Mathew Sam
Staff Machine Learning Engineer at Qualcomm
San Diego, California, United States
Summary
👤
Senior🎓
Top SchoolMathew Sam is a Staff Machine Learning Engineer based in San Diego with eight years of experience specializing in computer vision for automotive and XR applications. At Qualcomm he has driven practical, low-power solutions for optical flow and depth-from-stereo, blending classical methods with deep learning to improve edge alignment, visual quality, and latency. He believes in multi-task approaches and has implemented DL-based holefilling, speckle filtering, and sky-region detection to bolster real-world confidence metrics. His academic work includes using optical flow to analyze human movement for medical studies, showing a knack for translating research tools into clinical and industrial impact. Mathew combines strong engineering rigor with domain-focused innovation, optimizing algorithms specifically for on-chip performance in safety-critical applications.
8 years of coding experience
6 years of employment as a software developer
10th grade Science Social Science French Maths English, 10th grade Science Social Science French Maths English at The Asian School - BahrainUniversity of California, San DiegoHigher Secondary School Physics Chemistry C++ Mathematics English, Higher Secondary School Physics Chemistry C++ Mathematics English at New Millenium School-DPS BahrainEngineer’s Degree Electronics and Communications Engineering, Engineer’s Degree Electronics and Communications Engineering at National Institute of Technology Karnataka
English, French, Malayalam, Hindi
Github Skills (12)
convolutional-neural-networks6
audio5
source-separation4
denoising4
python3
speech-enhancement3
detectron2
object-detection2
speech2
pytorch2
bayesian1
instance-segmentation1
Programming languages (2)
Github contributions (5)
MathewSam/Wave-U-Net-For-Speech-Enhancement-1
Mar 2019 - Sep 2019
Improved speech enhancement with the Wave-U-Net, a deep convolutional neural network architecture for audio source separation, implemented for the task of speech enhancement in the time-domain.
Contributions:13 commits, 10 pushes, 1 comment in 6 months
audioconvolutional-neural-networkssource-separationspeech-enhancement
eseetao/Super-Resolution
Feb 2022 - Mar 2022
Contributions:31 PRs, 15 pushes in 20 days
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