Saba Aflaki
Software Engineer L3 at Reddit, Inc.
Canada
Summary
👤
Senior🎓
Top SchoolSaba Aflaki is a Software Engineer L3 with 10 years of experience building high-performance data and backend systems for programmatic advertising and real-time services. He has driven end-to-end design and optimization of billing and reporting pipelines using Scala, Spark, Hadoop and Go, and has hands-on experience modernizing and stabilizing real-time auction infrastructure at Index Exchange. A Waterloo MCS graduate with a strong hardware background from Sharif University, he blends rigorous academic research—authoring four papers including an IEEE RDS best paper—with pragmatic production engineering. Now at Reddit, he brings deep observability, performance-tuning, and distributed-systems skills to large-scale data platforms while valuing collaborative, diverse teams. An under-the-radar strength is his cross-domain robotics and EKF experience, which informs his careful approach to systems correctness and sensing of failure modes.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Science (BSc) Computer Hardware Engineering, Bachelor of Science (BSc) Computer Hardware Engineering at Sharif University of TechnologyMaster's degree Computer Science, Master's degree Computer Science at University of Waterloo
Github Skills (8)
multi-camera10
extrinsic-parameters10
localization8
ros-node8
slam8
3d7
ros-driver4
usb3
Programming languages (1)
Github contributions (5)
wavelab/mcptam
Jul 2016 - Dec 2016
MCPTAM is a set of ROS nodes for running Real-time 3D Visual Simultaneous Localization and Mapping (SLAM) using Multi-Camera Clusters. It includes tools for calibrating both the intrinsic and extrinsic parameters of the individual cameras within the rigid camera rig.
Contributions:12 commits, 4 PRs, 29 pushes in 5 months
3dextrinsic-parameterslocalizationmulti-cameraros-node
aharmat/mcptam
May 2016 - Mar 2017
MCPTAM is a set of ROS nodes for running Real-time 3D Visual Simultaneous Localization and Mapping (SLAM) using Multi-Camera Clusters. It includes tools for calibrating both the intrinsic and extrinsic parameters of the individual cameras within the rigid camera rig.
Contributions:4 PRs in 10 months
3dextrinsic-parameterslocalizationmulti-cameraros-node
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