Intelligent Engineering Systems
Offered Fall 2019, Fall 2020, Fall 2021
This course introduces the basic concepts and key software and hardware technologies in intelligent engineering systems. Through in-classroom teaching, field visits, case studies and course experiments, students will master the basic concepts of intelligent systems, intelligent decision-making technology, and the application of data analysis technology in intelligent engineering systems. Basic knowledge and theories for the optimal design and operation of intelligent engineering systems regarding system reliability are included, such as fault tree and event tree analyses for complex systems, optimal redundancy allocation problem, multi-objective optimization and predictive maintenance, etc.
Machine Learning and Big Data
Offered Fall 2019, Fall 2020, Fall 2021
This course aims at undergraduates. We introduce probability and matrix theory (e.g., distributions, expectations, information); machine learning (e.g., LR, SVM, KNN, Naive Bayes, etc.), deep learning (e.g., ANN, CNN, GAN, RNN); industrial case (e.g., fault diagnosis, vibration prediction, etc.). This course combines a variety of classical theories with industrial applications.
Managerial Economics
Offered Fall 2018, Fall 2019, Fall 2020, Fall 2021
Managerial economics is a discipline which deals with the application of economic theory to business management. It deals with the use of economic concepts and principles of business decision making. Formerly it was known as “Business Economics” but the term has now been discarded in favor of Managerial Economics. This course is designed for Master of Engineering Management (MEM) students.
Reliability and Risk Management
Offered Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021
The course includes reliability and risk assessment of complex systems, data-driven reliability modeling, accelerated reliability testing, advanced machine learning and optimization methods with the applications to the areas of reliability engineering and risk analysis. The purpose is to enable students to master the necessary advanced tools to analyze and solve reliability problems in engineering practice, and to cultivate students' ability to carry out scientific research independently. The content taught in this course includes relevant knowledge from the basic to the latest cutting-edge, emphasize on the cultivation of scientific research capability, and provide the latest challenging research problems and practical project cases to guide students to learn and to improve.
News
Congratulations to Huan Wang on her paper accepted by IEEE Transactions on Reliability.
Congratulations to Chen Zhang on her paper accepted by IEEE Transactions on Reliability.
Congratulations to Tian-Li Men on her paper accepted by Reliability Engineering & System Safety.
Congratulations to Ying Zhang on her paper accepted by Renewable and Sustainable Energy Reviews.
Congratulations to Huan Wang on her paper accepted by IEEE Transactions on Instrumentation and Measurement.
Congratulations to Han-xiao Zhang on her paper accepted by Reliability Engineering & System Safety.
Congratulations to Hui Wu on her paper accepted by IEEE Transactions on Neural Networks and Learning Systems.
Congratulations to Fei-Peng Wang on her paper accepted by Journal of Risk and Reliability.
Congratulations to Ming Qian on his paper accepted by IEEE Transactions on Industrial Informatics.
Congratulations to Han-Xiao Zhang on her paper accepted by Reliability Engineering & System Safety.
Congratulations to Cheng-Wu Shao on his paper accepted by Risk Analysis.