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@kelindar
kelindar
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🚀
Building Platforms in Middle East!

Roman Atachiants kelindar

🚀
Building Platforms in Middle East!
Ph.D. in parallel systems; created superapps so reliable they only break during peak hours.

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kelindar/README.md

I've spent my career building systems that scale — sometimes even as planned. At Careem (Uber Inc.), I led the architecture for Data & AI, building platforms for machine learning, experimentation, and event processing that supported operations at scale. Before that, I served as Head of Data Science at AirAsia, where I worked to make data-driven decisions more accessible across the organization. At Grab, Southeast Asia's superapp, I worked on experimentation platforms and was the architect for transport and driver experience, helping millions of rides happen more efficiently. My Ph.D. from Trinity College Dublin & IBM Research focused on debugging parallel systems and visualizing performance problems — a mix of computer science and psychology that taught me patience (and the limits of it). Earlier in my career, I worked on everything from autonomous helicopters to particle simulators, building systems that were occasionally more reliable than their creators.


🚀Distributed Systems I have designed and open-sourced

  • emitter-io/emitter - high performance, distributed and low latency publish-subscribe platform
  • kelindar/talaria - distributed, highly available, and low latency time-series database for Presto

📦Golang Libraries I made to help me in building software faster or explore a certain idea

🧪Experiments in which I tried with various ideas

🎨Emitter Demos I have prepared for the project

  • chat - building a chat with emitter
  • actor - distributed actor model with emitter
  • client-server - how to create a client/server application with emitter
  • platformer - making an online platformer with emitter
  • retain - how to use message retention in emitter
  • share - how to use shared subscriptions in emitter
  • iss - tracking international space station in real-time
  • presence - demo of the channel presence for emitter

📚Blogs & Papers I have written in the past

  • Technical Blog - My random blog posts around experimentation, performance and open source
  • Ph.D Thesis - Supporting visual diagnosis of performance problems in multi-core and parallel software
  • SIGCHI'14 Paper - Design considerations for parallel performance tools
  • IEEE Journal Paper - Parallel Performance Problems on Shared-Memory Multicore Systems: Taxonomy and Observation

visitorsGitHub User's stars

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  1. emitter-io/emitteremitter-io/emitterPublic

    High performance, distributed and low latency publish-subscribe platform.

    Go 4k 355

  2. columncolumnPublic

    High-performance, columnar, in-memory store with bitmap indexing in Go

    Go 1.5k 63

  3. searchsearchPublic

    Go library for embedded vector search and semantic embeddings using llama.cpp

    Go 468 18

  4. eventeventPublic

    Simple internal event bus for Go applications

    Go 509 5

  5. bitmapbitmapPublic

    Simple dense bitmap index in Go with binary operators

    Assembly 341 25

  6. talariadb/talariatalariadb/talariaPublic

    TalariaDB is a distributed, highly available, and low latency time-series database for Presto

    Go 225 31


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