welcome to Yasamin Aali’s page

I am a graduate student studying my Master of Computer Science in Brock University under the supervison of Dr.Rahnuma Islam Nishat. I’m working on Graph Theory and 3D Printing. Additionally, I’m fascinated with ML and AI, especially interested in Natural Language Process and its use in social networks, Recommender Systems. I have done several research projects in these areas.

Enhancing Sentence Relatedness Assessment using Siamese Networks

Explainable detection of online sexism (EDOS)

Online communication has brought about an increase in sexist comments and tweets, posing significant harm to women and their social,psychological, and economic well-being. Detecting whether a text is sexist or not remains a significant challenge. This study focuses on fine-grained classifications for sexist content from two popular social media platforms, Gab and Reddit, using machine learning and natural language processing techniques. The study compares multiple classification models, including simpler models like Logistic Regression and SVM, and more advanced models like ensemble methods and BERT, with the aim of developing more effective tools to detect and combat online sexism.

Association rules algorithm using financial dataset

My bachelor thesis aimed to analyze a financial dataset using R programming language and association rules algorithm. This project includes several steps, including data cleaning and preprocessing, exploratory data analysis, and building an association rules model. This model was used to identify patterns and relationships between data set variables and generate actionable insights for investors and financial analysts. The results of the analysis showed that the association rules algorithm is effective in identifying interesting patterns and relationships in the financial data set. The model identified several rules that can be used to guide investment decisions, such as the relationship between profitability ratios and stock prices. You can find more about this project on it’s github code.

Data mining algorithms using heart disease dataset

Data mining project with heart disease dataset from Kaggle using Python. Used supervised and unsupervised algorithms (k-nearest neighbor, naive bayes, logistic regression, decision tree, k-means, one-r). You can find more about this project on it’s github code.

Business Data Analyst Intern

I worked as a Business Data Analyst Intern at Snapptrip, a dynamic company specializing in hotel bookings and ticket sales. In my role, I was tasked with analyzing data to gain insights into customer preferences, market trends, and operational efficiency. This involves extracting meaningful information from large datasets to help the company make informed decisions and enhance the overall user experience. It was an exciting opportunity that allowed me to apply my analytical skills in a real-world setting and contribute to the success of a rapidly growing travel and hospitality platform.