Xiaoya Lin (林小雅)

Xiaoya Lin (林小雅)

Hi, I’m Xiaoya Lin(林小雅), an aspiring researcher currently pursuing my Bachelor of Electrical and Electronic Engineering (Year 3) at Nanyang Technological University. My research interest centers around Generative Visual Forensics & Deepfake Detection, Image Restoration and Visual Anomaly & Robust Generative Modeling.

You can find my CV here: LinXiaoya’s Curriculum Vitae.

Email / Github / LinkedIn / Wechat

🎓 Education

Nanyang Technological University, Singapore
Bachelor of Electrical and Electronic Engineering
Aug 2023 – May 2027 (Expected)

  • Specialization in Data Science and Machine Learning
  • Dean’s List (2024)
  • NTU Science & Engineering Undergraduate Scholarship Recipient

💼 Research & Work Experience

GlobalFoundries

Data Scientist Intern (May 2025 – Dec 2025)
Research Focus: Intelligent Data Engineering for Scalable Analysis and Visual ML

Project 1: Scalable Trace Data Pipeline & Compression for Semiconductor Analytics

  • Designed and optimized modular pipelines using AWS S3, Boto3, and PySpark for multi-month trace data retrieval and analysis.
  • Investigated and deployed Parquet + Snappy compression techniques to enhance computational efficiency and data fidelity.
  • Achieved major scalability milestones: extraction time reduced from hours to 4–8 mins, storage reduced by up to 90%, and eliminated memory crashes on large-scale workloads.

Project 2: Trace-to-Image Machine Learning Pipeline

  • Conducted a literature survey and pilot study on time-series-to-image conversion and visual classification for semiconductor trace data.
  • Developed a multi-phase pipeline converting segmented traces into images (e.g., Gramian Angular Fields, line charts), followed by RNN baseline model training and hyperparameter tuning using Optuna and Keras-Tuner.
  • Delivered a reproducible ML pipeline with ≥5% accuracy improvement, validated through internal presentations and journal deliverables.

A*STAR

Healthcare Data Pre-Processing Research Intern (Jan 2025 – Apr 2025)

  • Preprocessed and anonymized facial healthcare datasets for AI validation
  • Applied feature preservation techniques aligned with model optimization
  • Supported research in compliance with national healthcare standards

Classbro (Shanghai DAOBI EdTech)

Data Science & ML Instructor (Jun 2024 – Dec 2024)

  • Developed and delivered lectures on core ML algorithms and SQL
  • Designed course content that contributed 10,000 SGD+ in growth

🧠 Skills & Technologies

  • Programming Languages: Python, R, C
  • Data Science Tools: Pandas, NumPy, Scikit-learn, TensorFlow, XGBoost
  • Cloud & Big Data: AWS S3, Boto3, PySpark
  • Databases: MySQL, MongoDB, NoSQL
  • Software & Tools: Jupyter Lab, Figma
  • Certifications: Bloomberg Market Concepts, Coursera ML & Python modules

🔬 Research Projects

URECA Project – AlzCare Smart Watch (Aug 2024 – Present)

  • Leading AI wearable development for dementia care
  • Implementing behavioral monitoring, geofencing, and fall detection models
  • Engaging with SG Jamiyah & SG DementiaHub for user-centered validation

Hotel Booking Trends & Cancellation Forecasting (Feb 2024 – Apr 2024)

  • Applied ensemble ML models to Kaggle data
  • Achieved 91% accuracy via TensorFlow neural network optimization
  • Delivered business insights through structured analytics and visualization

EV Transition Database Analysis (Aug 2023 – Nov 2023)

  • Used MySQL & MongoDB to assess EV infrastructure in Singapore
  • Proposed strategic recommendations for sustainable transportation

🌱 Co-Curricular Activities & Leadership

  • NTU IET, Liaison Manager (Jul 2024 – Present)
  • NTU Investment Interactive Club, Member (Jul 2024 – Present)
  • CFLS-MUN, Academic Director (Dec 2019 – Dec 2021)
    • Chaired the North-East MUN Conference with 1,000+ attendees
    • Led delegations to World MUN and Yale MUN
    • Trained 100+ students in debate strategy and resolution writing