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Aneesh Sharma
Adding randomness to Google
Aneesh Sharma is a Software Engineer at Google, based in Stanford, California. He has a robust academic and professional background in computer science, particularly focusing on algorithmic analysis and its applications in social and information networks.
Education
- Ph.D. in Theoretical Computer Science from Stanford University (2006-2010)
- Masters in Computational Mathematics from Stanford University (2004-2006)
- B.Tech. from the Indian Institute of Technology, Delhi (1998-2002)
Professional Experience
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Software Engineer at Google (August 2017 - Present)
- Engaged in algorithmic analysis to enhance understanding of complex networks.
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Member of Technical Staff at Twitter (October 2010 - May 2017)
- Contributed to the development of algorithms for real-time content recommendations and user engagement strategies.
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Graduate Student Researcher at Stanford University (September 2006 - August 2010)
- Focused on research that utilized algorithmic tools to analyze social and economic networks.
Internships
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Summer Intern at Google (June 2007 - September 2007)
- Worked on search quality algorithms.
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Summer Intern at Microsoft (June 2008 - September 2008)
- Developed algorithms for search result diversification.
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Summer Intern at Yahoo! (June 2009 - September 2009)
- Focused on learning clickthrough rates.
Research Interests
Aneesh's research interests include:
- Algorithmic analysis tools
- Social and information networks
- Real-time data processing and recommendations
He has authored several papers on topics related to network structures and algorithms, contributing significantly to the fields of computer science and data analytics.123
