Farshid Varno
Senior Staff Engineer at d-Matrix
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolFarshid Varno is a Senior Staff Engineer based in San Francisco with over 8 years of industry experience and a 15-year background combining academic research and hands-on hardware design. He specializes in AI-hardware co-design, developing custom AI kernels, non-linear approximators, and FPGA-based telecommunication modules while optimizing hardware-software integration for high-performance AI systems. His research has driven state-of-the-art Federated and Transfer Learning methods, resulted in a filed patent, and produced practical tooling like the FedSim federated learning simulator. At companies from Imagia to Rain and now d-Matrix he has bridged R&D and production, shipping kernel-level improvements and accelerator innovations. Farshid pairs deep FPGA/VHDL expertise (TDM switches, AES modules, Cyclone/Virtex platforms) with modern ML deployment experience across edge and distributed settings. He is passionate about leading technical teams that translate cutting-edge research into deployable AI-hardware solutions.
8 years of coding experience
9 years of employment as a software developer
DLRL Summer School, DLRL Summer School at Mila - Quebec Artificial Intelligence InstituteDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Dalhousie University1st class Master of Science (MSc) Computer Architecture, 1st class Master of Science (MSc) Computer Architecture at University of Isfahan
English, Persian
Stackoverflow
41reputation
12kreached
3answers
0questions
Github Skills (76)
simulator9
optimization8
python8
deep-learning8
privacy8
federated-learning8
machine-learning8
pytorch8
gpu7
computer-vision7
object-detection7
data-science7
semantic-segmentation7
apache-spark6
inkscape6
Programming languages (3)
Github contributions (5)
fvarno/fvarno.github.io
Feb 2022 - Nov 2025
Contributions:39 pushes, 1 branch in 3 years 9 months
varnio/fedsim
May 2022 - Oct 2022
A generic Federated Learning simulator!
Contributions:19 releases, 329 commits, 93 PRs in 4 months
federated-learningdeep-learningdistributed-learningneural-networksoptimization
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