Innovative Creep Analysis Methods. Questo articolo non è disponibile.Innovative Creep Analysis Methods

Vahid Monfared completed his PhD in Mechanical Engineering (Solid and Applied Mechanics), and works as a part-time lecturer/instructor at the University of Rhode Island/URI (USA), He also holds roles as an Associate Professor at Islamic Azad University of Zanjan, and as a Postdoctoral Research Fellow at Harvard Medical School (Harvard University) in the field of Machine Learning (AI) and Data Science to Medicine, Healthcare, and Engineering). Vahid also has practical experience as an engineer at Varian (a Siemens Healthineers company). In addition to the main filed in mechanical engineering (solid mechanics), his research interests include the application of Data Analytics and ML/AI in prediction of complex phenomena such as creep, mechanical deformations, and failure analysis. Along with working on AI and machine learning projects at Harvard Medical School. He furthered his knowledge of applied data analytics and machine learning at the Massachusetts Institute of Technology (MIT) and Boston University (BU) by completing a master’s degree in applied data analytics.