Pak Him (Ryan) Kwok

Undergraduate majoring in Artificial intelligence and Computer Science at the University of Edinburgh. An enthusiast with a burning passion for understanding various fields of AI and wants to pursue a career involving AI and machine learning.

• 10/2022, Data Science And Machine Learning: Making Data Driven Decisions
• 07/2023, Microsoft Certified: Azure Al Fundamentals
• 08/2023, Machine Learning with Python

• 10/2024, 01/2025, ProjectX 2024 (University of Toronto)

Write a research paper on Multimodal AI. We chose the focus area: Data fusion on Multimodal AI.

• 09/2024, 09/2024, Robust 3D Occupancy Perception with Thermal Image for Autonomous Driving

The project aims to exploits the illumination-independent sensing ability of thermal cameras to achieve robust occupancy perception under visual degradation for high-level autonomous driving. 

• 08/2024, 08/2024, Computer Vision Project on Lumbosacral Radiographs

The project is currently in early stages of development. My task was to implement an object detection/semantic segmentation model on lumbosacral radiographs. 

• 06/2024, 08/2024, 2D Floorplan Map

Reconstruct the entire floor scene using LiDAR. Create a top-down view based on it and enclose the whole region with a box. 

• 01/2024,03/2024, System Design Project

The System Design Project is intended to give students practical experience of (a) building a large scale system (b) working as members of a team. The project involves applying and combining material from several courses to complete a complex design and implementation task. At the end of course each group demonstrates its implemented system and gives a formal presentation to an audience of the students, supervisors, and visitors from industry.

• 08/2023, 08/2023, Rain Prediction in Australia

The objective of the project is to build a classifier to predict whether there will be rain the following day using the rainfall dataset from Australian Government's Bureau of Meteorology. The following algorithms are used: 1. Linear Regression 2. KNN 3. Decision Trees 4. Logistic Regression 5. SVM The results are reported as the accuracy of each classifier, using the following metrics, when these are applicable: 1. Accuracy Score 2. Jaccard Index 3. F1-Score 4. Log Loss 5. Mean Absolute Error 6. Mean Squared Error 7. R2-

Score 

• 08/2022, 09/2022, Netflix Movie Recommendation

The objective of this project is to build a recommendation system to recommend movies to users based on the ratings given to different movies by the users. 

• 08/2022, 09/2022 New York Taxi Trip Duration Prediction

The objective of this Project is to build a predictive model, which will help in predicting the duration of a taxi trip in NYC. We have to create new features using feature engineering and build a model with good performance.

• 07/2022, 08/2022, Pima Indians Diabetes Analysis

To analyse different aspects of Diabetes in the Pima Indians tribe.