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"Success is a lousy teacher. It seduces smart people into thinking they can't lose."

Bill Gates

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About me

Hello World!

I'm a final year Computer Engineering student at the Nanyang Technological University (NTU) and I'm currently pursuing a minor in Mathematics (Statistics). I'm interested in the field of Machine Learning, Deep Learning, and Artificial Intelligence.

I'm currently doing my Final Year Project titled 'AI for Healthcare', focusing on mental health, detecting depression and emotions from text data using deep learning techniques.

I love to tackle challenging problems even though the process may be tough at times. I believe that having challenges along the way gives me valuable experiences, which cannot be obtained from theory or conventional classes. I'm also eager to learn new skills and I believe that learning never stops even when I've graduated from university.

Skills

LANGUAGES


SKILLS

MySQL | MongoDB | Git | Tensorflow | PyTorch | Scikit-learn | Pandas | Numpy | Scipy | Flask | AWS EC2/S3

Work Experience

INFO-COMMUNICATIONS MEDIA DEVELOPMENT AUTHORITY (IMDA)

DATA ANALYTICS INTERN

May 2019 - Aug 2019

Under the Customer Experience Platform Division, I'm in charge of the Machine Learning segment of the project. I analyse datasets given by the client and provide insights out of it. I also made use of the dataset to draw relevant correlations and to do predictions.

I've collaborated with UI/UX Engineer and Software Engineer to formulate a F&B recommendation engine project. Researched on collaborative filtering and content-based filtering algorithm for the recommendation system.

I'm also exposed to graph theory and the algorithms to implement our project using neo4j, a graph database tool for knowledge graph. Using neo4j, I'm able to draw relations between different classes of objects and visualise it in a graphical format with nodes and edges. I also learnt how to do software testings, how to write a good software and how to deploy the application from experienced Software Engineers.

During the 3 months in IMDA, I've learnt about the whole Software Engineering pipeline as well as the agile methodology using SCRUM which makes the deployment and planning of tasks much easier.

Projects/Competitions

ACADEMIC

Final Year Project

Jan 2021 - Present

  • Title: AI for Healthcare – Detecting Depression and its Emotion from Text.
  • Detect signs of depression and emotions from text data through sentiment analysis using Deep Learning and NLP techniques.
  • Researching on Emotion-Cause Pair Extraction from text clauses in the depression context.

Information Retrieval System for Sentiment Analysis

Jan 2021 - Apr 2021

  • Built a search engine from scatch in the restaurant food domain aimed at retrieving the comments and sentiments of users through querying the user interface
  • Crawled through 97,190 entries with 137,499 unique words for the search engine using Python and BeautifulSoup.
  • Trained a BERT model using Tensorflow to do sentiment classification with validation accuracy 92.78%, weighted average F1-score of 0.95 and AUC of 0.8341.
  • Explored Aspect-based Sentiment Analysis and Named-Entity Recognition to enhance the classification task.

Next "Singlish" Sentence Generator

Aug 2020 - Nov 2020

  • Implemented a Natural Language Generation (NLG) project that uses English texts with some Singlish words.
  • Started the project from scratch (from scraping the data to training the model) using Tensorflow 2 (Python).
  • Trained a GPT-2 model in Google Colaboratory to generate coherent sentences.

PAT-A-PET

Jan 2020 - Apr 2020

  • Implemented an Android application about pet-boarding using Android Studio (Java).
  • Led a team of 5 members and implemented various application features which includes chat box, chat list, view/edit user’s profile, Firebase and incorporating government’s API on veterinaries in Singapore and Google Map API.


OTHERS

Depression Information Chatbot (Pet Project)

Jul 2021

  • Chatbot application built using Flask, HTML and jQuery which aims to provide information about depression and generate jokes and motivational quotes.
  • Trained a feed-forward neural network using the Pytorch framework.

DSTA BrainHack - Today I Learnt 2021 Competition (Hackathon)

Jun 2021

  • Unlocked all six challenges consisting of Sound Classification and Computer Vision Problems.
  • Adopted both the data and model centric approach to solve the challenges.
  • Trained various models using the Pytorch framework.
  • Achieved Top 8 for this competition.

Shopee Ultra Hackathon 2021

Jan 2021

  • Developed an application that aims to change the interface of the Shopee mobile application and to introduce some features to increase user engagement.
  • Responsible for the translator and search bar components which uses the dart translator API.
  • Coded in Flutter/Dart.

Next Word Predictor

Jun 2020 – Jul 2020

  • Researched and trained a language model that takes in a user input (word/phrase/sentence) and predict the top next matching word and the next three best alternative word using Katz Back-off Model.
  • Deployed into a webpage using shinyapps.io and coded using R programming.

DSTA BrainHack - Today I Learnt 2020 Competition (Hackathon)

Jun 2020

  • Trained models for Computer Vision (CV) and Natural Language Processing (NLP) problems posed in the competition.
  • Achieved 11th position for the Kaggle competition in the NLP segment, with an accuracy of 98.607% private score.

Share for Food Webpage (Hackathon)

Feb 2020

  • Developed a webpage for food stalls in NTU to donate their leftover food to local charity organisations.
  • Executed our plan with HTML/CSS/Javascript for the logic and user interface.
  • Deployed Firebase database to store the information of the stall owners and the charity organisations.

MOOCs Taken

I'm an active learner! Whenever I'm free, I will head over to MOOC to learn new skills and gain new knowledge. Some notable MOOCs that I've taken are as shown below...

Contact Me


LinkedIn

GitHub

Email