akamaster
Summary
🤩
RockstarYerlan Idelbayev is an applied scientist with 11 years of experience specializing in machine learning research and model compression, currently based in Los Angeles. He has held applied science roles at AWS and Snap and completed internships at NVIDIA, Google, and Facebook, bringing both industry-scale production experience and deep research rigor. Yerlan earned a Ph.D. in Computer Science and an MS from UCSD, and his early academic work improved medical record classification using LSTMs, outperforming prior baselines. He blends research-driven innovation with hands-on engineering across cloud and ML systems, and has a track record of translating state-of-the-art models into deployable solutions. A detail that sets him apart is his combined teaching background and broad internship pedigree, which helps him communicate complex ideas to diverse technical audiences.
11 years of coding experience
Github Skills (26)
pytorch10
resnet10
bugtracking9
compression9
gpu8
mixture-of-experts8
model-compression8
constrained-optimization8
algorithm7
machine-learning7
inference7
data-parallelism7
deep-learning7
deepspeed7
acceleration5
Programming languages (2)
Github contributions (5)
akamaster/pytorch_resnet_cifar10
Oct 2018 - Jul 2021
Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.
Contributions:1 review, 10 commits, 3 PRs in 2 years 9 months
pytorchresnetresnet20resnet32resnet44
UCMerced-ML/LC-model-compression
Jul 2020 - Jul 2021
Model compression by constrained optimization, using the Learning-Compression (LC) algorithm
Contributions:10 commits, 12 pushes, 4 comments in 11 months
compressionconstrained-optimizationmodel-compression
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