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Yuan Xu
Junior Machine Learning Engineer specializing in multimodal AI and audio deepfakes detection
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About
Internship experience building production-oriented AI systems, including a real-time voice scam/spoof detector (RawNet + AASIST) hardened for noisy audio via aggressive augmentation and Zoom-based noise simulation, evaluated with EER on clean and wild datasets. Also built an LLM-driven UI automation agent using Playwright for apps like Linear/Notion with modular tool design, unit tests, and replayable scripted scenarios, and has AWS Step Functions experience orchestrating Lambda/Cognito workflows.
Experience
Education
Key Strengths
- Built and benchmarked a real-time voice scam/spoof detection system using RawNet + AASIST
- Improved robustness to noisy real-world audio via heavy data augmentation and Zoom noise simulation
- Uses rigorous evaluation (clean vs wild datasets; EER) to measure model robustness
- Production workflow reliability using AWS Step Functions with retries/timeouts for Lambda-based systems
- Designs AI agents as modular tools with unit tests plus scripted task suites and log replay
- Iterative model/prompt strategy driven by error analysis (moved from single-LLM to two-stage planning; enforced short plans with explicit UI attributes)
- Effectively collaborates with non-technical stakeholders by reframing ML metrics into operational tradeoffs; reduced false positives and manual inspections on a production line
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