Hakan Yasarer

Hakan Yasarer is an Associate Professor of Civil Engineering at The University of Mississippi (Ole Miss). He holds a Ph.D. in Civil Engineering from Kansas State University (2013). His research focuses on geotechnical engineering, pavement performance modeling, groundwater hydrology, and machine learning applications in civil infrastructure systems. He specializes in developing predictive models using artificial neural networks (ANN) and integrating geospatial data with environmental monitoring systems.

• Education: Ph.D. Civil Engineering, Kansas State University (2013)

Dr. Yasarer’s work emphasizes sustainable infrastructure solutions, including pavement deterioration modeling for state transportation departments (e.g., MDOT), groundwater stress zone mapping using GRACE satellite data, and innovative material applications like recycled glass for soil stabilization. He has pioneered open-source frameworks for downscaling GRACE data and transforming hydrology tools into web APIs. His research bridges civil engineering challenges with advanced computational methods, addressing both terrestrial (e.g., Mississippi Delta groundwater systems) and extraterrestrial construction scenarios (e.g., moon-to-Mars infrastructure).

His publications consistently apply machine learning to civil engineering problems, such as predicting geotechnical parameters from seismic data, optimizing pavement maintenance strategies, and analyzing synthetic groundwater datasets. While no specific awards are listed, his contributions to geospatial hydrology and ANN-based modeling reflect impactful scholarly work.

Dr. Yasarer’s advising and grant activities are integral to his role, though specific grant details are not provided in the text. His lab likely focuses on computational civil engineering tools and sustainability initiatives, supported by collaborations with state agencies and NASA-funded projects like the 'In-Situ, Resilient, and Sustainable Moon to Mars Construction' campaign.