Mohammad Kamani
Senior AI ML Researcher at NVIDIA
Kirkland, Washington, United States
Summary
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Senior🎓
Top SchoolMohammad Kamani is a Senior AI/ML Researcher with a Ph.D. from Penn State and eight years of experience designing efficient algorithms for federated learning, distributed optimization, model compression, and Edge AI. He has transitioned research breakthroughs into industry impact across roles at Wyze, AMD, and now NVIDIA, focusing on resource-constrained inference and training for real-world systems. His academic work introduced novel multi-objective optimization methods for bias mitigation—Targeted Data-driven Regularization and Pareto Descent Optimization—that outperform prior approaches and generalize beyond fairness tasks. Mohammad combines deep theoretical expertise with applied engineering, routinely tackling domain adaptation, imbalanced and robust learning, and knowledge distillation in production settings. Based in Kirkland, WA, he is known for bridging collaborations between research and product teams to deliver high-quality, deployable ML solutions. An uncommon strength is his track record of turning provable optimization ideas into compact models suited for edge devices.
8 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Information Sciences and Technology, Doctor of Philosophy - PhD, Information Sciences and Technology at Penn State UniversityMaster's degree, Electrical, Electronics and Communications Engineering, Master's degree, Electrical, Electronics and Communications Engineering at Sharif University of Technology
English, Persian
Github Skills (65)
python10
deep-learning10
shape-context10
chatgpt10
fuzzy-logic10
ai10
generative-ai10
neural-network10
transformer10
skeleton10
gpt10
llama10
typescript10
matching10
amd10
Programming languages (4)
Github contributions (5)
mmkamani7/SkeletonMatching
Nov 2017 - Dec 2020
This repository implements skeleton matching algorithm.
Contributions:12 commits, 2 pushes, 1 branch in 3 years 2 months
skeletonizationskeletonmatchingmatching-algorithmshape-matching
MLOPTPSU/FedTorch
Oct 2020 - Jul 2021
FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.
Contributions:2 releases, 57 commits, 2 PRs in 8 months
benchmarkingpytorchfederated-learningdistributed-optimizationdistributed
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