Artificial Intelligence

ASL Computer Vision Detection

As a part of my assistantship in the Applied Machine Learning and Intelligence Lab, I was tasked with creating a computer vision model that could detect American Sign Language (ASL) hand signs. The example you see below involves static hand signs only, so gestures that require movement are not interpretable with this method.

Empirical Evaluation of Signal Preprocessing in Electrocardiography Signal Classification

Data quality plays a crucial role in the performance of machine learning model training. Data preprocessing can contribute to enhancing the data quality, leading to overall improvement of the model performance. Thus, selecting the ap- propriate preprocessing algorithms is a critical step in designing any machine learning model, which remains challenging. This paper provides an empirical study of scaling algorithms and their reflection on model performance, primarily focusing on the electrocardiography signal classification tasks that are utilized in different disease detection systems.

This paper was written from Winter 2023 - Spring 2024. It was submitted to the IEEE ICMI-2024 Conference, but due to issues with University funding, it was not published.

IEEE ICMI2024 Reviewer

In the Spring of 2024, with my submission to the IEEE ICMI-2024 conference, I was asked to review several papers for the conference. I had to evaluate each paper based on various criteria such as originality, technical soundness, relevance, and presentation. I was also asked to provide constructive feedback to the authors of the papers I reviewed. Despite the issues with securing funding from my University for my own paper, I was able to provide valuable feedback to the authors of the papers I reviewed.