Abhinandan Das
Dr Abhinandan Das received his Ph.D. in Computer Science from Cornell University in 2005. He has authored several research publications in leading conferences and journals on databases, data mining and data stream processing (including a best paper nomination at the World Wide Web conference). His published work has been deployed in production systems in companies such as Google, Uber, and Microsoft, among others. He holds 20+ issued and filed patents in diverse areas such as real-time Recommendation Systems, Collaborative Filtering, Personalization, Data Mining, Related Search, Query Suggestions, Web Search Ranking, Autocomplete Systems, Query Rewriting and Spell Correction, Text Input Likelihood Prediction, Name Disambiguation, Distributed Group Membership Protocols and Distributed Systems Monitoring, among others.
Authored Publications
Google Publications
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Semantic Approximation of Data Stream Joins
Distributed Set Expression Cardinality Estimation
Approximation Techniques for Spatial Data
Approximate Join Processing Over Data Streams
Efficient Approximation of Correlated Sums on Data Streams
Rohit Ananthakrishna
Johannes Gehrke
S. Muthukrishnan
Divesh Srivastava
IEEE Trans. Knowl. Data Eng., 15(2003), pp. 569-572
Automating Layout of Relational Databases
SWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocol
Preview abstract
The group membership protocol described in this paper (SWIM) has since been implemented by Uber and has been in use in their production infrastructure for several years as of 2016(!). It is a key scalable building block of Uber's Ringpop, and is referenced prominently on their engineering blog: https://eng.uber.com/intro-to-ringpop/
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