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Bahman Bahmani

Bahman Bahmani
Vice President, Data Science and Engineering, Rakuten

Bahman did his PhD at Stanford University, supported by William R. Hewlett Stanford Graduate Fellowship, and focused on the topic of algorithms for big data applications, in which he is a well-published author in some of the best conferences and journals, including PVLDB, SIGMOD, WWW, and KDD. He was the last PhD student of the legendary late Rajeev Motwani, and was also advised by Ashish Goel and Prabhakar Raghavan (formerly Yahoo Chief Strategy Officer, currently Google VP of Engineering). His industry experience during his PhD studies spans several internships and collaborations with some of the best researchers and practitioners from Twitter, Microsoft Research, Yahoo Research, AOL, and Google. A recipient of the Yahoo Key Scientific Challenges Award, he was dubbed by Yahoo Labs as one of the “outstanding graduate student researchers who have the greatest potential to make significant contributions and become thought leaders in their research fields”.


Hardcore Data Science Gramercy Suite
Bahman Bahmani (Rakuten)
Average rating: ****.
(4.10, 10 ratings)
We will show how scalable algorithm design can enable big data applications that would otherwise be simply infeasible even using the most modern big data architectures. Then, we provide effective techniques for designing such algorithms and explain the tradeoffs governing them. We will crystallize these techniques using concrete examples from machine learning to social network and text analytics. Read more.
Office Hour Table D
Bahman Bahmani (Rakuten)
During the office hour, depending on the attendees’ interests, we can go into more details on any of the following topics: * Tradeoffs governing MapReduce algorithms * Techniques and patterns for MapReduce algorithm design * How to use the introduced techniques for attendees' particular applications Read more.


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