Chen Kan from the Department of Industrial and Manufacturing Systems Engineering at Pennsylvania State University will present a Seminar this Thursday, April 7, at 1:30pm in the Rady Room, Nedderman Hall (NH) 601. Mr. Kan’s presentation title, abstract, and biographical sketch are below.
All students and faculty are encouraged to attend. Because this is a Thursday seminar, there will be no attendance sheet for GTAs and on-campus GRAs. However, there will be a student meeting on Friday at which attendance will be recorded. More on the student meeting is forthcoming.
Author: Chen Kan
Title: Dynamic Network Modeling and Analysis of Large-scale Internet of Things with Manufacturing and Healthcare Applications
Location: Rady Room, NH 601
Date: Thursday, April 6
Time: 1:30pm – 2:50pm
Abstract: Rapid advancement of sensing technology brings the proliferation of high-dimensional data with complex structures. Realizing full potentials of sensing data depends on the development of new sensor-based methods and tools for process monitoring and control, as well as data-driven system optimization. However, the complexity of sensing data poses significant challenges: 1) Distributed sensing leads to multi-channel signals, which show high levels of nonlinear and nonstationary behaviors in the presence of extraneous noises. 2) Advanced imaging technology leads to 2-D, 3-D or higher dimensional functional images (i.e., dynamic and time-varying), which contain rich information about the underlying processes. 3) Internet of Things connects large amounts of machines in digital manufacturing, as well as human subjects in smart and connected health. This gives rise to big and networked data that call for next-generation methodologies for system informatics and control. The goal of my research is to develop innovative sensor-based methodologies for modeling, monitoring and optimization of large-scale complex systems. Specifically, my research focuses on the development of nonlinear and stochastic network models for process monitoring and control. This research will enable and assist in 1) the handling of massive, complex data generated from advanced sensing systems in manufacturing and healthcare settings; 2) the extraction of pertinent information about system dynamics; and 3) the exploitation of acquired knowledge for decision making and performance optimization.
Biographical Sketch: Chen Kan is currently a Ph.D. candidate in the Department of Industrial and Manufacturing Engineering, the Pennsylvania State University. His research focuses on wireless sensing systems and network theory for large-scale IOT-based monitoring, modeling and control of complex systems, with applications for advanced manufacturing and smart health. He was the Entrepreneurial Lead of NSF I-Corps Team of the Mobile E-network Smart Health (MESH) project in 2014. He has published multiple papers in top journals, including Journal of Manufacturing Systems, Quality and Reliability Engineering International, Computers in Biology and Medicine, IEEE Journal of Biomedical and Health Informatics, and IEEE Transactions on Automation Science and Engineering.