CV

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Research Interests

AI security — the security of AI agents and retrieval-augmented generation (RAG) systems, data governance, adversarial attacks and practical defenses, and audio watermarking.

Professional Experience

• USC Information Sciences Institute, Marina Del Rey, USA Jun 2026 – Aug 2026
  Research Intern
  • Reproduced and ported 34 research artifacts across 9 topics from ACSAC, IEEE S&P, USENIX Security, and NDSS to the SPHERE testbed, enabling researchers to reuse the artifacts.
  • Built an agent-based tool that automatically screens research artifacts for incompatible hardware and software requirements.
• Joint Laboratory of Materials Science, Xi'an Jiaotong University – Shanghai Hongzhiwei, Xi'an, China Jan 2022 – Jul 2024
  Data Scientist
  • Developed a machine learning chip-test classification algorithm with 98.5% accuracy, reducing workload by 75%.
  • Investigated process anomalies and yield-loss root causes by correlating production and test data using t-tests, ANOVA, and XGBoost feature importance, contributing to a 10% production-yield improvement within one month.
  • Analyzed wafer-map data using DBSCAN to localize spatial defect patterns, and developed a CNN-based wafer-map classifier for automated defect identification.
  • Designed the architecture and interactive interface for a yield-analysis platform supporting production-data analysis, visualization, and yield investigation.
• Yangtze Memory Technologies Co., Ltd. (YMTC) FDC Team – Hongzhiwei, Wuhan, China Jan 2023 – Jul 2024
  Product Manager
  • Designed the architecture and interactive interface for a Yield Management System supporting production-data analysis, visualization, and yield investigation.
  • Built a Defect Management System (DMS) and a Wafer Classification System.
  • Identified manufacturing and yield trends by analyzing wafer-defect maps and WIP/CP/FT data under the visualization modules.
  • Built four statistical process monitoring algorithms based on WECO rules, including consecutive N-point threshold and centerline-side rules, to detect process anomalies.
• Perry Ellis International, Doral, USA Jun 2019 – Jun 2020
  Data Scientist
  • Built ensemble sales forecasting models with Seasonal ARIMA and LSTM on Google Cloud Platform, reducing inventory costs by 12%.
  • Developed Bayesian sentiment analysis models using word-count and TF-IDF features to identify drivers of customer feedback.
  • Built ETL and automated ML prediction pipelines using Apache Beam and Google Cloud Dataflow, supporting scalable batch data processing and model deployment.

Education

• Indiana University Bloomington, Bloomington, USA Aug 2026 – Present
  Ph.D. in Computer Science
• University of Hawaiʻi at Mānoa, Honolulu, USA Aug 2024 – Aug 2026
  Ph.D. in Electrical and Computer Engineering
  GPA 4.00/4.00
• University of Miami, Miami, USA Jul 2018 – Sep 2019
  M.S. in Business Analytics
  GPA 3.64/4.00
• University of the West of England, Bristol, UK Aug 2016 – Jun 2018
  B.A. (Hons) in Accounting and Finance
  GPA 3.71/4.00
• Guangdong University of Finance, Guangzhou, China Sep 2014 – Jun 2018
  B.E. in Finance
  GPA 3.40/4.00

Publications

See the Publications page for the full list with links.

Technical Skills

• Programming languages: Python, R
• Visualization: Tableau, Power BI
• Cloud & infrastructure: AWS, GCP, SPHERE testbed