AIgen
Machine Learning Engineer
Pittsburgh, Pennsylvania, United States
Summary
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RockstarMachine Learning Engineer with 8 years of experience based in Pittsburgh and currently a graduate student at Carnegie Mellon University's Machine Learning Department. Specializes in deploying and optimizing ML for resource-constrained edge devices, demonstrated by contributions to Microsoft Research’s widely used EdgeML repository where they implemented core ProtoNN functions and a BTLS optimization to boost model accuracy. Experienced in both low-level algorithm implementation and project documentation, balancing rigorous code changes with clear README and maintenance work. Comfortable bridging research and production, translating academic methods into practical, efficient implementations for real-world hardware. Known for attention to numerical detail and for improving model performance in constrained environments.
8 years of coding experience
Github Skills (5)
pytorch10
machine-learning10
cpp10
deeplearning-ai9
deep-learning9
Programming languages (4)
Github contributions (5)
microsoft/EdgeML
Sep 2017 - Jun 2018
This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.
Role in this project:
ML Engineer
ML EngineerContributions:21 commits, 2 PRs, 13 pushes in 9 months
Contributions summary:AIgen primarily contributed to the `microsoft/edgeml` repository, which focuses on machine learning for edge devices. Their commits involve modifications to the `src/ProtoNN/ProtoNNFunctions.cpp` file, which likely implements core machine learning algorithms. The user also updated and fixed bugs in the README files, indicating their role in maintaining and documenting the project. These actions include the implementation of a BTLS optimization which is used to test and improve model accuracy in the context of machine learning.
classifieredge-machine-learningsensortensorflowmicrosoft
AIgen/QOOB
May 2020 - Mar 2021
Contributions:16 commits, 20 pushes, 1 branch in 10 months
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