Ayden Narayan — Software Engineer

Open to SWE Internships · Melbourne, AU

Ayden Narayan

3rd-year Mathematics & Advanced Computer Science student at Monash University.


Who I am

Hi, my name is Ayden and I'm a Mathematics and Advanced Computer Science student at Monash University building strong fundamentals across software engineering, systems, machine learning and actively research within the space of quantum approaches to inference within Bayesian networks.

Outside of this space, I also really enjoy music. From following trends in the space, to understanding how innovation is achieved in such a creative space where the audience perceives art through sound, visuals, and surprisingly social issues which we face in our contemporary landscape.

University
Monash University
Degree
B.CompSci Adv (Honours)
Location
Melbourne, AU

What I work with

Languages
Python Java C JavaScript HTML/CSS SQL
Tools
Git Linux / Bash VS Code Cloudflare Workers Docker
Coursework (CS)
Adv Algorithms & DS Computer Architecture Databases Parallel Computation OOP Design and Implementation
Coursework (Math)
Adv Calculus III Adv Linear Algebra Real Analysis Complex Analysis Network Mathematics Theory of Computation

What I've built

Bayesian Network Inference Engine

Implemented junction tree (clique tree) inference using the Hugin / Lauritzen–Spiegelhalter message-passing algorithm in Python. Built clique potentials, separator set operations, and a two-phase collect–distribute propagation loop from scratch. Demonstrated on the classic Asia diagnostic network with full support for evidence insertion and marginal query answering over arbitrary variables.

Note that as this is a current research project I am involved in, this means that the souce code related to this project will not be available at this current stage.

Python Probabilistic Graphical Models Message Passing Bayesian Inference
Random Fourier Features Research Project
github ↗

Investigated the use of Random Fourier Features (RFF) to improve the scalability of kernel-based machine learning algorithms. Designed and implemented experiments examining the trade-off between computational efficiency and predictive accuracy when approximating kernel functions with randomized feature mappings.

Analysed theoretical foundations from contemporary research and validated findings through empirical testing, data visualisation, and performance benchmarking. The project demonstrated how advanced mathematical techniques can enable large-scale machine learning systems to achieve near-kernel performance while significantly reducing computational complexity.

Key areas included kernel approximation, feature engineering, statistical learning theory, and scientific computing.

Python Machine Learning Kernel Methods NumPy SciPy Matplotlib
Simulation of Elden Ring

Developed a Java-based simulation inspired by Elden Ring, building a custom game engine to model core gameplay mechanics using object-oriented design principles.

Implemented and integrated over ten gameplay features, including character interactions, combat systems, item management, and world mechanics, with a strong emphasis on modularity, extensibility, and clean software architecture.

Collaborated within a team of four using Git-based workflows to coordinate development, manage version control, and maintain a scalable codebase throughout t he project lifecycle.

Note that as this project relates to a past assignment, the source code is unable to be disclosed. This has been one of my favourite projects to work on and I am more than happy to discuss this further :)

Java Object Oriented Programming Game Design Agile model

Where I've been

2025 — Present
Access Monash Mentor Leader
Monash University
As an Access Monash Mentor Leader, I led and supported a team of peer mentors in delivering structured mentoring sessions designed to improve the transition experience for commencing students. I took responsibility for coordinating mentor activities, ensuring consistency and quality across sessions, and fostering an inclusive, supportive environment that encouraged student engagement and confidence.

I acted as a key point of contact between mentors and program coordinators, helping to streamline communication, resolve issues efficiently, and maintain smooth program delivery. Beyond operational coordination, I contributed to shaping session delivery by guiding mentors in best practices for student support and engagement, with a focus on accessibility and early university success.

Through this role, I helped strengthen the impact of the Access Monash program by improving mentor effectiveness, enhancing session consistency, and supporting a positive transition experience for first-year students.
2024 — Present
Sales Supervisor
Delaware North
Progressed from Sales Assistant to Sales Supervisor within a high-volume stadium retail environment, demonstrating strong leadership, operational management, and customer service capabilities.

Responsible for supervising retail staff, coordinating day-to-day operations during major sporting and entertainment events, resolving customer escalations, and ensuring efficient transaction processing under significant time pressure.

Contributed to sales growth by maintaining high merchandising standards, supporting team performance, and delivering exceptional customer experiences in fast-paced, high-traffic settings.

Where I studied

2024 — 2027
Bachelor of Computer Science
Monash University
Specialising in Advanced Computer Science and majoring in Mathematics

Let's talk

I'm actively looking for software engineering internship opportunities. If you're hiring or want to chat, I'd love to hear from you. OR if you are interested in having a conversation with me related to music, I am more than happy to have a chat.