Recently, two research results of the innovation research team of artificial intelligence and big data visualization analysis were accepted by IEEE VIS 2020, an A-list international conference of the China Computer Federation (CCF).

The paper "Visual Abstraction of Geographical Point Data with Spatial Autocorrelations" was supervised by Professor Zhiguang Zhou, Dr. Yuhua Liu, and Dr. Yuanyuan Chen, and was co-authored by Xinlong Zhang, a postgraduate student of the School of Information Management and Artificial Intelligence, and Zhendong Yang, an undergraduate student majoring in Software Engineering. This paper uses the spatial autocorrelation model to express the attribute relationships of geospatial objects, which in turn is maintained and enhanced in the process of simplification of large-scale geospatial data.

The paper "Context-aware Sampling of Large Networks via Graph Representation Learning" was supervised by Professor Zhou and Dr. Liu, and was co-authored by Chen Shi, a postgraduate student of the School of Information Management and Artificial Intelligence, and Lihong Cai and Xilong Shen, undergraduate students majoring in Software Engineering. This paper uses graph representation learning methods to extract semantic features between network graph nodes, which in turn drive the sampled expression of large-scale network graph data and the subsequent calculation and processing. In addition, the paper was also recommended for publication in the A-list journal IEEE Transactions on Visualization and Computer Graphics (TVCG) of CCF.

In recent years, the data visualization team has achieved fruitful research results under the support and funding of ZUFE's innovation research team and the school's Hive team, including hosting 6 projects supported by the National Natural Science Foundation and 8 provincial and ministerial scientific research projects, published more than 30 SCI journal papers, more than 10 research papers on core journals at home, and jointly won the Third Prize of Science and Technology Progress of Zhejiang Province, and undertook and participated in various projects of social services. The team also explores innovative talent training model that combines teaching and research, and strengthens students' extracurricular practice, academic thinking and training of research methods. Currently, the talent training program has achieved initial results.