CV

Bachelor of Computing (Computer Science) with Honours (Highest Distinction)

National University of Singapore (NUS)

Focus Area: Distinction in Artificial Intelligence; Double Degree Programmes Specialisation: Multimedia Modelling

• Grade: 4.84/5.00
• Undergraduate Dissertation: Automated ECG Diagnosis using an Explainable AI Framework (Advised by Prof Brian Y. Lim)

Bachelor of Science (Applied Mathematics) with Merit

National University of Singapore (NUS)

• Grade: 4.91/5.00

Dean's List

School of Computing, NUS

Top 5% at School of Computing, NUS

Distinction in the Artificial Intelligence Focus Area

School of Computing, NUS

Achieved an average grade of 4.5/5.0 or above in at least three AI-related modules

Outstanding Performance in Machine Learning

School of Computing, NUS

Placed among the top students in a class of 291 students

Outstanding Performance in Computer Graphics

School of Computing, NUS

Placed among the top students (first place) in a class of 171 students

Outstanding Performance in Design and Analysis of Algorithms

School of Computing, NUS

Placed among the top students in a class of 263 students

Dean's List

Faculty of Science, NUS

Top 5% at Faculty of Science, NUS

Science and Technology Undergraduate Scholarship

jointly awarded by NUS and Singapore Ministry of Education

A merit-based full scholarship (~150K USD), covering tuition fees, accommodation, and living expenses

Research Assistant (Supervisor: Prof. B.T. Thomas Yeo)

Center for Translational Magnetic Resonance Research (TMR), NUS

Responsibility: analyze functional magnetic resonance imaging (fMRI) data using statistical, computational, and machine learning models; manage our center's research informatics system and High-Performance Computing (HPC) infrastructure

• Conducted experiments to improve the mean-field model (MFM), a computational model for simulating and understanding human brain dynamics.
• Currently developing a generalized additive model (GAM) to investigate how the E/I ratio, a key indicator of brain health estimated by the MFM, evolves across the human lifespan.
• Containerized our fMRI preprocessing pipeline with Docker and Singularity for cross-platform consistency.
• Developed an automated tool that generates intuitive MRI reports, helping patients compare their brain condition to others of the same age (expected to be used in a large hospital serving millions annually)
• Maintaining the website and server of XNAT, the platform that manages and stores our MRI imaging data.

Undergraduate Researcher (Advisor: Prof. Brian Y. Lim)

Ubicomp Lab, School of Computing, NUS

Developed an explainable AI framework that aligns AI predictions with clinical reasoning in electrocardiogram (ECG) diagnosis, providing clinically relevant explanations to support doctors' decision-making.

• Currently extending the framework to other rule-based domains with a user-friendly interface for customizing and integrating logical rules into interpretable AI models.

Research Intern (Advisor: Prof. B.T. Thomas Yeo)

Computational Brain Imaging Group, Yong Loo Lin School of Medicine, NUS

Explored with various machine learning models, such as graph neural networks (GNNs), to accelerate the parameter optimization process for the aforementioned computational model MFM.

• Improved the computational efficiency by 5,000 times while preserving simulation accuracy and the MFM's mechanistic insights into brain function.

Optimizing Biophysically-Plausible Large-Scale Circuit ModelsWith Deep Neural Networks

to be submitted to Nature Methods

Tianchu Zeng*, Fang Tian*, Shaoshi Zhang, Gustavo Deco, Theodore Satterthwaite, Avram Holmes, B.T. Thomas Yeo (* indicates equal contribution)

Aligning AI models with Editable Explanations (In Progress)

to be submitted to User Interface Software and Technology (UIST), 2025

Fang Tian, Haoyang Chen, Jingwen Bai, Brian Y. Lim

Automated ECG Diagnosis using an Explainable AI Framework

Final Year Project (undergraduate dissertation), NUS

Fang Tian, Brian Y. Lim

Teaching Assistant, CS3244 Machine Learning

School of Computing, NUS

Conducted tutorial sessions, mentored student projects, and set examination papersn

Tutor

Sunbeam Place, Singapore

Teach children in the foster care home to program in Python and build a Telegram application on their own

Storyteller

an iPad application that simplifies storyboard creation for independent filmmakers. As the core developer and project leader, I implemented advanced features like layer management with elegant software design patterns, while effectively managing the team and ensuring timely milestone delivery.

• Built with Swift and UIkit
• Implement shot designer (PencilKit) with layer support (Composite+Visitor Patterns)
• Heavy use of OOP & SOLID principles

WottleNFT

a Cardano non-fungible token (NFT) marketplace. In this student-initiated startup, I led the front-end development, utilizing Next.js, Ionic, Next SEO, and Tailwind CSS to deliver optimized performance, an intuitive interface, enhanced search engine optimization (SEO), and responsive design.

• Exchange ideas with the design team using Figma
• Search Engine Optimization with Open Graph support (Next SEO)
• Achieve native look and feel using Ionic framework
• Optimize image loading and webpage navigation using Next.js
• Responsive design using Tailwind

Lunaris

a native iOS client for NUS's course management system (LumiNUS), offering an intuitive interface for browsing modules, downloading files, and managing tasks. This project received the Orbital-Advanced certificate.

Ocean-Peggle

a feature-rich iOS Peggle-inspired game, featuring a custom physics engine, complex ball dynamics, and intricate level mechanics—all developed within an ambitious two-month sprint.