On the evening of November 18, the 11th International Academic Report was successfully held in the conference room at the corner of the fourth floor in the School of Computer Science. On this seminar, Liu Le, the Associate Professor from School of Computer Science, Northwestern Polytechnical University, was invited to be the lecturer, and almost 30 undergraduates and postgraduates from School of Computer Science participated in this seminar.
Liu Le held a seminar with the theme of “Comprehending Human Cognitions of Uncertainty Visualization.” Liu Le mentioned, uncertainty inevitably exists in all stages of data analysis. Therefore, effectively getting the uncertainty of data plays an important role in exploring data of the complex phenomenon of nature and science. Visualization makes the most use of visual processing and is considered to be one of the most efficient ways to transmit uncertainty. On the seminar, Liu Le introduced to students about the development of computer information visualization technology, and also showed the visualization techniques for analyzing the structure of the flame model, a mouse body structure and the human brain. He also emphasized the uncertainty knowledge of visualization technology, and some existing evaluation methods of visualization efficiency. By citing relevant references, he represented the modeling analysis of some uncertain time. For example, he explained the prediction of the storm center and the area influenced by storm and showed the specific connotation of uncertainty in data visualization in the form of cartoons.
Ma Zijin, the attendant student said, “Mr. Liu Le gave us an academic seminar about visualization technology in English fluently, which shocked me greatly. In addition, his PPT production style gave me a lot of inspiration and thinking in terms of report and speech. In addition, Mr. Liu's explanation of visualization technology on the seminar gave me more perceptual understanding of visualization on the frontier research direction of Computer Science. As an important part of data, visual uncertainty helps data analysts to understand and analyze data more comprehensively, so as to help users make the most optimal decisions. But many important problems remain to be resolved. For example, how to conduct more effective uncertainty visualization will also be a research direction with rapid development in the field of Computer Science in the future.”
Reviewed by: Guo Bin