The Sketches of Infinite Data and Algorithms for Real-Time Data Insights
-- Approximate Algorithms, Stream Processing, Reservoir Sampling, Bloom Filter, Flajolet-Martin, Exponentially Decaying Windows, Estimating moments from streams ...--
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Synopsis:
How are machine learning algorithms able to answer questions from any nook and corner of the World Wide Web? How are trending hashtags from the near infinite microblog posts, unique visitors and other distinct counts in the near infinite website traffic determined? How do blogging websites avoid recommending articles a user has previously read? In general, how can we answer complex queries about enormous data streams without storing them entirely, in real-time? The answer often lies in clever approximation algorithms and data "sketches" that capture essential properties using vastly reduced space. The relentless flow of data in modern systems indeed presents significant challenges. These data streams are often too large to store and too fast to process exhaustively with traditional methods. This talk introduces key sketching and approximation techniques that help generate real-time data insights by processing data streams.
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Date and Time
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- Date: 20 Aug 2025
- Time: 01:00 AM UTC to 03:30 AM UTC
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- Starts 27 April 2025 07:00 AM UTC
- Ends 19 August 2025 07:00 AM UTC
- No Admission Charge
Speakers
Dr. Vishnu S. Pendyala of San Jose State University
Biography:
Vishnu S. Pendyala, PhD, is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the Santa Clara Valley Chapters of IEEE Computer and Computational Intelligence Societies, Area 4 Coordinator for Region 6, and a Distinguished Contributor of the IEEE Computer Society. As a past ACM Distinguished Speaker, researcher, and industry expert, he gave nearly 100 talks and tutorial sessions in various forums such as faculty development programs, the 12th IEEE GHTC, IEEE ANTS, 12th IACC, 10th ICMC, IUCEE, 12th ACM IKDD CODS and 30th COMAD to audiences at venues such as Stanford University, Google, University of Bolton, Computer History Museum, Universidad de Ingeniería y Tecnología, Lima, Peru, IIIT Hyderabad, KREA, IIT Jodhpur, University of Hyderabad, IIT Indore, IIIT Bhubaneswar. Some of these talks are available on YouTube and IEEE.tv. He is a senior member of the IEEE and ACM. He has over two decades of experience in the software industry in the Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. Two other books on machine learning and software development that he edited are also well-received and found place in the US Library of Congress and other reputed libraries. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022. Dr. Pendyala served on a US government's National Science Foundation (NSF) proposal review panel in 2023. He received the Ramanujan memorial gold medal and a shield for his college at the State Math Olympiad. He also played an active role in the Computer Society of India and was the Program Secretary for its annual national convention.
Address:One Washington Sq, San Jose State University, San Jose, New Jersey, United States, 95192-0250
