Yap Sin Yee

✉ emily@yapsinyee.com

An independent and self-motivated computer science graduate with proficient programming skills, particularly in web development and machine learning. A strong link between theory and practice from a BSc, practical internship and freelance web development job.

"Keep your eyes on the stars, and your feet on the ground."

Skills

Web Development (Front end/Back end web application, website)
Machine Learning (Modelling and simulation)
Bioinformatics (Neuroimaging analysis, sequence alignment)
Database Management (MySQL, SPSS, MongoDB)
Statistics (Results visualization)
Others (Communication, teamwork, critical thinking)

Languages

Malay ➊➋➌➍➎➏➐➑➈➉
Chinese ➊➋➌➍➎➏➐➑➒➉
English ➊➋➌➍➎➏➐➑➈➉
French ➊➋➌➍➎➅➆➇➈➉

💻 Work Experience

Research @ Universiti Teknologi Malaysia

Sept 2020 - Current

Full Time Research Assistant

Work with Dr. Chan Weng Howe's research team, focusing on the applied computing and computational intelligence researches.
Projects:

Modular Housing Design
A collaborative project involving Faculty of Engineering and Faculty of Built Environment & Surveying, focusing on developing genetic algorithm (GA) based multi-objective algorithm to optimize the identified variables (in terms of modular housing design and wall finishes) towards achieving near-optimal cost and sustainability.
Cancer classification using gene expression data
Applying ensemble machine learning technique and penalization method to select the informative gene for cancer classification.

Coronatracker

April 2020 - Current

Artificial Intelligence Team Member

CORONATRACKER.com is a community-based project and it is the only independent COVID-19 platform recognized by WHO.
Projects:

Differentiating country COVID-19 rates by demographic factors
Transportation/network model (flights/telco) to predict COVID-19 trends

Brain Mapping Unit @ University of Cambridge

September 2019 - January 2020

Research Intern (Neuroimaging Analysis)

Supervisor: Prof John Suckling, Director of Research
Research Area:Computer Vision, Machine Learning, Neuroimaging Analysis
Achievements:

Developed a Convolutional Autoencoder model that produces latent representation of functional connectivity with lower dimensionality.
Publish review paper (on-going).