Personal statement

  • I worked as a management consultant for years, and I regard DATA and AI as important tools to empower organizations and sustainability. Enjoy doing hands-on research, analysis, and coding for better solutions.
  • I have a good understanding of environmental science and data science (including machine/deep learning, natural language processing, and data visualization). My goal is to be a Data Scientist or IT consultant.
  • For vision, I have hands-on experience in YOLO, GAN, and image classification training, and familiar with RNN, and CNN fundamental knowledge. For NLP, I have experience in labeling, sentiment analysis, and other classification tasks. Have basic knowledge of Azure.
  • Have 3 years' team management experience. Open to learning and challenges, optimistic, and sustainable. Aspire to bring more female leadership to STEM fields.

Research interests & Available time

  • Research interests: data models applications for sustainability or product
  • Open to 2024 summer internship or graduation thesis program. Starting from July 1st, I can work full-time. (maximum 1 year till graduation in 2025 summer)

Education

Leiden Uinversity

Master of Data Science: Computer Science

2023 - 2025

  • Completed courses: Deep Learning(CV), Text Mining(NLP), Data Mining, Social Network Analysis, Software Development and Product Management(Scrum), and Data Science in Practice(FAIR ontology).
  • Courses ongoing till June: Information Retrieval, Reinforcement Learning, Biomodeling, Robotics, Game AI algorithms
  • Honours course: Career as a Climate Change Maker.
  • Member of Study Association De Leidsche Flesch in Leiden University

Sun Yat-Sen University (Zhongshan University)

Bachelor of Environmental Science

2008 - 2012

Related courses: Calculus, Probability and Statistics, Linear Algebra, Environment Information System, Biology, Chemistry, Ecology, Environmental Engineering, etc.

Graduation Thesis: The response of antioxidant system to Zn/Cd stress in Arabis paniculata Franch. (Grade A)

Internship: Summer internship in Plant aseptic tissue culture in Xiamen Botanic Garden

Skills

  • Programming

    Python, Java, Sql, JavaScript+CSS+HTML

  • Tools

    Git, LateX, Gephi, Origin, Figma, Snoopy, Azure

  • Language

    English, Chinese Mandarin, Cantonese, Dutch beginner

  • Package

    TensorFlow, nltk, transformers, spacy, gym, networkX, optuna, sklearn,numpy, pandas, matplotlib

  • Certificate

    Chinese Intermediate Economist

Work Experience

Match Consultancy, Adecco, Tianfu Bank, Independent Consultant

Management Consultant

August 2012 - December 2022

  • HR management consultancy: Worked with companies in the chemical, agricultural, AI robotics, and IT industries. Provided solutions for OD, pay-performance reform, recruitment, and training, etc. Responsible for BU talent pool information system implementation, talent recruitment and consultancy, and due diligence work in Tianfu Bank.
  • AI robot business: Cooperated with manufacturers to market, lease, and sell robots, and provided clients with training and data monitoring services.

Project Experiences

Personal datapod in FAIR-based ontology with permission control

Team Leader

  • Our course project for 'Data Science in Practice' aims to create a decentralized datapod prototype that allows specialized individuals to reuse their personal documents and medical data. Trust and privacy protection are crucial.
  • As a team leader, I led the team in studying and exploring the challenge, working with the lecturer, TAs, Ph.D. guide, interviewees, and advisers from other organizations.
  • Design the overall system's conceptual structure, work plan, and quality control. Research the technical difficulties of the project and provide solutions.
  • Achievement: I received great feedback, graded 8.5, and was invited to contribute a chapter for a new book to prolong the project beyond the course, will finish the writing before May.

Sentiment Analysis for Text Mining Course

  • Based on the SemEval-2017 Task 4 paper, researched, reproduced, and compared two models (the MSA and the self-built simplified converter model). Gain practical knowledge about Biltsm and transformer models.
  • The task of performing sentiment analysis on Twitter data was accomplished through data cleaning, embedding, model training, and delivered the scientific report.

Activities

National Hackathon Circular Economy 2024: Towards slow fashion