Seminario: Taming Big Data - Stream Summarization and its Many Applications
Martedì 5 maggio · ore 14:00 Aula P1.6 · DIEF · Speaker : Amr El Abbadi (University of California, Santa Barbara)
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In recent decades, internet-scale applications have generated massive amounts of data from user interactions. To analyze this data, summary statistics are needed, but exact methods are often too slow and resource-intensive. Instead, streaming algorithms use efficient approximations with controlled errors. The focus is on data stream summarization, especially the “heavy hitters” problem, along with related challenges such as handling insertions and deletions, privacy concerns, and applications in cloud caching and network monitoring, showing the connection between mathematical methods and big data management. Biography: Amr El Abbadi is a Computer Science professor specializing in distributed systems and databases. He earned his degrees from Alexandria University and Cornell University. His research focuses on fault-tolerant systems, cloud data management, blockchain, and privacy. He is an ACM, AAAS, and IEEE Fellow and has held important academic roles at UCSB, including Department Chair and Associate Graduate Dean. He has also served as editor for major journals and program chair for conferences like SIGMOD. He has published over 350 papers, supervised more than 40 PhD students, and received several awards for research and mentoring.
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