Alfeo Sabay
Founder CEO at MLPIPES
Plainfield, Illinois, United States
Summary
👤
Senior🎓
Top SchoolAlfeo Sabay is a founder and CEO with nine years of focused experience building ML-driven products and multi-agent AI systems, currently leading MLPipes LLC to deliver HIPAA-compliant healthcare solutions and automated operational workflows. He blends strategic product leadership from roles at IBM and Nokia with hands-on data science—MS in Data Science from SMU—and a track record of shipping cloud-native ML systems on AWS. His background spans technical product management, revenue-driving product globalization, and building production ML and BI pipelines using Spark, Python, and modern data stores. At CEEC he designed traffic forecasting and emergency vehicle path optimization models, demonstrating a knack for turning complex real-world problems into deployable systems. Known for marrying cross-functional collaboration with technical execution, he often architected solutions as ensembles of cooperating agents rather than single models. Based in Plainfield, IL, he combines enterprise product rigor with startup agility and a focus on compliance and operational automation.
9 years of coding experience
23 years of employment as a software developer
Business Administration and Management, General, Business Administration and Management, General at The University of Texas at El PasoBachelor of Science - BS, Engineering Technology, Bachelor of Science - BS, Engineering Technology at DeVry University PhoenixMaster’s Degree, Data Science, 3.9/4.0, Master’s Degree, Data Science, 3.9/4.0 at Southern Methodist University
English, Spanish
Stackoverflow
19reputation
13kreached
3answers
1question
Github Skills (28)
unet-image-segmentation8
in-progress7
apply7
partial7
truffle6
cryptocurrency6
arules6
mri6
anaconda6
ethereum6
go-ethereum6
rstudio6
r6
macos-sierra6
classification5
Programming languages (3)
Github contributions (5)
alsabay/CNN-BrainTumorDetection
Dec 2019 - Apr 2022
Experimental Deep Learning Brain Tumor MRI Detection and Classification Project. This is work in progress. Uses Image Pre-processing to hightlight features. Train and test 3 types (VGG14, InceptionV3, ResNet50) of Convolutional Neural Network Architectures and assess accuracy metrics of each type. New Section will apply CSPNet (Cross Stage Partial Networks, Jun-Wei Hsieh et. al.) to same Brain Tumor Data.
Contributions:12 commits, 7 PRs, 15 pushes in 2 years 4 months
brainunet-image-segmentationtensorflowclassificationinceptionv3
alsabay/HeartDiseasePrediction
Mar 2018 - Dec 2019
Contributions:10 pushes, 1 branch in 1 year 9 months
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