Chongqing, China

Mingjian Li

This inventor holds 1 USPTO granted patent. Top assignee: Ccteg Chongqing Research Institute. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Mingjian Li. Retrieved from https://idiyas.com/inventor/mingjian-li-6rvhibve

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


Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: Mingjian Li and Coal Mine Multi-Disaster Early Warning

Introduction

Mingjian Li is an inventor based in Chongqing, China, whose work addresses safety analysis and early warning in coal mines. His patent describes a method and system for combining information about multiple potential disasters to support earlier, more targeted warnings.

Latest Patents

Li is associated with 1 patent: “Multi-disaster fusion natural fission early warning method and system in coal mine.” The invention builds a model and relationship network among early-warning entities, updating their connections according to defined rules. It uses an LSTM artificial neural network to predict monitoring trends and applies natural-fission analysis rules to assess how a detected anomaly in one disaster index may relate to other hazards. A depth-first traversal algorithm helps identify relevant indexes for targeted forecasting. By establishing predictive relationships among early-warning indexes through correlation analysis, the system supports multidimensional analysis and advanced trend prediction.

Career Highlights

Li is associated with CCTEG Chongqing Research Institute. His patent focuses on integrating disaster indicators and forecasting methods to improve coal mine safety monitoring.

Collaborations

The provided information lists Haitao Sun and Zhigang Zhang as Li’s coworkers. Their specific roles in the patent or related research are not specified.

Conclusion

Mingjian Li’s patented work combines trend prediction, anomaly detection, and relationships among disaster indicators to advance multi-hazard early warning for coal mines.

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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