Nathan Post

Nathan Post is a Research Associate Professor at Northeastern University's Roux Institute with joint appointments in Civil and Environmental Engineering and Mechanical and Industrial Engineering. His research applies machine learning to optimize physical systems in renewable energy and manufacturing.

Key research areas:

• Machine learning for wind farm performance optimization
• Additive manufacturing process characterization
• Reverse osmosis membrane fouling mitigation
• Experimental mechanics for renewable energy systems

Publications demonstrate cross-disciplinary approaches combining experimental mechanics with machine learning. Recent work focuses on wind turbine wake steering, corrosion-resistant alloy discovery, and drivetrain reliability prediction.

Serves as technical advisor to the ReWind Network for wind blade repurposing and develops educational tools for fluid power curriculum. Research employs field data analytics from wind farm SCADA systems and laboratory-scale material testing.