Vahid Behzadan
Associate Professor Of Computer Science And Data Science
West Haven, United States
Summary
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Rockstar🎓
Top SchoolVahid Behzadan is an associate professor and director of the Secure and Assured Intelligent Learning (SAIL) lab with eight years of academic experience and a long-standing background in cybersecurity, machine learning, and communication systems. He combines hands-on adversarial ML engineering—contributing practical RL attack scripts to the well-known CleverHans adversarial-example library—with theoretical research exploring game theory, optimal control, and neuroscience for AI safety. His career bridges industry and academia, from SDR and communications engineering to leading research on adversarial attacks against complex adaptive systems. As an independent cyber-security consultant and former communications systems designer, he brings a rare systems-level perspective on robustness and threat modeling that informs both teaching and lab-driven experiments.
8 years of coding experience
23 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Kansas State UniversityDoctor of Philosophy (Ph.D.) Security and Dynamics of Distributed Networks, Doctor of Philosophy (Ph.D.) Security and Dynamics of Distributed Networks at University of Nevada, RenoMSc by Research RF Engineering, MSc by Research RF Engineering at University of BirminghamBS Electrical Engineering, BS Electrical Engineering at Eastern Mediterranean University
English, Persian
Github Skills (10)
adversarial-machine-learning10
machine-learning10
benchmarking10
benchmark10
tensorflow10
python10
security10
reinforcement-learning9
openai-gym8
gymnasium8
Programming languages (3)
Github contributions (5)
cleverhans-lab/cleverhans
Jan 2018 - Jan 2018
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 2 PRs, 9 comments in 6 days
Contributions summary:Vahid primarily contributes to the development and modification of example scripts for reinforcement learning (RL) attacks, specifically within the context of adversarial machine learning. Their contributions include adding and modifying Python code, including the introduction of model.py and the incorporation of attack methods, such as crafting adversarial examples. The changes indicate a focus on experimenting with attacks, possibly within the domain of RL environments, and testing the robustness of models against these attacks.
benchmarkingrobustnessadversarial-machine-learningsecurityadversarial
behzadanksu/rl-attack
Nov 2017 - Mar 2019
Adversarial Example Attacks on Policy Learners
Contributions:2 releases, 14 commits, 13 pushes in 1 year 4 months
policyadversarial-attackspythonrobustnessadversarial
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