I'm an aspiring Machine Learning Engineer and Researcher with a deep love for machine learning and a fascination with understanding how algorithms work. To me, machine learning is a form of art; capturing the intricate ways we think, perceive, and learn and mapping it all into mathematical representations is truly beautiful and inspiring. My journey began during my undergraduate studies, where I discovered the true beauty of the art behind these algorithms.

Currently focused on deep learning applications in natural language processing and recommendation systems (and a little bit of computer vision), I'm constantly expanding my knowledge through hands-on projects, research, and collaboration with the AI community.

My goal is to contribute to cutting-edge research while building practical AI systems that are ethical, explainable, and beneficial to society.

• Nanyang Technological University, Singapore
  • Bachelor of Engineering (Honours) in Electrical and Electronic Engineering
  • Specialising in Data Analysis and Machine Learning

• Evooq Pte. Ltd.
  • Large Language Model Developer Intern
• Panasonic
  • AI Deep Learning Software Developer Intern

• NTU Course Recommender Chatbot
  • Part of my undergrad Final Year Project
  • Conversational RAG chatbot that gives you information about NTU's undergraduate programmes. It can also provide you with programme recommendations based on your academic background, among other things.
  • LangChain, Ollama, DeepSeek, Python, Hugging Face
  • Previously: Python, Hugging Face, LangChain, Llama, Mistral, Groq
• Bobby the Chatbot
  • This was for one of my uni modules, "Design Innovation Project". We built a web application, and I developed the chatbot for it.
  • Python, OpenAI SDK
• AI Data Analyst Assistant
  • I developed an AI assistant that returns the user stock prices that they ask for. Comes with voice audio.
  • Did this for an internship application. Managed to impress the CTO with this during the interview and landed the internship.
  • Python, OpenAI SDK, Streamlit

• Recommendation System for NTU Aptitude-Based Admissions (ABA) applicants
  • Built a recommendation system that recommends appropriate schools in NTU to ABA applicants based on their interests, strengths, and academic background.
  • Collaborative Filtering using Probability Matrix Factorisation, Content-based Filtering via computing cosine similarity of BERT embeddings of user interests with school descriptions, Weighted Hybrid System of both filtering algorithms.
  • Tons of libraries (Pandas, Numpy, Hugging Face, NLTK, Matplotlib, ...)
• Information Extraction / Question-Answering Bot
  • Without using LLMs
  • Part of a project for my university module "Natural Language Processing".
  • Built a machine learning model that extracts key information from the lecture transcripts when given a user query (kinda like Google)
  • Experimented with different ways to do this, such as utilising a BERT-based NER model, a simple TF-IDF + cosine similarity, and finally fine-tuning BERT variants on the SQuAD dataset + our curated dataset
  • Conducted extensive hyperparameter tuning to achieve more than 90% accuracy of the model
• Face Recognition
  • Part of my university module "Intelligent Systems Design".
  • Collaborated with 6 other EEE students to design and build face recognition systems using (1) traditional machine learning methods like Principal Component Analysis and (2) deep learning techniques like MTCNN
  • Python, OpenCV
• Dogs vs Cats Classifier
  • Part of my university module "Artificial Intelligence and Data Mining". Got a 'B+'.
  • I collaborate with 2 other EEE students to design and develop a convolutional neural network (CNN) that accurately classifies images of dogs and cats.
  • We performed some data augmentation techniques on the image dataset to expand it, and we conducted extensive hyperparameter tuning on the machine learning model to optimise its performance.
  • Python, PyTorch, NumPy
• Handwritten Digit Recogniser Web Application
  • I designed and constructed a convolutional neural network (CNN) using Pytorch that can identify handwritten digits given by the user in this web application.
  • Python, PyTorch, Flask, HTML, CSS JavaScript
• NTU Undergraduate Research Opportunity Programme (UROP)
  • I conducted a research project under my university's UROP. The title of my project is "Dummy Data Generation and Data Augmentation Using Machine Learning".
  • I explored the use of generative adversarial networks (GANs) and neural style transfer for the purposes of data augmentation.
  • Python, PyTorch, NumPy, Matplotlib

more coming soon...

• Dental Clinic Website
  • Part of my university module "Web Application Design". Got an 'A'.
  • I collaborate with a fellow EEE student to design and build a web application for a dental clinic that we call Radiant Smiles Dental.
  • HTML, CSS, JavaScript, PHP, MySQL
• Web Application Design Case Study
  • Part of my university module "Web Application Design".
  • I collaborate with a fellow EEE student to architect and develop a web application according to a case study's requirements. The case study is about building a website for a coffee house. The project involves a webpage that allows the customer to submit orders, and webpages for the manager to update prices and get a sales report.
  • HTML, CSS, JavaScript, PHP, MySQL

more coming soon...