Skip to content
View JasmineLJM's full-sized avatar
4 followers · 11 following

Achievements

Achievement: Pull Shark

Achievements

Achievement: Pull Shark

Highlights

  • Pro

Block or report JasmineLJM

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Content in all repositories owned by your account will be closed.
Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
JasmineLJM/README.md

Jie-Min-Liang

Hi, I'm Jie Min Liang I am an Honours Computer Science student at Concordia University, interested in medical AI, vision-language model interpretability, and biomedical corpus validation. My current work focuses on evaluating whether domain-specific biomedical text corpora can improve the interpretability of biomedical vision-language models such as BiomedCLIP. I am especially interested in how semantic descriptions, medical imaging concepts, and model representations can connect in ways useful for explainable AI.

Research Interests

  • Medical AI and biomedical vision-language models
  • VLM interpretability and semantic representation analysis
  • Biomedical text corpus construction and validation
  • BiomedCLIP, TextSpan, and domain-specific evaluation
  • Machine learning for structured and imaging-related data

Current Work

  • NSERC USRA project: developed a biomedical TextSpan-style corpus for interpreting biomedical vision-language models
  • COMP 490 research: validating a biomedical corpus for BiomedCLIP/TextSpan interpretability across public biomedical imaging datasets
  • Selected ML project: time-series temperature forecasting using regression models and preprocessing pipelines
  • Power BI project: end-to-end hotel booking analytics (Python ETL -> star schema -> DAX -> 4-page report, version-controlled as a Power BI Project)

Technical Skills

  • Python, PyTorch, scikit-learn, NumPy, Matplotlib
  • BiomedCLIP, TextSpan, BioBERT, BERTScore, LLM-based evaluation
  • Power BI, DAX, Power Query, data modelling (star schema)
  • SQL, Java, JavaScript, HTML/CSS
  • Linux, Windows, Microsoft 365, VS Code

Selected Projects hotel-booking-powerbi A Power BI analysis of 119,208 hotel bookings (two hotels in Portugal, 2015-2017).

  • Cleaned the data in Python and modelled it as a star schema (1 fact table, 8 dimensions, marked date table)
  • Wrote 29 DAX measures, including weighted ADR, cancellation rates and year-over-year growth on comparable months
  • Built a 4-page report on revenue, cancellations, guest markets and seasonal pricing; found that bookings made over a year ahead cancel 68% of the time vs 10% for last-week bookings

ForecastPrediction A machine learning project for forecasting daily high temperatures in Montreal using weather station data.

  • Built preprocessing pipelines for daily aggregation, missing value imputation, feature engineering, and outlier handling
  • Compared Linear Regression, Neural Networks, SVR, and Random Forest models
  • Improved SVR test MSE from 77.06 to 42.94 through hyperparameter tuning

Contact

Pinned Loading

  1. ForecastPrediction ForecastPrediction Public

    Time-series machine learning project for daily high-temperature forecasting in Montreal.

    Jupyter Notebook