Projects

Guided Speech Enhancement Network | Sep 24 to Dec 24
[Project Details], [GitHub Repository]

Implemented and trained Google’s Guided Speech Enhancement Network (GSE Network) using PyTorch on the Google Cloud Platform Compute Engine for denoising and enhancing local Singaporean English.
Utilized IMDA’s National Speech Corpus for curating a dataset of beamformed waveforms for more realistic training and evaluation.

No Pain, Just Gain | Sep 24 to Dec 24
[Project Details], [GitHub Repository]

Implemented and trained Google’s BlazePose model using TensorFlow for human pose estimation.
Experimented and modified the BlazePose architecture in an effort to improve Percentage of Correct Key-points (PCK) scores.
Added Convolutional Block Attention Modules (CBAM) to the architecture to improve intermediate feature representations.

SmartDrive, Machine Learning Researcher (Computer Vision) | May 23 to Dec 23

Conduct literature reviews and identify relevant research and technologies for detecting driver fatigue.
Collect and preprocess sensor data from depth and thermal cameras to prepare it for algorithms to detect fatigue.
Implement and test algorithms relevant to Computer Vision, and utilized various techniques such as PERCLOS, Head Pose Estimation, and Eye Gaze Estimation.

Sentiment and Entity Analysis (Natural Language Processing) | May 23 to Aug 23
[Project Details]

Designed and applied a machine learning system using Hidden Markov Models to identify sentiments in informal sentences (tweets).
Tuned and validated the system by varying different smoothing methods which resulted in a ~240% improvement in the F scores (precision and accuracy) for identifying sentiments in the Spanish Language.
Instilled good practices for developing a machine learning framework to train and cross validate across different models to select the best model for optimal results.

Office of Student Life Web Application (Software Engineering) | May 23 to Aug 23
[Project Details]

Designed a web application for SUTD’s office of student life and used Amazon Web Services (AWS) such as Amazon Cognito, API Gateway and serverless Lambda Functions to deploy the web application.
Developed the application through a hybrid of Incremental and Iterative methodology and the Agile Manifesto whilst documenting the project with Unified Modeling Language (eg: Use Case diagrams, Sequential diagrams etc)
Performed unit, integration, and system tests for the backend functionalities of the application to achieve a coverage of 90.22% using Jest.
Integrated and configured AWS and Github for the team to develop and deploy the application (eg: AWS Identity and Access Management (IAM) for permissions, AWS Amplify for CI/CD deployment and AWS RDS for database management).

Solar Dehydrator DCH, Data Analyst | Sep 22 to Dec 22
[Project Details]

Worked in a group of five to design a unique and successful prototype to dehydrate food using Solar Panels, Arduino and a Fresnel lens which dried the (wet) test sponge within 1 hour. My main role is to analyze and interpret Solar Irradiance data.
Conducted data cleaning by fixing structural errors and filtering outliers (the 29th of February in the leap year).
Performed Q-Q plots to assess if the data fits a normal distribution. Subsequently, utilized the Central Limit Theorem to establish a confidence interval. Ultimately, we concluded that the solar dehydrator receives enough solar irradiance to dehydrate food continuously with a 90% confidence level.