Bing Hu
Sydney,NSW
Summary
Self-driven professional with a strong work ethic, demonstrating exceptional focus and diligence in data-related tasks. Passionate about leveraging data to drive insights and decision-making. Excellent communicator and team player, adept at collaborating in diverse environments. Quick learner with a keen analytical mind, consistently embracing new technologies in the evolving field of data science. Creative problem-solver who effectively bridges technical concepts with business objectives. Committed to continuous growth and staying current with industry trends, while maintaining strong time management skills in fast-paced settings.
Overview
2
2
years of professional experience
Work History
Medical data analysis and machine learning predictive models (R language)
08.2023 - 09.2023
- Development of diabetes risk prediction system using advanced data analysis technology
- For 130000 patients, 180 characteristics of large-scale medical data sets for deep cleaning and feature engineering, significantly improve data quality and model efficiency.
- Design and implement KNN, SVM, logistic regression, XGBoost and other machine learning models
- Through innovative parameter tuning methods to improve model performance Systematically compare model performance, identify optimal algorithms, significantly improve prediction accuracy, create intuitive data visualization, enhance model interpretability.
Handwritten character recognition system optimization research
02.2023 - 03.2023
- Comparison of traditional machine learning and deep learning technology to develop high-precision handwritten character recognition model
- The EMNIST data set for depth feature engineering, the application of normalization and PCA and other techniques to optimize the 160000 sample of the high-dimensional feature space.
- Build and implement multi-level machine learning model combinations, including logistic regression, support vector machines (SVMs), and convolutional neural networks (CNNs)
- Design automated hyperparameter tuning processes, using grid search and other algorithms to optimize SVM kernel functions and CNN architectures.
- Through rigorous cross-validation and statistical analysis, the model performance is significantly improved, and the performance of each model in complex scenarios is discussed in depth.
Image segmentation system development: brick recognition and detection in industrial scenes
08.2022 - 10.2022
- Using deep learning technology to develop a high-precision image segmentation system for brick recognition and location in industrial scenes
- Use Stable Diffusion to generate large-scale high-quality industrial scene image datasets, covering a variety of different scenes
- Apply LabelMe tools for accurate data labeling, develop efficient image preprocessing processes, and achieve pixel-level labeling
- Design and implement a U-Net architecture-based deep convolutional neural network model to optimize encoder and decoder structures.
- Use the PyTorch framework to build models for data loading, model training, validation and prediction
- By iteratively optimizing the training strategy and model structure, significantly improve the system in complex industrial scene recognition accuracy.
- Successful development of systems that can accurately identify and locate bricks in complex industrial environments.
Intern in user research and experience design
University of Technology, Sydney
02.2022 - 05.2022
- Participate in the development of customized housing recommend platform for international students, committed to alleviating the housing pressure of international students
- Design and implement a multi-stage user research program, including questionnaires, in-depth interviews and user log analysis, to collect 60 international students' multi-dimensional needs data
- Lead the interview data qualitative analysis process, refine key user insights and independently build 5 data-driven user portraits, covering demographics, behavior patterns, needs and pain points and other dimensions, for product strategy to provide actionable user insights.
- Assist the team to develop user goals and user tasks to ensure that product features and actual user needs closely match
- Regularly present user research findings to cross-functional teams to drive data-driven product decision-making processes
- The final product will be launched in 3 months to help 280 students match their ideal residence.
Education
Master - Information technology
University of Sydney
12.2024
Bachelor - Information technology
University of Technology, Sydney
12.2023
Skills
- Proficient in Python programming, with strong skills in data processing, analysis and visualization using libraries such as NumPy, Pandas, Matplotlib, etc
- Proficient in SQL, can write complex queries, database design and optimization, and have database management and large-scale data processing experience
- Proficient in using BI tools such as Tableau, Power BI, and Excel for data analysis and creating interactive dashboards and reports
- In-depth understanding of machine learning algorithm principles, such as SVM, logical regression, CNN, etc, can be skillfully applied to practical projects
- Familiar with deep learning framework TensorFlow and Keras, have build and optimize neural network model practice experience
- Proficient in data preprocessing techniques, including feature engineering, dimensionality reduction (such as PCA) and data cleaning
- Proficient in using Scikit-learn for machine learning model training, evaluation and optimization, and has a solid statistical foundation, can carry out hypothesis testing, regression analysis and variance analysis
- Proficient in using Figma and other design tools, can independently complete user interface prototype design
Timeline
Medical data analysis and machine learning predictive models (R language)
08.2023 - 09.2023
Handwritten character recognition system optimization research
02.2023 - 03.2023
Image segmentation system development: brick recognition and detection in industrial scenes
08.2022 - 10.2022
Intern in user research and experience design
University of Technology, Sydney
02.2022 - 05.2022
Master - Information technology
University of Sydney
Bachelor - Information technology
University of Technology, Sydney
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