Ehsan Azarnasab
Co-Founder at Stealth AI Startup
Redmond, Washington, United States
Summary
👤
Senior🎓
Top SchoolEhsan Azarnasab is a pragmatic AI and embedded systems leader with 13+ years building deployed signal-processing, computer vision, and deep learning systems across startups and Microsoft research teams. As a co-founder and former CTO, he has taken algorithms from embedded firmware and realtime neural signal processing to cloud-scale computer vision and multimodal GenAI at Microsoft, blending low-level driver work with high-level model engineering. He contributed to the dlib C++ ecosystem by improving its cross-platform build and packaging, reflecting a knack for making research-grade code reliably build and ship. Comfortable across C/C++, Python, CUDA and embedded toolchains, he repeatedly bridges the gap between hardware-constrained firmware and production AI services. Based in Redmond, he pairs academic training in electrical engineering and computer science with hands-on entrepreneurship and a taste for coffee, audiobooks and well-engineered systems.
13 years of coding experience
22 years of employment as a software developer
The University of UtahB.S. Electrical Engineering, B.S. Electrical Engineering at Isfahan University of TechnologyM.Sc. Computer Science, M.Sc. Computer Science at Georgia State University
English, Persian, German
Stackoverflow
2,625reputation
1.1mreached
41answers
12questions
gdb
top-5%
Github Skills (20)
c-language10
python10
machine-learning-models10
machine-learning10
cmake10
cprogramming-language10
package-management9
build-automation9
gdb9
computer-vision8
deeplearning-ai7
deep-learning7
dlib7
filepath6
x116
Programming languages (13)
Github contributions (5)
davisking/dlib
Aug 2015 - Feb 2017
A toolkit for making real world machine learning and data analysis applications in C++
Role in this project:
Backend Developer
Backend DeveloperContributions:33 commits, 5 PRs, 29 comments in 1 year 6 months
Contributions summary:Ehsan primarily contributed to the setup and configuration of the dlib library build process and packaging tools. This involved modifying the `setup.py` file to manage build options, dependencies, version information, and distribution artifacts, alongside ensuring proper inclusion of necessary packages. The user also implemented improvements to handle cross-platform builds and resolved potential issues related to platform-specific artifact packaging. These modifications streamlined the build and packaging process for the dlib library.
data-analysispythondata-sciencedeep-learningc-plus-plus
dashesy/langchain
Feb 2023 - Jul 2023
⚡ Building applications with LLMs through composability ⚡
Contributions:1 PR, 221 pushes, 11 branches in 4 months
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