Introduction

About

Profile

Yeongjin Yu | Statistics & Data Analytics Graduate
Australia
yjyuwisely@gmail.com
linkedin.com/in/yeongjinyu
With a strong foundation in mathematics and statistics, I am focused on building practical, data-driven solutions using statistical analysis and applied machine learning. ๐Ÿ˜Š

Hello! Iโ€™m Yeongjin Yu, a Statistics and Data Analytics graduate with a strong foundation in mathematics and statistical modelling. My work focuses on data analysis, applied machine learning, and building reproducible, interpretable solutions using real-world datasets. I am particularly interested in applying statistical reasoning and machine learning techniques to support data-driven decision-making. I am currently focused on building industry-ready projects and gaining professional experience in Statistician or Data Analyst roles in Australia. In the longer term, I aim to progress into more advanced machine learning and research-oriented work after establishing strong analytical and industry foundations. This portfolio highlights my academic training and applied projects in statistics and data analytics, laying the foundation for professional growth and future progression into advanced machine learning and research-oriented work.๐ŸŒฑ

Education

Education

  • UOW University of Wollongong (UOW) | Master of Mathematical Sciences

    My masterโ€™s coursework focused on advanced statistical modelling and data analysis, with practical applications using R and Python. Key areas included regression modelling, time series analysis, and data-driven analytical methods, with an emphasis on reproducible analysis and real-world datasets.

  • UOW University of Wollongong (UOW) | Graduate Diploma in Mathematical Studies

    My studies at UOW focused on advanced statistical theories, artificial intelligence, numerical analysis, and linear algebra. The coursework covered a wide range of subjects, including Data Mining and Knowledge Discovery, Statistical Inference, Linear and Generalised Linear Models, Probability, Research Methods, and Financial Calculus, providing a comprehensive foundation in statistical theories and AI. I undertook an extensive research project using R programming to analyze satellite big data. This culminated in my thesis, "Bayesian Identifiability with Application to COโ‚‚ Flux Inversion," where I used Bayesโ€™ theorem, hierarchical models, and Kullback-Leibler divergence to estimate COโ‚‚ fluxes. These academic pursuits highlighted the importance of advanced statistics and analytical techniques in AI.

  • UWA University of Western Australia (UWA) | Bachelor of Science in Quantitative Methods

    I majored in Quantitative Methods, gaining a solid foundation in the theoretical and practical aspects of data analysis crucial for AI. My proficiency grew in R for data processing and visualization, and I expanded my skills with Python and Java through elective courses. The curriculum included mathematical subjects such as Calculus, reinforcing my understanding of essential mathematical concepts for AI algorithms. In a significant research project, my thesis "Determining Factors Affecting First-Time Peripheral Intravenous Cannulation Success in the Emergency Department" utilized advanced statistical techniques, such as logistic regression and ROC Curve analysis, to explore real-world healthcare challenges.

Continuing Education & Training

  • Seoul ICT Innovation Square Seoul Capital Area ICT Innovation Square | Advanced AI Bootcamp (Python & Deep Learning)

    Participated in an advanced AI bootcamp focused on applied deep learning using Python. Developed a real-world AI system as part of a team-based final project, applying model development and deployment techniques.

    Top Project Award โ€” awarded for overall project quality, technical implementation, and practical applicability. (Nov 2024)

    The program was delivered by Seoul Capital Area ICT Innovation Square as part of the government-supported Training initiative, focusing on practical applications of artificial intelligence and deep learning. The curriculum covered Python-based model development, applied deep learning techniques, and end-to-end project execution in a real-world setting.

  • UlsanGreenComputerAcademy Ulsan Green Computer Academy | [K-Digital Training] IoT-Based Smart Healthcare Web Service Development Bootcamp

    This intensive bootcamp significantly deepened my understanding of key frontend and backend technologies, as detailed in the Skills section of my portfolio. Its hands-on curriculum emphasized practical application, which bolstered my skills in teamwork and problem-solving. The program also developed my capabilities in project management, communication, and creative thinking, proving instrumental in laying a solid foundation for my career as an AI research scientist.

Skills

Statistics & Data Analytics
Statistical modelling, regression/GLMs, time series, hypothesis testing, EDA, data visualisation
Programming
Python, R, SQL
Python (Data/ML)
pandas, NumPy, scikit-learn, Jupyter
R (Data/Stats)
tidyverse, ggplot2
Version Control
GitHub
Visual Design and Communication
Figma (UI Design), Canva (Presentation Design)
Team Communications
Notion

Data Analytics & Applied Machine Learning Projects

This section will feature applied data analytics and machine learning projects using real-world datasets, with an emphasis on statistical modelling, reproducible analysis, and practical insights.

AI Development Project List

MovieSense: Empowering Movie Reviews with AI

Aug - Sep 2024 Enhancements (Individual Project)

nlpProject1_1 nlpProject1_2

In this project, I focused on deepening my understanding of various NLP (Natural Language Processing) techniques by developing MovieSense, a tool that leverages state-of-the-art models to analyze and enhance movie reviews. MovieSense combines sentiment analysis, summarization, translation, and text generation to enrich user engagement with movie critiques across different languages.

Key Features:
  • Sentiment Analysis:
    Utilizes a pre-trained BERT model (`distilbert-base-uncased-finetuned-sst-2-english`) for accurate sentiment classification, improving on the initial Naive Bayes approach.
  • Dynamic Summarisation:
    Generates concise summaries using Facebook's BART model, effectively capturing the essence of lengthy reviews.
  • Translation:
    Translates reviews seamlessly reviews from English to French using the mBART model, handling multilingual NLP tasks more robustly compared to the initial Helsinki-NLP model.
  • Text Generation:
    Produces coherent movie reviews based on user prompts using the GPT-2 model and the enhanced GPT-3.5-turbo with Retrieval-Augmented Generation (RAG) for greater contextual accuracy.

    • GitHub ๐Ÿ‡บ๐Ÿ‡ธ
    https://github.com/yjyuwisely/MovieSense_NLP

    Primary Language
    Python
    NLP Techniques & Models
  • Sentiment Analysis: BERT (`distilbert-base-uncased-finetuned-sst-2-english`)
  • Summarisation: BART (Hugging Face's Transformers)
  • Translation: mBART (Hugging Face's Transformers)
  • Text Generation: GPT-2, GPT-3.5-turbo with Retrieval-Augmented Generation (RAG)
    • Frameworks/Libraries
    NLTK, Transformers (Hugging Face), Flask (Backend Development)
    Frontend
    Vanilla JavaScript, Bootstrap, CSS3, HTML5

    Check out the GitHub repository to explore the code, experiment with the models, or contribute to further development.

    Web Project List (2023)

    The projects below, consisting of three team projects and two individual projects, were completed during my time at the Healthcare Web Service Development Bootcamp in South Korea from December 2022 to July 2023. This bootcamp is part of the K-Digital Training initiative, a recognized national program focused on tech education and skills development.

    To show the web projects, please click the button below.

    Blog & Github

    github-mark Github_Logo
    github.com/yjyuwisely
     My GitHub repository showcases coursework and applied projects in statistics and data analytics, including time series forecasting, statistical machine learning, clustering, classification, and data visualisation. Projects are implemented in R and Python with an emphasis on reproducible analysis, real-world datasets, and clear communication of results. The repository also includes the source code for this portfolio website.

    Blog
    yjyuwisely.tistory.com
     I created this blog to store and share what I've learned. This blog contains personal study notes, project reflections, and learning records, primarily written during my bootcamp period. Most posts are in Korean.

    Awards

    'MO BAO AWARD'

    Outstanding Performance in the Field
    International Studio of Art and Culture

    I participated in the International Studio of Art and Culture program in Bali, Indonesia, as part of the architecture and design department during my undergraduate studies. Through this experience, I immersed myself in the local culture, learning about the region's artistic traditions and refining my skills in photography and painting. I was honored to receive the prestigious MO BAO AWARD, which is presented to the most exceptional student making a positive impact on fellow students. Interestingly, I received this recognition even though my major wasn't in design, which surprised the professors. Reflecting on this achievement, I recall how my curiosity led me to explore new challenges, fostering a passionate and proactive approach to learning and applying new technologies. The MO BAO AWARD represents not only my dedication to pursuing excellence but also underscores how diverse experiences drive personal and professional growth.

    © 2023 Yeongjin's portfolio. All Rights Reserved.