Alireza Ziabari is a data scientist and graduate research assistant at USC with eight years of experience applying machine learning across industry and academia. He has built production ML systems—from ETA prediction and search ranking at TAPSI to object detection for embedded dash cams at FANAP—and explored anomaly detection with autoencoders and GANs during his undergraduate research. Currently pursuing a PhD in Computer Science, he works in the Computer Social Science Lab and recently completed an ML research internship at Netflix focused on aligning and evaluating LLMs for recommender systems. He combines practical engineering experience with research rigor, moving models from prototype to deployed services. Based in Los Angeles, he is curious about real-world ML applications and often blends adversarial and representation-learning techniques to uncover better features.
8 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Southern California
High School Diploma, High School Diploma at Allameh Helli school
Bachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Sharif University of Technology
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Contributions:8 pushes in 1 year 8 months
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