Computer Science Events
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Computer Science
[PAST EVENT] Colloquium on March. 13 at 8AM in McGl 020
March 13, 2015
8am - 11:59pm
Title: Large-scale Network Analysis and Graph Mining
Speaker: Nesreen Ahmed, Ph.D., Purdue University
Abstract: Network analysis and graph mining play a prominent role in providing insights and studying phenomena across various domains, including social, behavioral, biological, transportation, entertainment, and financial domains. For example, online activity and interaction networks formed from electronic communication (e.g., email), social media (e.g., Twitter), and content sharing (e.g., Facebook). A key characteristic of these networks is that their complex structure is massive and continuously evolving over time, which makes it challenging and computationally intensive to analyze, query, and model these networks in their entirety. In this talk, I will discuss challenges of large-scale network analysis and show how sampling can mediate between the accuracy requirements of the network analysis task, the network characteristics, and the available resources. The talk will include a discussion of sampling, estimation, and visual network analytics and mining, showing how to use them for high-impact machine learning and big data applications in social, biological, and behavioral domains.
Bio: {{http://www.nesreenahmed.com, Nesreen Ahmed}} is a doctoral researcher in the Department of Computer Science at Purdue University. Her research interests in large-scale data mining and machine learning focuses on the design of efficient and scalable techniques for the analysis and modeling of network, social media, and time-series data. Nesreen earned a master's degree in statistics and computer science from Purdue University and a bachelor of science from Cairo University. She authored numerous papers at top conferences, journals, as well as patents. She has also given tutorials at top data mining conferences. Nesreen worked as a researcher at Facebook, Intel data analytics, Adobe Advanced Technology labs, and the data mining and computer modeling Center of Excellence in Cairo. She has also authored the web-based network repository project {{http://www.networkrepository.com}}, the first data repository with interactive visual graph analytics to help researchers find, explore, and understand network data in real-time.
Speaker: Nesreen Ahmed, Ph.D., Purdue University
Abstract: Network analysis and graph mining play a prominent role in providing insights and studying phenomena across various domains, including social, behavioral, biological, transportation, entertainment, and financial domains. For example, online activity and interaction networks formed from electronic communication (e.g., email), social media (e.g., Twitter), and content sharing (e.g., Facebook). A key characteristic of these networks is that their complex structure is massive and continuously evolving over time, which makes it challenging and computationally intensive to analyze, query, and model these networks in their entirety. In this talk, I will discuss challenges of large-scale network analysis and show how sampling can mediate between the accuracy requirements of the network analysis task, the network characteristics, and the available resources. The talk will include a discussion of sampling, estimation, and visual network analytics and mining, showing how to use them for high-impact machine learning and big data applications in social, biological, and behavioral domains.
Bio: {{http://www.nesreenahmed.com, Nesreen Ahmed}} is a doctoral researcher in the Department of Computer Science at Purdue University. Her research interests in large-scale data mining and machine learning focuses on the design of efficient and scalable techniques for the analysis and modeling of network, social media, and time-series data. Nesreen earned a master's degree in statistics and computer science from Purdue University and a bachelor of science from Cairo University. She authored numerous papers at top conferences, journals, as well as patents. She has also given tutorials at top data mining conferences. Nesreen worked as a researcher at Facebook, Intel data analytics, Adobe Advanced Technology labs, and the data mining and computer modeling Center of Excellence in Cairo. She has also authored the web-based network repository project {{http://www.networkrepository.com}}, the first data repository with interactive visual graph analytics to help researchers find, explore, and understand network data in real-time.
Contact
[[cs|ppeers, Pieter Peers]]