John Ehrlinger
Assistant Staff - Lead Data Scientist - Cardiovascular Outcomes Registry And Research
Cleveland, Ohio, United States
Summary
🤩
Rockstar🎓
Top SchoolJohn Ehrlinger is a seasoned data and applied scientist with 14 years of experience building production-grade ML and statistical solutions across healthcare, engineering, and government sectors. Currently leading data engineers and biostatisticians at Cleveland Clinic's Cardiovascular Outcomes Registry, he combines deep expertise in survival analysis, time series forecasting, predictive maintenance, geospatial satellite time series, and computer vision to drive outcome-focused research. He has a rare technical blend—PhD-level statistics, an MS/BS in mechanical/aerospace engineering, and early-career CFD/aerodynamics software development—that informs principled modeling and robust system design. A proven technical lead and mentor, John has shaped MLOps and CI/CD practices at Microsoft and Altamira and contributed to prominent open-source computer vision recipes used for model training and webcam integration. He emphasizes interpretable, responsible AI in production pipelines and authors R packages to streamline reproducible analysis for clinical research.
14 years of coding experience
14 years of employment as a software developer
Ph.D Statistics, Ph.D Statistics at Case Western Reserve University
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (11)
computer-vision10
jupyter-notebook10
python10
image-classification10
deeplearning-ai9
machine-learning9
deep-learning9
resnet8
user-manual7
tensorflow6
image-processing6
Programming languages (9)
Github contributions (5)
microsoft/computervision-recipes
Apr 2019 - Oct 2022
Best Practices, code samples, and documentation for Computer Vision.
Role in this project:
Data Scientist
Data ScientistContributions:3 reviews, 27 commits, 3 PRs in 3 years 6 months
Contributions summary:John primarily contributed to the development and modification of Jupyter Notebooks focused on image classification and training models within the computer vision domain. Their work involved updating notebook content, correcting code, and incorporating techniques related to pretrained models and webcam integration. They demonstrate an understanding of fast.ai, ResNet, and other related libraries and concepts. Their contributions support building and understanding computer vision models.
pythonjupyter-notebookoperationalizationimage-classificationmicrosoft
ehrlinger/PySpark-Predictive-Maintenance
May 2017 - Feb 2023
Contributions:2 pushes in 5 years 10 months
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