Jaiyam Sharma
Senior System Software Engineer at NVIDIA
Koto, Japan
Summary
👤
Senior🎓
Top SchoolJaiyam Sharma is a Senior System Software Engineer with 11 years of cross-disciplinary experience building embedded AI and robotics systems, currently focused on performance and safety for NVIDIA DRIVE. He holds a PhD from The University of Electro-Communications and a B.Tech from IIT Delhi, and his academic work on semiconductor sensors for medical diagnostics yielded a Japanese patent and peer-reviewed publications. Jaiyam has shipped perception and Tegra-related software across commercial robotics products at Yanmar and Rapyuta and contributed style-transfer and ResNet18-based training code to popular open-source CV resources. Based in Koto, Japan, he blends deep research experience with hands-on systems engineering and blogs openly about his work, signaling a commitment to community-driven tooling beyond his day job.
11 years of coding experience
6 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at The University of Electro-CommunicationsMaster’s Degree, Electrical and Electronics Engineering, Master’s Degree, Electrical and Electronics Engineering at Toyohashi University of Technology
English, French, Japanese, Hindi
Stackoverflow
121reputation
13kreached
4answers
3questions
Github Skills (17)
pytorch10
opencv10
python10
machine-learning10
style-transfer10
deep-learning10
deep-neural-networks10
neural-network10
computer-vision10
faster-rcnn9
mask-rcnn9
ethernet6
linear-algebra6
video-processing6
linux6
Programming languages (9)
Github contributions (5)
spmallick/learnopencv
Sep 2021 - Jan 2023
Learn OpenCV : C++ and Python Examples
Role in this project:
ML Engineer
ML EngineerContributions:13 commits, 9 PRs in 1 year 3 months
Contributions summary:Jaiyam contributed code related to style transfer, including the implementation of a StyleNetwork using PyTorch. The work involved defining convolutional and deconvolutional layers, building a depthwise separable module, and implementing style and content loss functions. Furthermore, the user set up a StyleTrainer class to train the style transfer model, leveraging a loss network based on ResNet18 architecture.
opencv-librarypythondeep-learningopencv3computer-vision
dataplayer12/shavenet
Oct 2018 - Oct 2019
Predict when you last shaved with machine learning
Contributions:14 commits, 8 PRs, 8 pushes in 1 year
shavepythondeep-learningmachine-learningpredict
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