Summary
Parsa Hejabi is a PhD student in Computer Science at USC and a research-focused engineer who builds secure, production-ready NLP systems that bridge lab research and real-world deployment. He designs annotation platforms and secure pipelines for sensitive body-worn camera data, prototypes multi-agent simulations to probe LLM creativity and deception, and co-authored metrics featured in an ACL 2024 workshop. Prior roles include scaling election‑monitoring pipelines and fine-tuning moderation models (F1 up to 0.85) at USC‑ISI, plus full‑stack and DevOps contributions in industry. Currently interning as a deep learning/agent builder where he applies graph neural nets to molecular data and orchestrates LLM-backed agent workflows with FastAPI and DAG-style orchestration. Fluent in Python, PyTorch, Hugging Face, and cloud tooling, he combines rigorous research methods with hands-on product engineering. An understated strength is his track record of delivering secure, reproducible tooling for sensitive datasets—an asset for any team deploying ML in constrained environments.
9 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
Allameh Helli 2 Middle School
Bachelor of Science - BS Computer Engineering, Bachelor of Science - BS Computer Engineering at Shahid Beheshti University
High School Diploma Mathematics, High School Diploma Mathematics at Allameh Helli school
Persian, English