Jessica Thompson
Junior Research Fellow at University of Oxford
Oxford, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolJessica Thompson is a Junior Research Fellow and Postdoctoral Researcher at the University of Oxford with 14 years of experience at the intersection of cognitive neuroscience, machine learning, and auditory perception. She completed a PhD at Université de Montréal under supervisors connected to BRAMS and Mila, and her work combines computational modelling, ultra high-field neuroimaging, and behavioral experiments to probe human information processing. She has a strong engineering background from early roles at McGill building large-scale Java and Python systems and has contributed ML engineering improvements and unit tests to legacy pylearn2 code, notably making a convolutional Gaussian visualization layer robust to arbitrary axes ordering. Comfortable moving between lab, codebase, and classroom, she has held visiting and teaching positions in Maastricht and supervised undergraduate research projects. Her profile reflects a rare blend of rigorous experimental methods, practical software engineering, and music-technology fluency from graduate studies in digital musics.
14 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), Cognitive Science and Neuropsychology, Doctor of Philosophy (PhD), Cognitive Science and Neuropsychology at Université de MontréalM.A., Digital Musics, M.A., Digital Musics at Dartmouth CollegeB.A., Psychology, Computer Science, Music Technology, B.A., Psychology, Computer Science, Music Technology at McGill University
English, French
Github Skills (7)
neural-network10
unit-testing10
machine-learning10
convolutional-neural-networks10
python10
theano10
numpy9
Programming languages (3)
Github contributions (5)
lisa-lab/pylearn2
Mar 2014 - Mar 2014
Warning: This project does not have any current developer. See bellow.
Role in this project:
ML Engineer
ML EngineerContributions:9 commits in 4 days
Contributions summary:Jessica's contributions primarily involve the development and testing of the GaussianVisLayer within the `pylearn2` repository. They implemented functionality to handle arbitrary axes ordering in the convolutional GaussianVisLayer, enhancing its flexibility. Furthermore, the user added unit tests to verify the correctness of the GaussianVisLayer, including tests for both VectorSpace and Conv2DSpace, with and without arbitrary axes ordering. Finally the user provided methods to set the biases within the `GaussianVisLayer`.
javascripttypescript
thompsonj/ripples
Nov 2015 - Aug 2016
Contributions:12 commits, 11 pushes, 1 branch in 8 months
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