xiaofei Wang

I am a Ph.D. Candidate in Electrical and Computer Engineering with over five years of hands-on research experience in machine learning, deep learning, large language models, and behavioral biometrics. My research focuses on AI-driven security solutions such as keystroke dynamics authentication, user behavior modeling, anomaly detection, and fairness evaluation on large-scale datasets.

I independently design, train, optimize, and deploy robust ML models and production-ready pipelines, having implemented classical and deep-learning architectures (SVM, Random Forest, XGBoost, LSTM, Transformer) and automated data processing for thousands of users. My work improved authentication accuracy by 10% and produced multiple peer-reviewed publications in IEEE and other venues.

I build practical tools to translate academic innovation into real-world impact, including an LLM-powered research assistant with automated arXiv connectors and an interactive Streamlit dashboard, and I seek R&D roles in applied machine learning or data science where I can continue to advance secure, fair, and scalable AI systems.