Pradeep Krishnamurthy
Uppsala, Uppsala County, Sweden
Summary
🤩
Rockstar🎓
Top SchoolPradeep Krishnamurthy is a computational neuroscientist-turned-software engineer with seven years of industry experience building computer vision and AI systems for automotive, imaging, and assistive-app domains. His background spans postdoctoral neuroscience research and large-scale brain simulations to hands-on CV/ML engineering at companies like Scania, Qualcomm, and Teledyne FLIR, translating neural-data expertise into production-ready models. He has contributed to core back-end data tooling such as the h2oai/datatable project, fixing nuanced numerical and sorting bugs that reveal a deep understanding of data manipulation internals. Comfortable in C++ and Python, Pradeep has applied ML to calcium-imaging analysis, autism-focused apps, recommender systems, and self-driving stacks, often bridging research rigor with practical deployment. Based in Uppsala, he combines a rare mix of neuromorphic research pedigree and pragmatic engineering that helps move cutting-edge models from lab prototypes into robust products.
7 years of coding experience
7 years of employment as a software developer
Post doctoral Neuroscience, Post doctoral Neuroscience at The University of Edinburgh
Tamil, Hindi, English, Swedish
Github Skills (12)
data-structures10
numerics10
numerical10
computation10
numeric10
python10
data-structure10
data-analysis10
pytest9
testing9
performance-monitor9
performance-analysis9
Programming languages (6)
Github contributions (5)
h2oai/datatable
Sep 2020 - Dec 2021
Role in this project:
Back-end Developer
Back-end DeveloperContributions:52 reviews, 25 commits, 17 PRs in 1 year 3 months
Contributions summary:Pradeep primarily contributed to the `datatable` Python package, focusing on improving its core functionality and fixing bugs related to numerical operations. Their commits addressed issues like handling division by zero, promoting data types for specific operators, and ensuring the correct behavior of sorting functions, including the handling of NA values and reverse sorting. These changes involved modifying test files and core code files, indicating a deep understanding of the package's internal workings and a focus on data manipulation logic.
data-analysispythonftrltabular-datadimensional
pradkrish/igraph
Nov 2021 - Dec 2022
Library for the analysis of networks
Contributions:38 pushes, 5 branches in 1 year
networksocial-network-analysisnetwork-graphnetwork-analysis
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