Date & Time: 
Fri, 10/08/2021 - 11:00am
Herman Shem
Job title: 
Mechanical & Aerospace Engineering, Ohio State University
Discovery Park F116

We all have been amazed by successful applications of AI deep learning technology to areas such as image, speech, text, and games. However, we are also staring to recognize the weaknesses, including long training times and divergent issues, choice of architecture & hyperparameters, and complexity of the set-up. To address this, my recent work has involved the development of a entirely different paradigm in deep learning architecture to overcome these obstacles. Furthermore, I have applied my research to deep learning-driven Digital Twin Technology to engineering design, manufacturing, operational production optimization, and predictive maintenance. The conclusions from my work thus far have produced new comprehensive information/knowledge-based prognostics and health management e-tools for remaining useful life (RUL) predictions, predictive/proactive maintenance, scheduling optimization and synchronization high reliability, maintainability, and safety of plant equipment of all types of mass production or assembly processes. As more real and generative maintenance data becomes available and a deeper repository of such data is created, my deep learning-driven management will eventually take over the core competencies to form a new knowledge-centric proactive/predictive maintenance culture aiming to predict RUL o the components optimized operation quick real-time decision-making. I look forward to discussing the above work. Additionally, I will also briefly discuss my recent work in bridging deep learning and healthcare applications.

Herman Shem

Dr. Herman Shen, Professor of Mechanical & Aerospace Engineering (MAE), The Ohio State University (OSU), received his Ph.D. degree from the University of Michigan in 1989 and joined the faculty of MAE at OSU in 1989. For the past thirty-two years, he has pioneered developments in structural health management framework and fatigue life prediction schemes for gas turbine engines, power generation assets, wind turbines, offshore platforms, oil & gas assets, pipelines, and manufacturing processes.

His recent research efforts have been focused on bridging deep learning and engineering, manufacturing, and healthcare applications. Dr. Shen is a recipient of the Air Force Research Initiation Award, ALCOA Science Foundation Award, and The Ohio State University College of Engineering Lumley Research Award. Dr. Shen has published more than 200 journal papers, book chapters, US Patents, and technical reports and received more than $6 million in research funding at Ohio State.

Seminar ID: 

Mechanical Engineering