Mohiuddin Qader
Applied Researcher 3 Staff Software Engineer 2 at eBay
California, United States
Summary
👤
Senior🎓
Top SchoolMohiuddin Qader is an applied researcher and staff software engineer with 12 years of experience building massively scalable, consensus-backed storage and geo-distributed database platforms at eBay. He holds a PhD from UC Riverside where his thesis and research produced practical I/O and indexing optimizations for LSM-based big data stores, and he has a track record of turning those ideas into production systems like MonstorDB and a Paxos-based block-replication engine. Deeply experienced in Java and C/C++, he specializes in distributed replication, storage engine design, and cloud-native deployments on Kubernetes, with hands-on familiarity with Raft, PhxPaxos, LevelDB, AsterixDB, Lucene and Hadoop. Colleagues rely on him for architecture-level decisions informed by rigorous experimental evaluation, and he has repeatedly bridged academic research with shipping resilient, low-latency production storage. An interesting facet of his profile is that he’s moved multiple indexing and LSM-structure innovations from graduate projects into large-scale industrial platforms.
12 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (PhD) Computer Science, Doctor of Philosophy (PhD) Computer Science at University of California, RiversideBachelor of Science (B.Sc.) Computer Science and Engineering, Bachelor of Science (B.Sc.) Computer Science and Engineering at Bangladesh University of Engineering and Technology
English, Bengali
Github Skills (6)
lsm-tree8
state-machine8
key-value-store6
hybrid3
cpp1
microsoft-azure1
Programming languages (1)
Github contributions (5)
mohiuddin-shuvo/LevelDB_Eager
Aug 2014 - Oct 2017
Contributions:5 commits, 3 pushes in 3 years 2 months
mohiuddin-shuvo/LevelDB_Embedded-Secondary-Index
Feb 2014 - Jan 2015
Contributions:8 commits, 4 pushes in 11 months
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