Sydney, Australia Open to opportunities

AI student · IT problem-solver · systems thinker

I like turning messy problems into
clear systems.

I’m Behrad. I study Artificial Intelligence, build practical digital tools, and care about making complicated things genuinely easier to use.

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Artificial intelligencePractical problem-solving Human-centred systemsWorldbuilding Artificial intelligencePractical problem-solving Human-centred systemsWorldbuilding
01 / About

The short version

Curious by default.
Practical by choice.

I’m an Artificial Intelligence major at Macquarie University with a hands-on background in IT support.

Before university, I spent two years helping students and staff solve real technology problems—from hardware and software troubleshooting to digital classrooms and day-to-day support. That experience shaped how I approach tech now: start with the person, understand the real problem, then make the solution clear.

I’m bilingual in English and Persian, comfortable across macOS, Windows, and Linux, and happiest when I’m learning something complex enough to pull apart and rebuild.

02

Years of hands-on
IT support experience

03

Operating systems:
macOS, Windows, Linux

02

Languages spoken:
English + Persian

27

Expected graduation
from Macquarie

02 / Selected work

Things I’ve worked through

Selected systems.

A mix of AI, networking, data, and tools designed to solve actual problems.

01

Network architecture

Multi-site healthcare network

Designed an eight-site network with VLANs, subnetting, routing, a data centre, and end-to-end validation.

CiscoVLANsRouting
02

Applied AI concept

AI Home Energy Companion

Developed an evaluation framework for an AI product designed to improve household energy decisions.

AIKPIsSDG 7 + 13
03

AI search & reasoning

Intelligent puzzle solver

Compared search strategies—including IDS, A*, and beam search—through implementation and evaluation.

PythonA*Evaluation
03 / Mindset

How I work

I don’t just want
the answer. I want the
mental model.

My best work happens when I can see the whole system, break it into manageable parts, test my understanding, and then explain it simply.

  1. 01
    Map the system

    Find the parts, constraints, and connections.

  2. 02
    Make it concrete

    Turn theory into a diagram, prototype, or working example.

  3. 03
    Stress-test it

    Use questions, edge cases, and iteration to find weak points.

  4. 04
    Make it clear

    If the explanation is confusing, the thinking probably is too.

04 / Beyond the screen

Systems are everywhere—even in the things I do for fun.

01

Worldbuilding

Characters, rules, choices, and stories that feel alive.

02

Games

Buildcraft, strategy, and understanding what makes a system tick.

03

Learning

Turning unfamiliar topics into something I can use and explain.

Currently in Sydney · Studying AI · Building what’s next

Have a problem worth
thinking about?

Let’s talk
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