Mohammed Innat
AI Software Engineer, ML Research at CHOWA GIKEN Corporation
Dhaka, Dhaka Division, Bangladesh
Summary
👤
Senior🎓
Top SchoolMohammed Innat is an AI software engineer and ML researcher with a decade of hands-on experience building and scaling computer vision, multimodal, and LLM systems from prototype to production. Based in Dhaka, he has delivered generative AI and CV solutions at CHOWA GIKEN and Venturas, including large-scale semi‑automated labeling pipelines for millions of images and a siamese-network counterfeit detection system. He contributes to industry tooling—adding augmentation layers like GridMask and RGBShift to the popular KerasCV project—and routinely optimizes models for deployment using ONNX, TensorRT, quantization and pruning. A Kaggle Master with strong demonstrated competition and code contributions, he translates cutting‑edge research into tested, documented code and presents findings to both technical and non‑technical audiences.
10 years of coding experience
3 years of employment as a software developer
Bachelor’s Degree Electronics and Communications Engineering, Bachelor’s Degree Electronics and Communications Engineering at Khulna University of Engineering and TechnologyHigher Secondary Certificate | GPA 5.00 Science, Higher Secondary Certificate | GPA 5.00 Science at Savar University College
English, Bangla, Hindi, French
Stackoverflow
16,812reputation
6.8mreached
392answers
17questions
neural-network
top-5%
tensorflow
top-1%
python
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deep-learning
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machine-learning
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keras
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Github Skills (16)
keras10
computer-vision10
machine-learning10
image-augmentation10
deep-learning10
tensorflow10
python10
neural-network9
pytorch9
markdown6
opencv6
transfer-learning6
loss-functions6
plot6
github6
Programming languages (10)
Github contributions (5)
keras-team/keras-cv
Feb 2022 - Apr 2022
Industry-strength Computer Vision workflows with Keras
Role in this project:
ML Engineer
ML EngineerContributions:202 reviews, 5 commits, 13 PRs in 2 months
Contributions summary:Mohammed primarily contributed to the development of KerasCV preprocessing layers, focusing on computer vision tasks. Their work involved implementing new layers such as `GridMask`, `Grayscale`, `ChannelShuffle`, and `RGBShift`, including writing tests and demo examples. The user demonstrated expertise in modifying existing code and adding new features and functionality related to image augmentation techniques within the KerasCV framework.
visiondeep-learningcomputer-visionindustrystrength
innat/VideoSwin
Oct 2023 - Mar 2025
Keras Implementation of Video Swin Transformers for 3D Video Modeling
Contributions:1 release, 2 PRs, 95 pushes in 1 year 5 months
kerastensorflowtorchvideo-classificationvideo-dataset
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