Those who knew Rajeev as a young boy remember him as an avid reader. When Rajeev was seven, his father was stationed in the scenic town of Devlali near Mumbai, India. His family would walk a kilometer to the local library to get books, and the seven-year-old Rajeev would be seen reading the books they had borrowed from the library as they walked home! His brothers recall that not a single day would pass when he did not read a whole book. Rajeev would read books of all types, including novels, comics, autobiographies and scientific books.

This was partly shaped by the books I had at home. My parents for some reason had a lot of these books - 10 great scientists or five famous mathematicians - their life story and so on. As a child, whatever heroes you read about you want to become.

Rajeev and I were classmates is St Columba's High School in New Delhi over 30 years ago. Of course he was a brilliant maths whiz even back then, but what struck me the most is how vividly I remember how much he used to help me and other classmates understand the complex problems that were a bit beyond our grasp.

Nori had just come back from Europe. He stayed for a year or so and taught the first course in programming. He was a wonderful teacher and used to tell great stories. ... Nori ... was a very inspiring person. He did more than just teaching. He created such a wonderful ecosystem and developed a personal connection with his students.

[Berkley] was a very politically oriented university. .... Ronald Reagan was the president then. So then for 3 years I had a blast. Did not do any work and fully enjoyed the environment. My advisor was Richard Karp, who won the Turing award - which is like the Nobel Prize in computer science in 1985-86, when I had finished those 3 years. It was then that I thought that I was not doing anything and letting this man down. So from then on I worked really hard and was quite productive for the next two years.

I first met Rajeev when I came to Stanford in 1988. We were both young researchers and Rajeev struck me from the beginning as brilliant, very knowledgeable, and having broad interests. Working with him, he was always full of new ideas, prolific, but also very calm and mature. He was very ambitious of course, yet I never felt that he was in any way competitive. He had a very quiet self confidence which reflected on everyone around him. I felt very fortunate to have collaborated with him.

That there might be profit in extending the classical notion of computation to encompass random choice was a fundamental insight. The potential value of this extension became apparent in the mid-1970s with the discovery, by Rabin, and Solovay and Strassen, of fast primality tests based on the construction of "dense witnesses" to compositeness. It is only in the last decade or so, however, that most of us have come to appreciate the true importance of the role of randomness in the study of computation. Today, it seems that randomness has contributed at least as much to computer science - surprising results, exciting new techniques, and practical algorithms - as that other extension to classical computation, namely, parallelism. But whereas there have been several books on parallel computation (though fewer good ones), Motwani and Raghavan's is the first textbook, to the best of the reviewer's knowledge, devoted to randomised algorithms. The new book arrives at a strategic moment, for it is still just possible to cover in a single volume all the main aspects of the topic. ... Even though the pace is often rapid, the authors have succeeded in making the material accessible. By emphasising the role of a number of key ideas and techniques, they have elucidated the structure of the subject matter and imparted a satisfactory shape to the book. ... This is an authoritative work by researchers active in the field. The book is welcome as a reference work, as a source book for algorithmic ideas, and as a graduate-level course text. (My guess is that the material is too advanced for any but the most exceptional undergraduate class.)

At the time when I started graduate school, I was somewhat unexcited about theoretical Computer Science, and it was Rajeev's Randomized Algorithms class that made me fall in love with theory again. His lectures were so perfectly crafted, from the progression of describing a simple approach providing the intuition to generalizing it, to doing an impeccable formal analysis, to the perfect board technique, that I left every lecture excited about a new powerful topic that I have just learned and understood. Rajeev could be covering the contents of a few serious research papers in one lecture but in his presentation, understanding them was both effortless and insightful.

As a researcher and technologist, Rajeev was brilliant - words could do little justice in describing his immense influence. As a teacher, he was awe-inspiring - carrying with him an equanimity and cheerfulness that remained undisturbed through every lecture. As a student advisor, he was kind and supportive - never impatient or proud (though he may have had every reason to be so). As a supervisor, he was trusting and understanding. Most of all, however, his immense stature never came in the way of his friendly, smiling disposition ...

Rajeev Motwani's great interest in fundamental problems of theoretical computer science and a keen interest and awareness of applications sets him apart as a rarity among theoretical computer scientists. He repeatedly exhibited a grasp of issues affecting many areas of computing, and actively sought out and influenced new applications of his theoretical ideas.

We formed this research group called Midas which stood for Mining Data At Stanford. We did a lot of good work on data mining. Then there was this guy called Larry Page who wasn't really a part of the Midas group but was a friend of Sergey Brin [who was part of the group] and would show up for these meetings. He was working on this very cool idea of doing random walks on the web. When I understood what the World Wide Web would look like, I knew I had to somehow force randomness into it. When Larry showed us what he was doing, it was like a complete epiphany, we thought it was absolutely the right thing to do. So Sergey got involved and it became a sub group inside Midas. I was really a good sounding board for Sergey and Larry and I could relate to what they were doing through randomness.

In this paper, we take advantage of the link structure of the Web to produce a global "importance" ranking of every web page. This ranking, called PageRank, helps search engines and users quickly make sense of the vast heterogeneity of the World Wide Web.

We have developed a global ranking of web pages called PageRank based on the link structure of the web that has properties that are useful for search and navigation ... We have used PageRank to develop a novel search engine called Google, which also makes heavy use of anchor text.

Rajeev accepted me as a student when I was unsure of my interests and capabilities and gave me direction by suggesting concrete open problems. The many hours he spent with me in my first few years here, when I needed his time the most, have contributed much to my scholarship. I express my sincere thanks to him for his support, guidance and wisdom. His persistence in tackling problems, confidence, and great teaching will always be an inspiration to me.