Overview
Our lab focuses on developing and applying data analytics tools to facilitate the transition from 'Data Rich' to 'Information Rich' in smart and connected systems. See both opportunities and challenges in the smart and connected systems in Figure 1.
Figure 1. Opportunities and challenges in the smart and connected systems.
Learn more about the three research topics explored in our lab:
System Modeling Based on Transfer Learning
Transfer learning (TL) is a machine learning tool that focuses on storing knowledge gained while solving one problem and applying it to a different but related problem.
Process Monitoring Based on Bayesian Analysis
The Bayesian analysis facilitates the real-time update of the process status in a probabilistic view, which provides rich information/evidence for decision-making.
Control of Stochastic Processes
The control of stochastic processes refers to identifying the optimal input settings to achieve the desired output performance. This is a widely studied problem in the optimization community.
Other Topics
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Seasonal to sub-seasonal temperature and precipitation modeling and prediction
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Modeling of reduced oxide graphene FET sensors
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Fault diagnosis of rotational machinery