Daniel Gatica-Perez among 2018th most influential scholars by AMiner

Recognized for his outstanding contributions to the field of Web and Knowledge Engineering, Multimedia, the head of Idiap’s Social Computing group is among the most influential researchers according to the AMiner platform.

In 2018, the AMiner Most Influential Scholar List names the world's top-cited research scholars from the fields of Artificial Intelligence (AI). The list is conferred in recognition of outstanding technical achievements with lasting contribution and impact to the research community. The 2018 winners are among the most-cited scholars from the top venues of their respective subject fields in recent ten years (between 2007 and 2017). Recipients are automatically determined by a computer algorithm deployed in the AMiner system that tracks and ranks scholars based on citation counts collected by top-venue publications. The full list of the most influential scholars can be found here:  https://www.aminer.cn/ai10/ke


A research project in social influence analysis


Created as a research project in social influence analysis, social network ranking, and social network extraction, AMiner is a free online service for academic social network analysis and mining. As of 2018, the system has collected information on over 136 million researchers, 230 million publication papers, and 368,402 venues. Started in 2006, the research was funded by the Chinese National High-tech R&D Program and the National Science Foundation of China.


AMiner is commonly used in academia to identify relationships between and draw statistical correlations about research and researchers. The platform is designed to search and perform data mining operations against academic publications on the Internet, using social network analysis to identify connections between researchers, conferences, and publications. This allows it to provide services such as expert finding, geographic search, trend analysis, reviewer recommendation, association search, course search, academic performance evaluation, and topic modelling.


More information about Aminer: https://aminer.org