Vienna, Austria

Roman Rudenko

USPTO Granted Patents = 1 

Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations by Roman Rudenko in Generative AI Software Fixing

Introduction

Roman Rudenko is an innovative inventor based in Vienna, Austria. He has made significant contributions to the field of software development through his groundbreaking patent. His work focuses on utilizing generative artificial intelligence to enhance code fixing processes, showcasing the potential of AI in improving software reliability.

Latest Patents

Rudenko holds a patent for a generative artificial intelligence-driven code fixing pipeline. This innovative system employs a transformer-based large language model (LLM) to identify and patch flawed program code. The process involves fine-tuning a pre-trained LLM to generate modified versions of code fragments, which are then integrated into a comprehensive pipeline that includes a cybersecurity scanner and a prompt generator. This approach not only identifies flaws in program code but also provides alternative patching solutions.

Career Highlights

Roman Rudenko is currently employed at Veracode, Inc., where he continues to develop and refine his innovative ideas. His expertise in generative AI and software development has positioned him as a key player in the tech industry. With a focus on enhancing cybersecurity through AI-driven solutions, Rudenko is paving the way for more secure software applications.

Collaborations

Rudenko collaborates with Anna Bacher, a fellow innovator in the field. Together, they work on advancing the capabilities of AI in software development, contributing to the evolution of technology in their respective areas of expertise.

Conclusion

Roman Rudenko's contributions to generative artificial intelligence and software fixing represent a significant advancement in the tech industry. His innovative approach not only addresses existing challenges in software reliability but also sets the stage for future developments in AI-driven solutions.

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