Jayanth Koushik
Postdoctoral Researcher at Carnegie Mellon University
Pittsburgh, Pennsylvania, United States
Summary
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Senior🎓
Top SchoolJayanth Koushik is a Postdoctoral Researcher at Carnegie Mellon University with 12 years of experience at the intersection of vision science, computational neuroscience, and machine learning, focusing on object categorization and classification. He holds a PhD in Computational Neuroscience and Machine Learning and an MS in Computational Data Science from CMU, building deep domain expertise in both theory and applied modeling. Prior industry experience as a software engineer at Directi and hands-on contributions to the well-known SheffieldML/GPy Gaussian processes library—where he strengthened cross-platform testing and Cython integration—underscore his attention to robust, reproducible code. Based in Pittsburgh, he blends rigorous research with practical engineering, often improving reliability and test infrastructure in open-source projects as a quietly influential contributor.
12 years of coding experience
1 year of employment as a software developer
BITS Pilani, Birla Institute of Technology and ScienceDoctor of Philosophy - PhD, Computational Neuroscience and Machine Learning, Doctor of Philosophy - PhD, Computational Neuroscience and Machine Learning at Carnegie Mellon University
Github Skills (8)
unit-testing10
gpy10
python10
cython10
testing10
kernel-methods9
numpy8
machine-learning7
Programming languages (9)
Github contributions (5)
SheffieldML/GPy
Oct 2017 - Feb 2018
Gaussian processes framework in python
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits, 1 PR, 13 comments in 3 months
Contributions summary:Jayanth primarily focused on improving the testing infrastructure of the GPy library. They fixed issues related to Cython module imports, ensuring consistent behavior across different operating systems. The contributions include adding and modifying tests, particularly for the coregionalize and other kernel functionalities, and refactoring test configurations. These changes aimed to enhance the reliability and robustness of the library by ensuring its components worked correctly with and without Cython acceleration.
gaussiangaussian-processespython
jayanthkoushik/sgd-feedback
Sep 2016 - Dec 2018
Contributions:82 commits, 27 pushes, 4 comments in 2 years 3 months
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