a leading cybersecurity company, and the Institute of Computer Science of the Czech Academy of Sciences. His work in these organizations has allowed him to develop and refine his innovative ideas in malware classification.

Collaborations

Ondrej has collaborated with talented individuals in his field, including Marek Krcál and Martin Bálek. These collaborations have contributed to the advancement of his research and the successful implementation of his patented technology.

Conclusion

Ondrej Svec's contributions to malware classification through his innovative patent demonstrate his expertise and commitment to enhancing cybersecurity. His work continues to influence the field and offers promising solutions for detecting malicious software.

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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