David Romero
Research Scientist at Cartesia
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolDavid Romero is a research scientist based in San Francisco with eight years of experience at the intersection of efficient deep learning and applied computer vision. He holds a cum laude PhD in Efficient Deep Learning from VU Amsterdam and has transitioned research into industry roles at NVIDIA, Google Research, Qualcomm, and now Cartesia AI. His background spans production-focused vision systems (from microscopy automation to device control) and cutting-edge model efficiency research, giving him a rare mix of hardware-aware engineering and academic rigor. Colleagues value his ability to move ideas from prototype to deployable systems, informed by hands-on experience in C++, Python, LabVIEW, and embedded communication protocols. Notably, his career blends classical signal-processing roots from mechatronics with modern ML research, enabling practical, resource-efficient solutions for real-world AI deployments.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science (5 Years degree) Mechatronic Engineering, Bachelor of Science (5 Years degree) Mechatronic Engineering at Universidad Nacional de ColombiaDoctor of Philosophy - PhD (cum laude) Efficient Deep Learning, Doctor of Philosophy - PhD (cum laude) Efficient Deep Learning at Vrije Universiteit Amsterdam (VU Amsterdam)Master of Science Computational Engineering Sciences, Master of Science Computational Engineering Sciences at Technische Universität BerlinExchange program - Bachelor of Science (4th year) Mechatronic Engineering, Exchange program - Bachelor of Science (4th year) Mechatronic Engineering at Leibniz Universität Hannover
Spanish, English, German, Dutch
Stackoverflow
95reputation
4kreached
5answers
8questions
Github Skills (66)
arxiv10
convolutional-neural-networks9
sequential9
resnet8
r8
hugo-theme8
rstudio8
pytorch8
page-builder8
rmarkdown8
open-science8
netlify8
hugo7
deep-learning7
forestry7
Programming languages (3)
Github contributions (5)
dwromero/ckconv
Feb 2021 - Nov 2021
Code repository of the paper "CKConv: Continuous Kernel Convolution For Sequential Data" published at ICLR 2022. https://arxiv.org/abs/2102.02611
Contributions:26 commits, 2 PRs, 16 pushes in 9 months
kerneliclrarxivkernel-convolutionabs
dwromero/titanic-excercise
Apr 2021 - Nov 2023
Contributions:3 pushes, 1 branch in 2 years 7 months
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