Murali Krishna Ramanathan

AWS AI Labs

Murali Krishna Ramanathan is a Principal Applied Scientist at Amazon Web Services (AWS), where he co-leads AWS CodeWhisperer, a machine learning-powered service that generates code in integrated development environments (IDEs).1 2 He joined AWS in August 2022 and is based in the San Francisco Bay Area.2

Professional Background

Ramanathan has extensive experience in software development and research:

Current Role: At AWS, he focuses on improving developer productivity through AI-powered code generation.1 2
Previous Experience: Before joining AWS, he worked at Uber Technologies as a member of the Programming Systems group, where he designed and implemented program analysis tools to enhance the quality and performance of Uber applications.3
Industry Experience: He also worked in the core analysis team at Coverity in San Francisco, developing widely-used program analysis tools.3

Education

Ramanathan has a strong academic background in computer science:

Ph.D. in Computer Science from Purdue University (2003-2008)2
M.S. in Computer Science from Purdue University (2000-2002)2
B.E. in Computer Science and Engineering from Anna University (1996-2000)2

Research and Achievements

Ramanathan is recognized for his contributions to software engineering and program analysis:

Recipient of the Google Faculty Research Award (2015)1 3
ACM SIGSOFT Distinguished Paper Award (ISSTA 2016)1 3
Maurice Halstead Award (Purdue 2006)1

His research interests include large language models, program analysis, and concurrency.1

Notable Projects

AWS CodeWhisperer: Co-leads this ML-powered service that generates code based on existing code and comments.1 2
Piranha: Built an automated refactoring tool to delete code due to stale feature flags at Uber.1
Go Data Race Detection: Contributed to dynamic data race detection for Go microservices code.4
SymPrompt: Recently involved in research on code-aware prompting strategies for large language models in test generation.5

Ramanathan continues to be active in the field, publishing research papers and contributing to advancements in AI-assisted software development and program analysis.