Daniel Maturana
Chief ML Scientist at Gather AI
Pittsburgh, Pennsylvania, United States
Summary
👤
Senior🎓
Top SchoolDaniel Maturana is Chief ML Scientist at Gather AI, bringing 16 years of experience in computer perception and machine learning for robotics and leading the startup’s drone-based warehouse inventory solutions. He holds a PhD in Robotics from Carnegie Mellon and has a strong research pedigree (Google Scholar) combined with hands-on engineering—contributions to projects like Lasagne and a Python PCD I/O library show he moves between deep learning frameworks and practical point-cloud tooling. Previously CTO of Gather AI and a long-term CMU researcher, he bridges academic rigor with product-focused deployment of ML systems in real-world robotic settings. Based in Pittsburgh, he’s as comfortable designing GPU-accelerated neural layers as refactoring backend libraries and adding test suites, reflecting a rare mix of research depth and production craftsmanship.
16 years of coding experience
8 years of employment as a software developer
Visiting student, Computer science, Visiting student, Computer science at Massachusetts Institute of TechnologyPontificia Universidad Católica de ChileExchange, Computer science, Exchange, Computer science at Georgia Institute of TechnologyDoctor of Philosophy (Ph.D.), Robotics, Doctor of Philosophy (Ph.D.), Robotics at Carnegie Mellon University
Stackoverflow
11reputation
495reached
1answer
0questions
Github Skills (16)
neural-network10
file-processing10
file-handling10
deep-learning10
file-access10
python10
cudnn10
fileio10
theano10
numpy10
data-structure9
machine-learning9
convolutional-neural-networks9
data-structures9
bitwise-operators6
Programming languages (10)
Github contributions (5)
dimatura/pypcd
Mar 2013 - Mar 2018
PCL pcd fileformat i/o in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 52 commits, 7 PRs in 5 years
Contributions summary:Daniel primarily focused on developing the core functionality of the Python package for Point Cloud Data (PCD) files. They added features for writing PCD files, including header creation and data formatting. They implemented methods for adding fields, concatenating, and copying point clouds. Furthermore, the user refactored the code, including moving script-related code into a main function, and added comments and a basic test suite.
deltapcdpythonpclfileformat
Lasagne/Lasagne
Sep 2014 - Mar 2015
Lightweight library to build and train neural networks in Theano
Role in this project:ML Engineer
ML EngineerContributions:30 commits, 3 PRs, 46 comments in 5 months
Contributions summary:Daniel primarily contributed to the `lasagne/lasagne` repository, a library for building neural networks in Theano. Their work focused on fixing typos, swapping variable names related to spatial layers, and adding and updating layers to utilize cuDNN, a library for deep neural networks. These changes involved modifications to core layer implementations and example code, demonstrating a focus on improving functionality and integration with GPU acceleration.
pythondeep-learningtheanoneural-networksdeep-learning-library
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