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SABAH, MALAYSIA / PUBLIC ADMINISTRATION + TECHNOLOGY

Ahmad Hazwan bin Abinan

Data. AI.
Public service.

I bring public administration and data science together to build practical tools, understand complex problems, and support better decisions.

PUBLIC ADMINISTRATION / MSc DATA SCIENCE, UNIVERSITY OF EXETERSCROLL TO EXPLORE ↓
Ahmad Hazwan bin Abinan

An administrative perspective.
A technical foundation.

I currently serve the Sabah State Government. My MSc studies in Data Science at the University of Exeter connect that public service experience with hands-on work in analytics, machine learning and AI.

I am interested in what happens beyond a promising prototype: how a system performs in a real setting, how people use it, and how it can be operated responsibly.

University of ExeterMaster of Science in Data Science · 2025–2026
University of MalayaBachelor of Engineering · Manufacturing Engineering · 2008–2012

PUBLIC-SERVICE EXPERIENCE

Ministry of Local Government and Housing2020–2025
Sabah State Public Service Commission2018–2020
[ 01 ]

Data & development

Python, data preparation and data systems. Turning messy inputs into usable foundations.

PythonData systemsAutomation
[ 02 ]

Analytics & machine learning

Model development, evaluation and site calibration, with a focus on real-world performance.

Machine learningComputer visionEdge AI
[ 03 ]

Strategy & governance

Evidence-based decisions, strategic and workforce analytics, data ethics and human oversight.

Strategic analyticsData ethicsHuman review

From research to reality.

Technical case studies in English
FEATURED / MSc RESEARCH2026

Parking occupancy.
Beyond the benchmark.

Can a parking detection system stay useful when it leaves a benchmark dataset and runs on embedded hardware at a real site?

Computer visionRaspberry Pi 5Site calibration
Read the case study
Parking occupancy system dashboard showing the lot schematic, camera view, occupancy status and active model
LIVE SYSTEM / RASPBERRY PI 5

Operational dashboard linking model output, parking-space geometry and the live camera view.

Technical case study

Parking Occupancy Detection on Embedded Hardware: Accuracy, Efficiency, Transferability and Site Calibration

Problem & role

My MSc research examined parking occupancy detection across model families and datasets, with deployment on a Raspberry Pi 5. The work covered model development, evaluation, transferability and local calibration.

Technical approach

Classical machine learning, CNN/transformer models, object detection and vision-language models were explored. On-device deployment tested the practical relationship between accuracy and computational efficiency.

What I learned

Performance on benchmark data did not reliably transfer to a new site. Local calibration and evaluation across daytime and night-time conditions were central to making the system useful in practice.

Responsible operation

The operational design considered monitoring, retraining, performance-gated promotion and rollback. On-device inference and aggregate occupancy outputs support an approach focused on spaces, rather than identifying people.

Research project; this case study does not claim deployment as a Sabah government service. The linked project environments may require access.

Useful possibilities for Sabah.

PROPOSED APPLICATIONS

Areas where I would like to contribute, combining an understanding of administration with practical data and AI skills.

↗ 01

Find the right information

Search circulars and working documents with source references and access controls that respect each officer’s permissions.

Permission-aware search · citations
↗ 02

Understand service delivery

Use licensing, process and workforce data to understand delays, track meaningful indicators and support better resource decisions.

Process analytics · workforce insights
↗ 03

Observe facilities responsibly

Explore on-device AI for facilities and public assets, using aggregate insights and proportionate data collection.

Edge AI · privacy by design

These are proposals for exploration, subject to approval, data protection, risk assessment and human oversight.

Ahmad Hazwan bin Abinan on an autumn evening in Exeter

Build thoughtfully.
Check what matters.

I use Python and AI-assisted development tools, including Codex and Claude Code, for prototyping, automation, documentation and testing. Human review, data security and appropriate governance remain part of the work.

PythonCodexClaude CodeTesting & review

Let’s start a
conversation.

For professional conversations, research and ideas worth exploring.

DIRECT MESSAGE

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