Jesse Livezey
Senior Applied Machine Learning Scientist at Dandelion Science Corp
Jersey City, New Jersey, United States
Summary
🤩
Rockstar🎓
Top SchoolJesse Livezey is a Senior Applied Machine Learning Scientist with 13 years of experience bridging physics, computational neuroscience, and machine learning to extract interpretable structure from large neural datasets. He designs and implements reproducible Python tooling—ranging from neural data standardization and signal-processing libraries to HPC workflows—and has led lab-wide software efforts at Berkeley Lab and Dandelion Science. His research produced methods like Dynamical Components Analysis and novel null models for sensory processing, with a track record of mentoring students and improving research software practices. An active open-source contributor, Jesse has improved performance and tests in cornerstone projects such as Theano/PyTensor and SciPy and helped maintain educational content for NeuromatchAcademy. Based in Jersey City, he combines a PhD-trained theoretical perspective with pragmatic engineering, often surfacing subtle statistical insights that make neural models more predictive of behavior.
12 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Biophysics, Theoretical Neuroscience, Machine Learning, Doctor of Philosophy - PhD, Physics, Biophysics, Theoretical Neuroscience, Machine Learning at University of California, BerkeleyB.A., Physics, Mathematics, B.A., Physics, Mathematics at Cornell University
English
Github Skills (20)
scipy10
benchmark10
python10
testing10
machine-learning10
benchmarking10
blas10
numpy10
performance-testing10
jupyter-notebook10
theano10
documentation10
test-automation10
tensorflow9
linear-algebra9
Programming languages (3)
Github contributions (5)
NeuromatchAcademy/course-content
Jun 2020 - Aug 2020
NMA Computational Neuroscience course
Role in this project:
Technical Writer
Technical WriterContributions:17 commits, 13 PRs, 64 pushes in 1 month
Contributions summary:Jesse's commits primarily involve processing and integrating tutorial notebooks within the neuromatchacademy/course-content repository. The commits focus on ensuring the correct display and functionality of the notebooks within the course structure, indicated by the "Process tutorial notebooks" commit messages. This suggests a role focused on the creation, maintenance, and presentation of course content, likely involving both technical and organizational aspects of the learning materials. The edits and the references to "CI fixes" suggest the user also participated in the integration process with the repository's automated testing and deployment.
neurosciencedynamic-systemspythoncomputational-neurosciencemachine-learning
Theano/Theano
Jul 2015 - Oct 2016
Theano was a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It is being continued as PyTensor: www.github.com/pymc-devs/pytensor
Role in this project:ML Engineer
ML EngineerContributions:14 commits, 8 PRs, 116 comments in 1 year 3 months
Contributions summary:Jesse contributed to the performance testing of the gemm function within the Theano library, focusing on different hardware configurations and CUDA versions. They added larger matrix sizes to the `check_blas.py` script for benchmarking, subsequently removing CUDA-specific information. Furthermore, they modified the code to optimize the CorrMM function within the Theano library, and fixed test failures related to the CorrMM functions, which demonstrated focus on optimizing core functionalities within the library.
python-librarymathmulti-dimensionalpythonevaluate
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