网络信息挖掘专题报告会

文:李艳丽 图:李艳丽 / 来源:计算机学院 大数据研究中心 / 2019-11-05 / 点击量:1076

  由电子科技大学计算机科学与工程学院(网络空间安全学院),大数据研究中心主办的“网络信息挖掘”专题报告会,邀请到Carlo Vittorio Cannistraci教授、Manuel Sebastian Mariani副研究员等作学术交流。具体安排如下,欢迎广大师生参加。

  时 间:2019年11月6日 9:00-11:30

  地 点:电子科技大学清水河校区图书馆百学堂视听阅览室(图书馆二楼A区与B区之间)

  主持人: 周涛教授

  日程安排:

主持人

周涛(电子科技大学,教授)

时间

报告人

题目

9:00-10:00

Carlo Vittorio Cannistraci

(Technische Universität Dresden,教授)

Machine intelligence and network science for complex systems big   data analysis

10:00-10:30

Manuel Sebastian Mariani

(电子科技大学,副研究员)

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: which will   win?

  报告人介绍:

Carlo.jpg

  Carlo Vittorio Cannistraci 

  Technische Universität Dresden,教授

  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 Communications featured 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.png

  Manuel Sebastian Mariani

  电子科技大学,副研究员

  He is the research 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 interestsincludequantitative 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.

  周方 电子科技大学,博士生

  His research interests include vital nodes identification, spreading models, link prediction, social networks analysis. He has published a paper in CNSNS(two district top journal), and got the CCCN2019 IJMPC Best Student Paper Award.

  李艳丽 电子科技大学,博士生

  Her research interests includelink prediction, influential nodes identification, recommendation system and economic social network analysis. She is also one of translators of 《Individual and Collective Graph Mining: Principles, Algorithms, and Applications》(《单图与群图挖掘:原理、算法与应用》)


编辑:杨棋凌  / 审核:李果  / 发布者:陈伟