Riley Dehaan
Doctoral Student at Computational Memory Lab - University of Pennsylvania
Philadelphia, Pennsylvania, United States
Summary
🤩
Rockstar🎓
Top SchoolRiley Dehaan is a doctoral student in psychology at the University of Pennsylvania who bridges translational neurotechnology, human memory research, and computational neuroscience with nine years of interdisciplinary experience. He investigates how direct current stimulation and intracranial EEG can modulate memory, while bringing practical machine learning and engineering skills from a Stanford MS and prior roles in deep learning for cybersecurity, robotics, and sensors. Riley has experience shipping reliable code quality practices—adding unit tests and pre-push hooks—to open-source forecasting tooling, and he’s the kind of researcher who pairs hands-on prototyping with careful experimental design. Comfortable moving between lab, cloud, and hardware, he’s open to summer internships that align with brain–machine interface and neuromodulation work.
9 years of coding experience
3 years of employment as a software developer
Master of Science, Electrical Engineering (emphasis in machine learning and software development), Master of Science, Electrical Engineering (emphasis in machine learning and software development) at Stanford UniversityBachelor's of Science in Electrical and Computer Engineering, Mechanical Engineering, Bachelor's of Science in Electrical and Computer Engineering, Mechanical Engineering at Baylor UniversityTimothy Christian High School, Class of 2014Ph.D., PSYCHOLOGY, Ph.D., PSYCHOLOGY at University of Pennsylvania
Github Skills (11)
unit-testing10
test-framework10
python10
unit-test10
testing10
forecast9
time-series9
forecasting9
machine-learning8
neural-network8
pytorch7
Programming languages (5)
Github contributions (5)
ourownstory/neural_prophet
Sep 2020 - Nov 2021
NeuralProphet: A simple forecasting package
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:19 commits, 1 PR, 9 pushes in 1 year 2 months
Contributions summary:Riley's primary contribution involves incorporating a unit testing framework and implementing pre-push Git hooks for running tests. They added test cases within `test_debug.py` to validate functionalities. Modifications to `setup.py` indicate efforts to integrate testing into the development workflow and ensure code quality through automated checks before code commits. The user is focused on improving the reliability of the software through testing.
forecastingneuralprophetpythonforecasttime-series
Riley16/scot
Feb 2019 - Mar 2019
Set Cover Optimal Teaching for Sequential Decision Making with Inverse Reinforcement Learning
Contributions:36 commits, 12 PRs, 26 pushes in 1 month
decision-makingdecisionteachingreinforcement-learninginverse-reinforcement-learning
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