Peter Laz

Peter Laz

Professor

What I do

Peter Laz's research is focused in orthopaedic biomechanics and materials, and involves the application of probabilistic methods to assess the contributions of uncertainty. Recent projects have involved the development of statistical shape models to characterize anatomic variability in the knee, shoulder and foot, and population-based evaluations of joint mechanics. In addition, he teaches a variety of undergraduate and graduate courses in solid mechanics and design, including Machine Design, Senior Design, Reliability, Optimization, and Fatigue.

Professional Biography

Peter Laz is a Professor in Mechanical and Materials Engineering and part of the Center for Orthopaedic Biomechanics.
He received a BS in Mechanical Engineering from Duke University, and MS and PhD degrees in Mechanical Engineering from Purdue University. He was a Fulbright scholar in Germany and also worked at the Southwest Research Institute.  He has been at DU since 2001. His research is in the area of probabilistic mechanics with applications to orthopaedic implants, materials and reliability-based design.

Degree(s)

  • BSME, Duke University
  • MS, Mechanical Engineering, Purdue University
  • Ph.D., Mechanical Engineering, Purdue University

Professional Affiliations

  • Orthopaedic Research Society

Featured Publications

Burton, W. S., Sintini, I., Chavarria, J., Brownhill, J., & Laz, P. J. (2019). Assessment of Scapula Morphology and Bone Quality with Statistical Models. Computer Methods in Biomechanics and Biomedical Engineering, 22, 341-351.
Hollenbeck, J., Cain, C., Fattor, J., Fitzpatrick, C., Rullkoetter, P. J., & Laz, P. J. (2018). Statistical modeling to characterize anatomy and disc degeneration in the lumbar spine. Journal of Biomechanics, 69, 146-155.
Sintini, I., Burton, W. S., Sade, Sr., P., Chavarria, J., & Laz, P. J. (2018). Investigating Gender and Ethnicity Differences in Proximal Humeral Morphology using a Statistical Shape Model. Journal of Orthopaedic Research, 36, 3043-3052.
Smoger, L., Cyr, A., Shelburne, K. B., Rullkoetter, P. J., & Laz, P. J. (2017). Statistical Shape Modeling Predicts Patellar Bone Geometry to Enable Stereo-Radiographic Kinematic Tracking. Journal of Biomechanics, 58, 187-194.

Awards

  • Best Teacher Award, Ritchie School of Engineering and Computer Science