Saeid Niari
Assistant Professor at University of Illinois Chicago
United States
Summary
👤
Senior🎓
Top SchoolSaeid Niari is an assistant professor of computer science with nine years of experience at the intersection of machine learning, software engineering, and fairness, currently on faculty at the University of Illinois Chicago after a prior appointment at UT El Paso. He earned a PhD in Computer Engineering from the University of Colorado Boulder and focuses on analyzing large-scale software, deep learning models, and ML libraries to provide fairness, performance, and security guarantees. Saeid blends rigorous academic research with practical teaching experience, having taught programming labs and supervised research since his graduate studies. His work often examines systemic properties of ML systems rather than isolated models, aiming to make deployed pipelines auditable and robust. Colleagues describe him as a methodical researcher who translates theoretical insights into evaluation tools that practitioners can apply to real-world codebases. Fluent in Persian and trained across top Iranian and U.S. institutions, he brings a global perspective to technical and ethical challenges in AI.
9 years of coding experience
11 years of employment as a software developer
Bachelor's Degree, Information Technology, 17.17, Bachelor's Degree, Information Technology, 17.17 at University of TabrizDoctor of Philosophy (Ph.D.), Computer Engineering, 3.96, Doctor of Philosophy (Ph.D.), Computer Engineering, 3.96 at University of Colorado BoulderMaster’s Degree, Information Technology, 18.54, Master’s Degree, Information Technology, 18.54 at Sharif University of Technology
English, Persian, Azerbaijani, Turkish, Spanish
Github Skills (50)
statistics10
fairness-ml10
data-science9
machine-learning-models9
artificial-intelligence9
python9
machine-learning9
ranking9
ai9
data-analysis9
scikit8
react8
science8
scikit-learn8
computer-science7
Programming languages (3)
Github contributions (5)
Tizpaz/Parfait-ML
Jul 2021 - Dec 2022
Implementations for detecting and understanding biases in ML libraries
Contributions:1 release, 2 reviews, 26 commits in 1 year 5 months
implementationsunderstandingdeep-learningbiasesml
cuplv/Discriminer
Aug 2016 - May 2018
Contributions:38 pushes, 1 branch in 1 year 9 months
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