Masoud Koleini
Principal Software Research Software Engineer at Arm
Austin, Texas, United States
Summary
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Rockstar🎓
Top SchoolMasoud Koleini is a Principal Research Software Engineer with 11 years of experience, based in Austin, specializing in stream processing, IoT edge computation, and production ML pipelines. As the maintainer of Fluent Bit’s Stream Processor at Arm, he has deep expertise in high-performance back-end systems and has enhanced SQL-like parsing, aggregate/group-by semantics, and timeseries functions for a widely used logs/metrics processor. His background blends formal research—holding a PhD and prior work on formal verification and unikernel development—with practical distributed systems and microservices engineering in Erlang, Python and C/C++. Masoud’s career spans embedded systems, security-focused research, and cloud-scale data services, reflecting a rare combination of low-level hardware-driven engineering and large-scale data processing.
11 years of coding experience
16 years of employment as a software developer
PhD Computer science, PhD Computer science at University of BirminghamMSc Telecommunications, MSc Telecommunications at Isfahan University of Technology
Github Skills (15)
c1710
ag10
stream-processing10
aggregate10
aggregates10
aggregations10
text-parsing10
c1110
parsing10
sql10
aggregator10
time-series9
data-structure7
data-structures7
logging6
Programming languages (8)
Github contributions (5)
fluent/fluent-bit
Mar 2019 - Aug 2022
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX and Windows
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 reviews, 60 commits, 36 PRs in 3 years 6 months
Contributions summary:Masoud primarily contributes to the stream processor module, focusing on enhancing the parsing capabilities for SQL WHERE clauses. Their work includes adding support for boolean values and null checks within the WHERE condition syntax. The user also refactored and improved existing aggregate functions and group-by functionalities. Additionally, the user implemented support for a timeseries function, enhancing the system's ability to process data over time.
data-collectorpromqlloggingprometheuscloudnative
koleini/fractal
May 2015 - Oct 2019
Contributions:21 pushes, 4 branches in 4 years 5 months
on-demanddnsdemanddns-serverunikernels
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