(欢迎各位同行莅临现场交流讨论，会后有头脑风暴和小范围聚餐)
时间：2019年11月6日 （上午：9:00-11:30）
地点：电子科技大学清水河校区图书馆百学堂（图书馆二楼A区与B区之间）
主持人 | 周涛 | |
时间 | 报告人 | 题目 |
9:00-10:00 | Prof. Carlo Vittorio Cannistraci | Machine intelligence and network science for complex systems big data analysis |
10:00-10:30 | Prof. Manuel Sebastian Mariani | The wisdom of the few: Predicting collective success by tracking key individuals |
10:30-11:00 | 周方 （电子科技大学，博士生） | Fast influencers in complex networks |
11:00-11:30 | 李艳丽 （电子科技大学，博士生） | 2-hop-based vs. 3-hop-based link prediction algorithms |
Carlo Vittorio Cannistraci is a theoretical engineer, head of the Biomedical Cybernetics Group and faculty of the Department of Physics in the TU Dresden, which is a member of the TU9 excellence-league (the nine most prestigious technical universities in Germany). Carlo’s area of research embraces information theory, machine learning and complex networks including also applications insystems biomedicine and neuroscience. Nature Biotechnology selected Carlo’s article (Cell 2010) on machine learning in developmental biology to be nominated in the list of 2010 notable breakthroughs in computational biology. Circulation Research featured Carlo’s work (Circulation Research 2012) on leveraging a cardiovascular systems biology strategy to predict future outcomes in heart attacks, commenting: “a space-aged evaluation using computational biology”. The Technical University Dresden honoured Carlo of the Young Investigator Award 2016 in Physics for his work on the local-community-paradigm theory and link prediction in monopartite5 and bipartite networks.In 2017, Springer-Nature scientific blog highlighted with an interview to Carlo his study on “How the brain handles pain through the lens of network science”. The American Heart Association covered this year on its website the recent chronobiology discovery of Carlo on how the sunshine affects the risk and time onset of heart attack. In 2018, Nature Communicationsfeatured Carlo’s article entitled “Machine learning meets complex networks via coalescent embedding in the hyperbolic space” in the selected interdisciplinary collection of recent research on complex systems.
Manuel Sebastian Mariani is the Associate Professor in Physics at the Institute of Fundamental and Frontier Sciences and he is the post doctor of the University of Zurich. His research interests include quantitative analysis of scientific and technological innovation, spreading processes and diffusion in networks, models of network growth and network-based ranking. He has publishednearly 20 papers in international renowned journals such as PNAS, Physics Report, and Physical Review E.
Fang Zhou, a PhD candidate in UESTC, whose research interests include vital nodes identification, spreading models, link prediction, social networks analysis. He has published a paper in CNSNS, and got the CCCN2019 Best Student Paper Award.
Yan-Li Lee, a PhD candidate in UESTC, whose research interests include link prediction, influential nodes identification, recommendation system and economic social network analysis. She has published two research articles in Physica A. She is also one of translators of the book entitled "Individual and Collective Graph Mining: Principles, Algorithms, and Applications" (《单图与群图挖掘：原理、算法与应用》).
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