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Systems Research Group

Research in database performance, application modernization, and programming languages.
An illustration that suggests coding and software development.
Who We Are
The MongoDB Systems Research Group focuses on various aspects of software engineering and related disciplines, such as programming/query languages, developer productivity, ML coding assistants, and data processing.
Research Areas
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Software modularity and extensibility

Modularizing monolithic software makes it easier to develop, maintain, extend, and compose.
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Programming and query languages

Next-generation approaches to writing programs and queries can unlock value in software and data.
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Efficient data processing and handling

Data is most valuable when it is easily and efficiently processed, regardless of system interfaces.
Our Team
Kevin Pulo image

Kevin Pulo

Staff Research Engineer
Kevin's research focuses on novel approaches to programming, and code modularity and extensibility.
Read bio

Kevin attended the University of Sydney, receiving a bachelor's (Hons) (2000) and Ph.D. in computer science (2005) in the field of information visualization, specifically the navigation and animation of clustered graphs. Prior to joining MongoDB, he worked in high-performance computing at Australia's peak academic supercomputing facility, doing a mix of low-level systems and tool programming, high-level scientific computation programming, scientific user education/training, and visualization development.

Kevin started at MongoDB in 2013 in Technical Services, focusing on technical deep-dives, tooling to boost engineer productivity, knowledge base, and close collaboration with the MongoDB core server engineering team. Following this, he joined the core server sharding team as a software engineer, where he implemented cluster-wide read/write concern (including provenance), the sharding vector clock, and tripwire assertions.

In 2020, Kevin was the first person to join MongoDB Labs (now MongoDB Research), where he worked on aspects of elastically scaling MongoDB, followed by various projects looking at quantifying and improving the modularity and extensibility of the MongoDB core server. Kevin's research interests also include improving the MongoDB aggregation pipeline's expressiveness and next-generation programming approaches, especially those based on logical transformations rather than text editing.