Ran Chang’s work centers on technology that’s future-focused and frequently in the news, including driverless cars, electric vehicles, machine learning, and user-friendly content-based methods of searching for images in vast databases.
Many large collections of images, such as surveillance camera data, lack word-based labeling and categorization. Pattern recognition and machine learning is crucial to categorizing and retrieving these images efficiently. Chang’s work has examined not only how to refine such image-based searches, but how to make machine learning more efficient with every search.
A lecturer in the Department of Human-Centered Computing at SOIC, he’s the author of a published book on using DSP software to develop integrated environment CCS. Chang also has authored and co-authored more than a dozen peer-reviewed journals and conference publications.
In 2011, he joined the Energy Dynamics Lab in Utah State University Research Foundation as a research officer. He participated in research projects dealing with moving object tracking, as well as inductive electricity power transfer for electrical vehicles. During this period, Chang’s research work was rewarded by three U.S. patents.
INFO I210 Information Infrastructure I
INFO I211 Information Infrastructure II
INFO I223 Data Fluency
INFO I421 Applications of Data Mining
INFO I425 Web Services in Information Systems