Seif Lotfy is a Co-Founder and CTO with 17 years of experience building high-throughput, cloud-native data platforms and distributed systems from startup to enterprise scale. Based in Cairo, he led Axiom to provide serverless, unlimited machine-data storage and previously engineered scalable analytics and ETL pipelines at Xamarin that delivered sub-second probabilistic query performance. He combines hands-on systems programming—contributions to InfluxDB, HyperLogLog++, and a popular cuckoo filter implementation—with platform and DevOps work around serverless runners and queue systems. Known for shipping production-quality code and useful open-source tooling, he focuses on data integrity, performance optimizations, and compact probabilistic data structures. His background spans numerical modeling, OpenStack automation, and real-time bidding research, revealing a rare mix of applied mathematics and pragmatic engineering. Quick to learn and intensely curious, he thrives on turning complex data problems into efficient, maintainable systems.
17 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BSc), Bachelor of Science (BSc) at TU Darmstadt
Contributions:2 reviews, 57 commits, 21 PRs in 6 years 10 months
Contributions summary:Seif primarily focused on implementing and refining a Cuckoo Filter, a data structure. Their work involved setting up the in-memory structure, incorporating methods for insertion, lookup, and deletion. The user also made improvements to the code and documentation. Additionally, they added and refined helper functions and implemented encode and decode functionality.
HyperLogLog with lots of sugar (Sparse, LogLog-Beta bias correction and TailCut space reduction) brought to you by Axiom
Role in this project:
Back-end Developer
Contributions:1 release, 1 review, 75 commits in 4 years 4 months
Contributions summary:Seif primarily focused on implementing core functionalities for the HyperLogLog++ data structure in Go. They initiated the implementation of the `hlltc` package, encompassing the foundational utilities and compressed data structures. The user also introduced marshaling and unmarshaling capabilities, allowing for data persistence and reconstruction. Furthermore, they worked on optimizing the internal registers' behavior and introduced bias corrections for cardinality estimations, improving the accuracy of the data structure.
sparsesugarloglogreductionbias
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