How good is Rajeev Motwani?

Rajeev Motwani has a Lunoo score of 8.6/10. This score is based on AI-powered analysis of category fit, feature coverage, pricing signals, public reception, and recency.

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Rajeev Motwani

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description Rajeev Motwani Overview

Rajeev Motwani was a professor of computer science at Stanford University whose research spanned randomized algorithms, approximation algorithms, online algorithms, and web search. He co-authored the textbook 'Randomized Algorithms' (1995) with Prabhakar Raghavan and mentored Larry Page and Sergey Brin, co-authoring foundational work on the PageRank algorithm that underpinned Google's search technology. He served as a technical advisor to numerous technology startups and companies. He died in 2009.

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What role did Rajeev Motwani play in Google's founding?

Motwani, as a Stanford professor, co-authored foundational work on PageRank with Larry Page and Sergey Brin and served as an informal advisor to Google during its early years. The original 1998 PageRank paper lists Motwani alongside Page and Brin, and he was instrumental in connecting the founders with early investors.

What textbook did Rajeev Motwani co-author on randomized algorithms?

Motwani co-authored 'Randomized Algorithms' with Prabhakar Raghavan, published by Cambridge University Press in 1995. The textbook remains the definitive reference in the field, covering topics from randomized sorting and data structures to online algorithms and number-theoretic algorithms.

When and how did Rajeev Motwani pass away?

Motwani passed away in June 2009 at the age of 47. His death was met with an outpouring of tributes from across the technology and academic communities, reflecting his outsized influence as both a researcher and a mentor in Silicon Valley.

What other areas of computer science did Rajeev Motwani contribute to?

Beyond PageRank and randomized algorithms, Motwani made significant contributions to data stream algorithms, approximation algorithms, and online algorithms. He was also an active angel investor and advisor to numerous Silicon Valley startups, bridging the gap between academic theory and industry.