My Curriculum Vitae

National University of Singapore
Singapore

Aug 2022 - Present

Politechnika Warszawska
Warsaw, Poland

Feb 2025 - July 2025

Fountainhead School
Surat, India

May 2020 - May 2022

Impact Experience Project

A two-year $20k team project to improve waste management standards in rural Cambodia in collaboration with the Young Eco Ambassador organisation, consisting of managing the logistics, infrastructure, and execution of a Bring Your Own Container programme and a corresponding awareness campaign to reduce plastic waste. Done as part of the NUS College Impact Experience programme (NEP3001).

rusTuring Machine

Github repo

A Turing machine simulator programmed in Rust for NST2056 (Computing Machines, Models, and the Mind)

HouR - Employee Management Platform

Github repo

A 12 kLoC GUI-based interactive desktop application for employee records management optimised for CLI usage. Has commands to add, edit, and delete employee records, manage their leaves and overtime hours, and track their metrics. Created for CS2103T (Software Engineering).

Kronos Task Manager

Github repo

A GUI-based interactive task manager with a chat interface and local storage capabilities, created for CS2103T (Software Engineering).

StarSnap

Github repo | Final report | Google Colab notebook

An integrated React web app consisting of a multiclass classification neural network to identify constellations, an astrophotography forum, a learning tab, and a personal gallery of astronomy photos.
Built using React.js and Chakra UI for the front-end, Redux for application state management, Supabase (a serverless database provider) for relational database management, PyTorch with PyTorch Lightning for creating and training the model, and Flask to make a REST API to send requests to the model. Created for CP2106 (Independent Software Development Project)

LiveIron

Github repo

A performant, extensible cellular automata simulator library with visualisation capabilities built in Rust. Supports evolving cellular automata using genetic algorithms, as conceptualised by Mitchell et al.

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Tools, Languages, and Frameworks

I have experience with the following tools (in decreasing order of proficiency within each section and sub-section):

Programming

• Java: The language of choice for most of my NUS coursework, including DSA, programming methodology (OOP), and SWE. I've slowly come to appreciate its type safety, even if it's a little verbose at times. A little annoying to use for functional programming with all of its monads and functors, but I've managed to get by.
• JUnit: Used it to test all of my Java apps. Has been a godsend for creating tests. I appreciate its simplicity and versatility.
• JavaFX: Used it in the SWE course to build UIs for two projects. Felt extremely tedious. I will probably stick to other languages for my UI needs.
• Python: My go-to language for most of my machine learning personal projects. I'm quite comfortable with its data science stack, although I probably need to develop better testing practices.
• NumPy, Pandas, Matplotlib: Pretty familiar with these libraries. I've used them for most of my data transformation and visualisation needs.
• PyTorch: Having done a few projects with it, it's my go-to deep learning framework; it feels more object-oriented and Pythonic than TensorFlow. I often use high-level interfaces on PyTorch, like PyTorch Lightning to reduce boilerplate.
• TensorFlow: I've used it for a few projects, but I'm not as comfortable with it as I am with PyTorch. Keras makes it really quick to whip up a model though.
• Flask: I've used it to handle requests and connect frontend inputs to ML models in a few web dev projects. Sort of familiar with its basic functions, and never really felt the need to go much deeper
• SciKit-Learn: I used it in my early days of learning ML. I don't really use it anymore.
• Rust: Extremely fascinating language in how it combines high performance with memory safety. I'm familiar with the basics, but I sometimes run afoul of the borrow checker when using generics or traits. It has also given me an opportunity to learn to implement from scratch some of the features I take for granted in other languages.
• Dioxus: A Rust library for creating desktop interfaces. I've used it for visualisation purposes in a few projects.
• Polars: A powerful Rust equivalent of Pandas. I've used it for data management in an ML project and found it a little limited in its functionality compared to Pandas, but it's still promising.
• Rocket: A web framework for Rust. I've used it in a few web dev projects, and I've found it quite intuitive.
• Reqwest: A HTTP client for Rust. Used it for a Hackathon once. Found it straightforward.
• JavaScript: I'm very comfortable with JavaScript, having used it for years in most of my web dev projects. I found it quite painful to debug due to its weak dynamic typing, but TypeScript has made it much more bearable and straightforward, even if at the cost of a little more verbosity.
• React: Very familiar with it. Was initially a little sceptical, but it has become my go-to language for building dynamic websites.
• jQuery: Used it a lot when I was first learning JS and web dev. However, as I learnt more JS and React, it has become largely superfluous. I only use it now once every few months to maintain some of my older projects.
• Unity, C#: I've used Unity for developing UIs for mixed reality wearables for an internship. I can use it for specific projects, but I'm not very comfortable with it.
• SQL: Familiar with the basics of SQL and similar RDBMS's, including PostgreSQL and MySQL. Used it in a few web dev projects to manage databases.
• Ruby: I'm familiar with the basics of Ruby, but I haven't used it much by itself, mostly using it in Rails projects.
• Ruby on Rails: Not my first choice for backend, but I've used it in a few web dev projects. I appreciate its simplicity and convention over configuration approach, but the MVC pattern seems overly complicated for smaller projects.
• HTML/CSS: I'm familiar with the basics of HTML and CSS, but often find myself looking up the docs for most features. I'd rather use JS libraries like React now.
• PHP: I'm familiar with the basics of request handling using PHP, but it always seemed overly verbose and complicated to me. I've used it in a few web dev projects before I found out about backend managment in JS and Python, but I've never really enjoyed using it.
• MATLAB: I've used it for mathematical computation in courses like linear algebra.
• C: I've used it for courses like computer organisation.
• R: I've only used it for my quantitative reasoning course.

Others

• Git/GitHub: Probably my most-used software after my code editor. I use it for version control in most of my projects, and I'm quite comfortable with it.
• Microsoft Office Suite: I use it for most of my coursework. Also, I spend a lot of time adding pointless animations to PPTs to compensate for my lack of presentation skills.
• LaTeX: I use it for taking notes and writing reports. I'm kinda comfortable with it, though I need to look up the docs often.
• Postman: I use it to test my API endpoints, although I haven't used it in a while.
• Radiant: Learnt it for my quantitative reasoning course. When my knowledge of Excel formulae fails me, I use Radiant to do some basic data visualisation.
• Canva: I've used it a couple times to make posters and infographics for NUSC courses. I'm terrible at designing them though.

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Coursework

Here are the courses I have taken at NUS (in reverse chronological order within each section):

Computing & Mathematics

• CS3264 - Foundations of Machine Learning
• CS3230 - Design and Analysis of Algorithms
• CS2109S - Introduction to AI & Machine Learning
• CS2105 - Computer Networks
• CP3209R - Undergraduate Research in Computing
• CS2100 - Computer Organisation
• CS2103T - Software Engineering
• CS2101 - Effective Communication for Computing Professionals
• ST2334 - Statistics and Probability
• CP2106 - Independent Software Development Project
• CS2040S - Data Structures and Algorithms
• CS2030S - Programming Methodology II
• IS1108 - Digital Ethics & Data Privacy
• MA2001 - Linear Algebra I
• CS1231S - Discrete Structures
• CS1101S - Programming Methodology I
• MA1521 - Calculus for Computing
• GEA1000N - Quantitative Reasoning with Data

NUS College

• NHS2076 - What Can I Know?
• NST2051 - Friction: May the Force Be With You
• NGT2001 - Global Social Thought
• NST2056 - Computing Machines, Models, and the Mind
• NHS2071 - Beyond Belief: Religious Experience & Encounter
• NEP3001 - Impact Experience Project
• NSS2001 - Science and Society
• NSW2001 - Understanding the Social World: Singapore & Beyond
• NGN2001 - Global Narratives
• NTW2001 - Thinking with Writing: The Social Life of Science

Astronomy

• PC2411 - Practical Astronomy

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