Dr. Ham

Suyun Ham, Ph.D., P.E.

Associate Professor in the Department of Civil Engineering at the University of Texas at Arlington
Director of the Smart Infrastructure and Testing Laboratory (SITL)
Office: 416 Yates St., 433 Nedderman Hall, Arlington, TX 76019​
Phone: 817-272-5217    / Fax   : 817-272-2630
email: s.ham@uta.edu

About him
Dr. Ham is currently an Associate Professor at the University of Texas at Arlington. HHe also holds his Civil Engineering Professional Engineer license (Texas PE License #153758). He finished his Ph. D. in Civil Engineering at the University of Illinois at Urbana-Champaign. Before that, he worked in industries for seven years as a researcher and a structural engineer on projects for more than 100 buildings and infrastructure designs. Dr. Ham’s interest area is nondestructive evaluation and structural health monitoring His research interests include nondestructive testing with advanced sensing where he applies mechanical and magnetic field phenomena to assess the condition of infrastructure. His secondary interests lie in material characterization and advanced machine learning (ML) and artificial intelligence (AI). He perform various infrastructure damage assessment field and laboratory testing include rail structures, bridge structures, and nuclear power plants. Dr. Ham is also an expert in full-scale structural experiment testing, advanced numerical analysis, and innovative sensing development.

Research Honor
Dr. Ham is a winner of the American Concrete Institute (ACI)-James Instrument Award, a recipient of the American Society Nondestructive Testing (ASNT) Research Proposal Fellowship Award in 2012, and a winner of Qualitative Nondestructive testing Evaluation (QNDE) Research Competition in 2014.

Research Interests

  • New energy / Metal hydride / Superadiabatic Thermal Wave
  • Sustainable / Smart Infrastructure
  • Nondestructive Testing / Structural Health Monitoring / Damage Assessment
  • Sensor Development /Advanced Sensing
  • Visualization technique: Image Processing, Image Reconstruction Algorithm
  • Automated inspection