Hi! I'm Winnie!

Analytically driven Data Scientist with expertise in data pipelines, automation, machine learning, NLP, and data visualization, strengthened by an MSc in Data Science and a background in Environment & Sustainability. Skilled at transforming complex data into actionable insights and intuitive dashboards.

With over six years of experience in business operations and supply chain optimization, I am passionate about applying advanced analytics and GenAI techniques to drive innovation in sustainability, ESG, and responsible supply chains.

What I do

  • Product Matching

    Mining the Web of HTML-embedded Product Data (MWPD) on the Semantic Web Challenge @ISWC 2020 called for a benchmark semantic technology to solve the product matching and product classification tasks on e-commerce data to facilitate the research in this domain.

  • Happiness Analysis

    How to live a joyful life? What types of people or surroundings make living happier?

    The project collects multiples datasets from London Datastore to replicate the Sustainable Cities Index (SCI) gauging method for investigating the external factors that mainly influence human mental well-being.

  • ESG Trend Insight Engine

    🌱 This project combines GenAI, NLP, and Knowledge Graphs to uncover how companies report their ESG (Environmental, Social, Governance) commitments over time.

    Key features include:

      📊 Keyword & topic trend visualisation by year, company, or industry
      🧠 Hybrid RAG pipeline (Vector DB + Knowledge Graph) for ESG Q&A
      🔍 Explainability toggle showing Claude summaries, Neo4j facts, and document snippets
      📈 Topic modelling (LDA/BERTopic) to track evolving ESG buzzwords

    The GitHub repo contains the full pipeline and a Streamlit app demo.

Who I Am

Building Innovative Solutions
for a Greener Future.

  • 2011 BS Plant Pathology & Microbiology
    NTU
  • 2012-2014 MS Environment & Sustainability
    UMich
  • 2015-2019 Project Engineer & Manager
    BizLink Tech
  • 2019-2020 MS Data Science
    City U of London
  • 2021- Data Analyst Accenture

I’m a Data Scientist and Sustainability Advocate, passionate about harnessing data and emerging AI technologies to drive positive environmental and business impact. My journey began with a deep interest in the intersection of data science and climate action, which led me to pursue an MSc in Data Science and an MS in Environment & Sustainability. Along the way, I’ve built expertise in machine learning, natural language processing, big data analytics, and generative AI applications.

Professionally, I bring over four years of experience delivering data-driven solutions — from automating complex reporting processes to optimizing supply chain efficiency. For example, I developed and implemented scalable data pipelines that reduced operational processing time by 75%, significantly improving decision-making and cost efficiency for stakeholders.


Beyond my professional work, I lead projects that explore the application of NLP and GenAI in ESG and supply chain insights, including building a hybrid RAG + Knowledge Graph system to extract sustainability trends from corporate reports. These projects fuel my vision of using data and AI to advance responsible sourcing, transparency, and sustainable growth.

Outside of data, I enjoy life as an adult ballerina and co-founded a jewelry brand that promotes conscious buying and sustainable making practices. I thrive on continuous learning and creative problem-solving, and I’m excited to keep pushing the boundaries of how data science and GenAI can accelerate solutions for climate change and ESG challenges.

If you’ve read this far, I’d love to connect and explore how we can work together to build a more sustainable future.

Contact Me

If you made it this far, I'd love to chat!
Message me on LinkedIn!