Alireza Azadbakht
Team Lead at Irapardaz
Tehran, Iran
Summary
👤
Senior🎓
Top SchoolAlireza Azadbakht is a Team Lead and AI Engineer with 8 years of experience building and deploying deep learning solutions, especially in medical imaging and edge-device applications. With an MSc in Computer Science from Shahid Beheshti University (top marks) and a thesis on MRI-to-CT image translation, he pairs rigorous academic research with practical data science work at the Non-Communicable Diseases Research Center and Irapardaz. He leads a data science and AI team, translating complex models into production-ready systems while retaining a hands-on role in model design, evaluation, and visualization of large medical datasets. His background includes teaching neural networks and advanced programming, plus early experience in VR game development and freelance software work, reflecting a rare blend of research, engineering, and product-minded creativity. Published work on deploying deep learning to edge devices signals both technical depth and a focus on real-world constraints. Ambitious about general AI, he aims to advance the field and mentor the next generation of researchers.
9 years of coding experience
3 years of employment as a software developer
Master of Science - MSc, Computer Science, 19.1/20, Master of Science - MSc, Computer Science, 19.1/20 at Shahid Beheshti UniversityHigh School Diploma, Mathematics, 19/20, High School Diploma, Mathematics, 19/20 at National Organization for Development of Exceptional Talents (Sampad)
Stackoverflow
1reputation
0reached
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Github Skills (26)
genetic-algorithm9
cifar1007
linear-regression7
data-mining7
deep-reinforcement-learning7
keras6
machine-learning6
deep-learning5
data-science5
algorithms5
accessibility5
kernel4
pytorch4
machine-learning-models4
edge-computing4
Programming languages (4)
Github contributions (5)
AlirezaAzadbakht/CNF-DNF-Calculator
Oct 2018 - Oct 2022
Contributions:7 commits, 6 pushes, 1 branch in 4 years
AlirezaAzadbakht/kernel-sharing
Sep 2022 - Oct 2022
Drastically Reducing the Number of Trainable Parameters in Deep CNNs by Inter-layer Kernel-sharing
Contributions:27 commits, 2 PRs, 10 pushes in 1 month
kernelcifar10convmixerseresnetcifar100
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