New Brunswick, NJ, United States of America

Vladimir Gligorijevic

This inventor holds 1 USPTO granted patent. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Vladimir Gligorijevic. Retrieved from https://idiyas.com/inventor/vladimir-gligorijevic-6sa86uue

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

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Average Co-Inventor Count = 1.0


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Vladimir Gligorijevic and Generative Protein Design

Introduction

Vladimir Gligorijevic is an inventor associated with New Brunswick, New Jersey. His patent work addresses computational methods for designing protein sequences with desirable properties.

Latest Patents

The patent listed for Gligorijevic is “Generative Protein Design with Composable Energy-Based Models.” It describes a method that identifies an input protein sequence and modifies it using a computational model trained to approximate a distribution of sequences with specified properties. The model uses one or more energy-based models and corresponding energy functions to guide sequence modification and assess whether a modified sequence is likely to meet the desired criteria. When the likelihood satisfies one or more thresholds, the method generates an output sequence based on the modified input. Gligorijevic is credited with 1 patent.

Career Highlights

This patent highlights the use of energy-based modeling in protein design. By combining sequence modification with likelihood evaluation, the approach provides a computational framework for generating candidate protein sequences that meet selected design objectives.

Collaborations

The supplied information lists Andreas Loukas and Stephen Robert Ra.. among Gligorijevic’s coworkers. Their names suggest a collaborative research environment connected to computational protein design.

Conclusion

Vladimir Gligorijevic’s listed patent presents a method for using composable energy-based models to guide the generation of protein sequences with desirable properties.

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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