Founder & Expertise
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Current research
NeuroEco Labs was founded by Artur Nurgaliev, an engineer and researcher specializing in artificial intelligence, environmental monitoring and oil & gas field operations.
His work focuses on the development of neural-network models for forecasting methane and associated gas emissions, as well as on the design of practical monitoring solutions that can operate in harsh climate conditions. Artur is the author and co-author of several peer-reviewed articles on environmental monitoring, emissions analytics and data-driven diagnostics of well integrity.
The project combines his industry experience with academic research, with the goal of creating scalable tools that improve environmental and industrial safety in the United States.
Founder and Principal Researcher
Artur Nurgaliev is an engineer and researcher specializing in artificial intelligence, environmental monitoring, and oil & gas infrastructure diagnostics. His work integrates machine-learning methods with industrial field measurements to improve the early detection of abnormal emission patterns and prevent environmental incidents.
Artur’s research includes the development of neural-network models for forecasting methane and associated gas emissions under harsh climatic conditions, including regions with winter temperatures down to −40°C. He is the author and co-author of peer-reviewed articles on gas-emission monitoring, climate-safety analytics, and data-driven diagnostics of well integrity.
His professional experience combines scientific research with practical field exposure to oil & gas operations, which helps bridge the gap between academic environmental research and real industrial challenges. Artur founded NeuroEco Labs to advance climate-safety technology that supports environmental protection and regulatory transparency in the United States.
Areas of expertise:
• AI-based emissions forecasting
• Climate-safety analytics for oil & gas infrastructure
• Anomaly detection and predictive maintenance
• Sensor-driven environmental monitoring
• Data analysis under low-temperature operational environments
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