Prague, Czechia

Marek Krcál

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: Marek Krcál. Retrieved from https://idiyas.com/inventor/marek-krcál

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: Marek Krcál: Innovator in Malware Classification

Introduction

Marek Krcál is a notable inventor based in Prague, Czech Republic. He has made significant contributions to the field of cybersecurity, particularly in the classification of malware. His innovative approach utilizes advanced neural network architectures to enhance the detection of malicious software.

Latest Patents

Marek Krcál holds a patent for "Malware classification of executable files by convolutional networks." This patent describes a convolutional deep neural network architecture capable of detecting malicious executable files by analyzing 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, Marek has worked with prominent companies in the technology sector. He has been associated with Avast Software, a leading cybersecurity firm, 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

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

Conclusion

Marek Krcál's contributions to malware classification through convolutional networks represent a significant step forward in cybersecurity. His innovative work continues to influence the industry and enhance the protection against 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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