Antoni Martin
Medford, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolAntoni Martin is a research-driven software engineer and PhD candidate at Texas A&M with 11 years of experience bridging aerospace engineering and machine learning. He has held research and engineering roles at IBM, Meta, Columbia University, and NASA JPL, applying advanced ML and backend systems to scientific and industrial problems. At IBM he progressed from Research Scientist to Staff Research Scientist, reflecting rapid impact and leadership in applied research. Antoni contributes to flagship open-source ML infrastructure—implementing NestedTensor features in PyTorch—to improve efficiency and irregular-data handling on GPU. His background uniquely combines aerospace PhD training with production-level ML engineering, enabling him to translate complex research into deployable systems. Based in Medford, MA, he also teaches and mentors, bringing academic rigor to industrial-scale AI development.
11 years of coding experience
7 years of employment as a software developer
Summer School, Business, Summer School, Business at IESE Business SchoolDoctor of Philosophy - PhD, Aerospace, Aeronautical and Astronautical Engineering, Doctor of Philosophy - PhD, Aerospace, Aeronautical and Astronautical Engineering at Texas A&M UniversityUPC Universitat Politècnica de CatalunyaCFIS, Engineering, CFIS, Engineering at CFIS-UPCBatxillerat, Tecnològic, Batxillerat, Tecnològic at INS Pius Font i Quer
English, Spanish, Catalan, French
Stackoverflow
11reputation
0reached
1answer
0questions
Github Skills (17)
pytorch10
python10
operation10
tensorrt10
gpu-programming10
machine-learning10
deep-learning10
tensorflow10
neural-network10
tensor10
c-language9
autograd9
cprogramming-language9
cuda9
testing8
Programming languages (9)
Github contributions (5)
pytorch/pytorch
Oct 2022 - Nov 2022
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:90 reviews, 6 commits, 25 PRs in 1 month
Contributions summary:Antoni contributed to the PyTorch library by implementing and generalizing layer normalization for nested tensors, ensuring the correctness of the implementation with unit tests. They added support for the `.to()` method, which allows moving NestedTensors between CPU and GPU, by implementing `empty_like()`, and implemented `copy_`, `fill_`, and `ones_like` for Nested Tensors backends, and a constructor for nested_tensor that is similar to torch.tensor(). Furthermore, they implemented a function to select elements in the irregular dimensions, which enhances functionality. They also added a unit test to check for negative arange issues and added an embedding op to jagged NT.
pythongpu-accelerationdeep-learninggpunumpy
seakers/daphne-interface
May 2017 - Aug 2022
Contributions:1 release, 3 PRs, 268 pushes in 5 years 3 months
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