The Hague, Netherlands

Gijs Michiel Van Essen

This inventor holds 1 USPTO granted patent. Top assignees: International Business Machines Corporation, Shell Oil Comapny. Active years: 2018.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Gijs Michiel Van Essen. Retrieved from https://idiyas.com/inventor/gijs-michiel-van-essen

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


Average Co-Inventor Count = 6.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2018

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1 patent (USPTO):Explore Patents

Title: Gijs Michiel Van Essen: Innovator in Predictive Modeling

Introduction

Gijs Michiel Van Essen is a notable inventor based in The Hague, Netherlands. He has made significant contributions to the field of predictive modeling, particularly through his innovative patent.

Latest Patents

Gijs Michiel Van Essen holds a patent titled "Reduced space clustering representatives and its application to long term prediction." This patent presents a technique for clustering model prior realizations into flow-equivalent sets. By identifying far fewer representatives from each cluster, the method ensures reliable predictions of future production across a range of scenarios. Only those representatives that indicate unique forecasts undergo the computationally intensive process of history matching.

Career Highlights

Throughout his career, Gijs has worked with prominent companies, including IBM and Shell Oil Company. His experience in these organizations has allowed him to apply his innovative ideas in practical settings, contributing to advancements in predictive analytics.

Collaborations

Gijs has collaborated with notable professionals in his field, including Andrew R Conn and Lior Horesh. These partnerships have further enriched his work and expanded the impact of his inventions.

Conclusion

Gijs Michiel Van Essen is a distinguished inventor whose work in predictive modeling has led to valuable innovations. His contributions continue to influence the field and demonstrate the importance of effective forecasting techniques.

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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