Abhinandan Das is a Director of Engineering, Search / Principal Engineer at Google.

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 more than 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.

Abhinandan Das is the Director of Engineering, Search / Principal Engineer of Google Search and has been with Google since 2005. ^[1]

From May-August 2004 he worked as a Networking Research Intern at the Nokia Bell Labs. Abhinandan worked as a Research Intern at Microsoft Research from May-August, 2001. ^[1]

1. Abhinandan Das, Mayur Datar, Ashutosh Garg, Shyamsundar Rajaram: Google news personalization: scalable online collaborative filtering. WWW 2007: 271-280

2. Abhinandan Das, Johannes Gehrke, Mirek Riedewald: Semantic Approximation of Data Stream Joins. IEEE Trans. Knowl. Data Eng. 17(1): 44-59 (2005)

3. Abhinandan Das, Johannes Gehrke, Mirek Riedewald: Approximation Techniques for Spatial Data.

SIGMOD Conference 2004: 695-706

4. Abhinandan Das, Sumit Ganguly, Minos N. Garofalakis, Rajeev Rastogi: Distributed Set Expression Cardinality Estimation. VLDB 2004: 312-323

5. Rohit Ananthakrishna, Abhinandan Das, Johannes Gehrke, Flip Korn, S. Muthukrishnan, Divesh Srivastava: Efficient Approximation of Correlated Sums on Data Streams.

IEEE Trans.

Knowl.

Data Eng.

15(3): 569-572 (2003)

6. Rakesh Agrawal, Surajit Chaudhuri, Abhinandan Das, Vivek R. Narasayya: Automating Layout of Relational Databases. ICDE 2003: 607-618

7. Abhinandan Das, Johannes Gehrke, Mirek Riedewald: Approximate Join Processing Over Data Streams.

SIGMOD Conference 2003: 40-51

8. Abhinandan Das, Indranil Gupta, Ashish Motivala: SWIM: Scalable Weakly-consistent Infection-style Process Group Membership Protocol.

DSN 2002: 303-312

1. Determining word boundary likelihoods in potentially incomplete text (US 9239888) ^[1]

2. Distributed set-expression cardinality estimation (US7873689) ^[1]

3. Fresh related search suggestions (US8782071) ^[1]

4. Generating midstring query refinements (US8577913) ^[1]

5. Generating query refinements from user preference data (US9378247) ^[1]

6. Generating sibling query refinements (US8244749) ^[1]

7. Name Disambiguation Using Context Terms (US20140214840) ^[1]

8. Presenting a diversity of recommendations (US8374985) ^[1]

9. Query autocompletions (US9031970 B1) ^[1]

10. Query suggestions based on entity collections (US9342626) ^[1]

11. Recommending products utilizing category attributes (US8612306) ^[1]

12. Scalable Online Collaborative filtering (US9177048) ^[1]

13.Search

suggestion rankings (US20150213041) ^[1]

14. Supplementing search results with historically selected search results of related queries (US9298828) ^[1]

In 2006, Das graduated from Cornell University and with a PhD in Computer science. ^[1] His research interests broadly included datastream processing, data summarization techniques, privacy, data mining, and distributed algorithms.

He graduated from IIT Bombay in 2000 with a B Tech in Computer Science. ^[1]

Abhinandan Das is also a graduate of Fergusson College and St Vincent's High School in Pune, India. ^[1]