David Quintana is a postdoctoral researcher and embedded systems specialist with a decade of experience focused on domain-specific accelerators for resource-constrained platforms. Based at EPFL’s Embedded Systems Lab after a PhD at Universidad Complutense de Madrid and an MSc from KTH, he bridges academic research and practical acceleration techniques for deep neural networks. His trajectory includes visiting researcher roles and hands-on industry experience building automation modules at Indra, demonstrating fluency across hardware-aware software and system integration. Collected expertise in computer architecture, embedded ML acceleration, and teaching punctuates a profile that combines rigorous theory with applied engineering. Notably, his work blends cross-country research exposure between Spain and Switzerland, reflecting both collaborative breadth and a bent for translating research prototypes into deployable accelerator solutions.
10 years of coding experience
1 year of employment as a software developer
KTH Royal Institute of Technology
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at Universidad Complutense de Madrid
Contributions:19 pushes, 1 branch in 3 years 11 months
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