Eben Olson
Senior Software Engineer at Presco Engineering
New Haven, Connecticut, United States
Summary
🤩
Rockstar🎓
Top SchoolEben Olson is a Senior Software Engineer in New Haven with 15 years of experience blending academic rigor and production engineering across machine learning and backend systems. He holds a Ph.D. in Engineering from Yale and has transitioned research-grade expertise from Yale School of Medicine into leadership roles, including Engineering Lead at Applikate and his current role at Presco Engineering. Eben is an active contributor to the Lasagne deep learning ecosystem, where he improved convolutional layer correctness, added unit tests, and converted Caffe models to practical examples—work that highlights both low-level numerical care and reproducible ML workflows. He combines hands-on bug fixes and test automation with an ability to translate complex models into usable examples for practitioners. Colleagues describe him as a meticulous problem solver who prefers strengthening foundations (layers, shapes, tests) over flashy demos, making systems more reliable in the long run.
15 years of coding experience
8 years of employment as a software developer
California Institute of TechnologyDoctor of Philosophy (Ph.D.), Engineering, Doctor of Philosophy (Ph.D.), Engineering at Yale School of Engineering & Applied Science
Github Skills (14)
neural-network10
testing10
machine-learning10
jupyter-notebook10
convolutional-neural-networks10
caffe10
model-conversion10
python10
theano10
image-classification10
lasagne10
pytest9
unit-test9
unit-testing9
Programming languages (11)
Github contributions (5)
Lasagne/Recipes
Jul 2015 - Mar 2019
Lasagne recipes: examples, IPython notebooks, ...
Role in this project:
ML Engineer
ML EngineerContributions:44 commits, 40 PRs, 31 pushes in 3 years 8 months
Contributions summary:Eben primarily contributes by adding and updating example notebooks demonstrating the use of pre-trained convolutional neural networks (CNNs) for image classification tasks. The commits involve converting models from Caffe's Model Zoo, such as the NIN and VGG-CNN-S models, for use within the Lasagne framework. The user also updates the CIFAR example, refining layer configurations and pooling strategies, and incorporating Inception-V3.
ipythonlasagne
Lasagne/Lasagne
Feb 2015 - Feb 2016
Lightweight library to build and train neural networks in Theano
Role in this project:Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:66 commits, 29 PRs, 371 comments in 1 year
Contributions summary:Eben primarily focused on improving the `lasagne/lasagne` library's convolutional neural network (CNN) capabilities. They addressed several bug fixes related to convolutional layer calculations, particularly concerning output shape and border modes (`valid`, `full`, and `same`). The user also added unit tests, demonstrating a commitment to code quality and verification of the implemented changes. Additionally, they updated and fixed tests, providing coverage for various configurations, including handling None values in input shapes and addressing issues with strided convolutions.
neural-networktheanodeep-learning-libraryneural-networkspython
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