Dr. Pengdi Zhang

Dr. Zhang received his Ph.D. in Mechanical Engineering with a thesis entitled “An Integrated Framework for Real-Time Pipeline Corrosion Detection Using Guided Waves and Deep Learning,” focusing on Structural Health Monitoring (SHM). His research integrated physics-based modeling with machine learning, specifically utilizing guided wave propagation, neural networks, and transfer learning for corrosion classification. He also explored the use of synthetic data and digital twins to enhance model performance. Following graduation, he joined Leidos as a Computational Scientist to support the National Energy Technology Laboratory (NETL). In his spare time, he enjoys snowboarding and attending musicals.