Muhammad Aiman bin Jamaluddin · Bachelor of Computer Science (Hons.)

Machine Learning,
Explainable AI &
Full-Stack Systems.

Computer Science (Hons.) student at UiTM with prior industry internship experience and hands-on work in machine learning, explainable AI, and full-stack web development. Seeking a 14-week Software, Data, or AI Intern placement from 15 March to 18 June 2027.

Internship: 15 Mar – 18 Jun 2027 Klang Valley (PJ & Shah Alam) aiman_jamaluddin@outlook.com +60 11-3991 0856
Muhammad Aiman bin Jamaluddin
Muhammad Aiman bin Jamaluddin UiTM Computer Science (Hons.) · @CaribbeanGreen
0
KTMB ETS trip records modeled
4.1%
Network MAPE (vs 6.4% baseline)
0.92
AUC on fine-tuned PyTorch LaBSE
3.25
Diploma CGPA · Dean's List

Core Focus & Technical Stack

AI & Data Science at the core. Full-stack ready.

Structured directly around the technologies, research tools, and engineering domains from my academic and industry work.

★ Core Engineering Focus

AI, Machine Learning & Data Science

For data science, ML engineering, or analytics teams building forecasting, NLP, or explainable AI pipelines. Proven on 2.2M+ rows of real-world Malaysian transport data and an 11,000-text literary corpus.

  • Random Forest & TreeSHAP implemented from scratch in pure NumPy and verified against brute-force Shapley values
  • PyTorch contrastive fine-tuning with Hugging Face sentence-transformers (LaBSE, raising held-out AUC from 0.65 to 0.92)
  • Local LLM (Gemma) & Gemini API evaluation pipelines for semantic scoring
  • Interactive data dashboards with pandas, scikit-learn, Streamlit and hand-written HTML/JS
  • Grade A in CSC649 Special Topics in CS & A- in CSP600 Project Formulation
01 / Languages

Programming

Python Java PHP SQL JavaScript C++
02 / Core Domain

Machine Learning & AI

scikit-learn Random Forest SHAP / TreeSHAP PyTorch pandas & NumPy Hugging Face (LaBSE) Gemma (Local LLM) Gemini
03 / Full-Stack

Web Development

PHP & CodeIgniter Java (Jakarta EE 10) JSP & Servlets MySQL & Oracle SQL HTML / CSS / Bootstrap JavaScript (PWA) GlassFish & XAMPP
04 / Environment

Tools & Analytics

Git & GitHub Streamlit Jupyter Linux Microsoft Excel (Basic) Power BI (Learning) NotebookLM
05 / Creative & IT

Design & Hardware

PC, Laptop & Printer Repair OS Formatting & Setup Adobe Photoshop Premiere Pro Canva & CapCut
06 / Research & Spoken

Research & Languages

Bahasa Melayu (Native) English (Fluent · MUET Band 4.0) Scopus & Mendeley

Shipped Work & Research

Featured Projects

Every project below links directly to its source repository or technical documentation.

Final Year Project · 2026

KTMB ETS Ridership Surge Prediction & TreeSHAP Engine

Python · NumPy · TreeSHAP · pandas · Open-Meteo API · HTML/CSS/JS dashboard

4.1% MAPE
vs 6.4% naive baseline
6.7% Festive
vs 9.4% festive baseline
01 / Explainable Machine Learning

Explainable Random Forest for KTMB ETS Ridership Surge Prediction

  • Implemented a Random Forest from scratch in NumPy, forecasting daily ridership across 21 districts on 2.2M hourly trip records (2023–2026) joined with Malaysia public holidays, DOSM demographics, and Open-Meteo weather.
  • Cut network-level forecast error to 4.1% MAPE on May–Dec 2025 test data vs 6.4% naive baseline (6.7% vs 9.4% on festive days).
  • Explained every prediction with TreeSHAP (also written from scratch in NumPy) verified against brute-force Shapley values; showed festive weeks and holiday eves raise ridership while Ramadan lowers it.
  • Built a live web dashboard with 2026 holdout evaluation, live weather fetch, and SHAP feature-contribution charts.
github.com/CaribbeanGreen/pantun-coherence
0.65 → 0.92 AUC · NLP & Deep Learning 2026 · Group Project

Pantun Pembayang–Maksud Coherence Analysis

  • Built a corpus of ~11,000 Malay pantun from published anthologies and scored pembayang–maksud coherence using five multilingual embedding models, rhyme rules, and LLM judges.
  • Fine-tuned LaBSE with PyTorch (contrastive loss), raising AUC for distinguishing real from shuffled pantun from 0.65 to 0.92 on held-out data (LLM judges scored near chance, 0.50–0.53).
  • Built a multi-role Streamlit demo with tailored views for students, lecturers, and researchers.
PythonPyTorchHugging Face (LaBSE)GemmaGeminiStreamlit
github.com/CaribbeanGreen/PulseLift-Workout-Tracker
Zero External 3D Libraries · PWA 2026

PulseLift – Workout Tracker Web App

  • Built an installable, offline-capable Progressive Web App for a 2-day full-body routine with weight and rep logging, workout history, and a rest timer.
  • Rendered interactive 3D anatomical models in plain JavaScript (no external libraries) that rotate 360° and highlight the specific muscles each exercise targets.
HTMLCSSJavaScript (PWA)WebGL
github.com/CaribbeanGreen/ChateauFido
Enterprise Java · Grade A+ 2026 · Group Project

ChateauFido – Dog Hotel Booking System

  • Built a full-stack pet-hotel booking web application featuring customer registration, dog profiles, room booking, and receipts.
  • Engineered a complete admin dashboard for bookings, reservations, rooms, and inventory across 44 Java classes and 24 JSP pages.
Java (Jakarta EE 10)JSPServletsMySQLGlassFish
Home Server · Self-Hosted Infrastructure
Linux & Networking 2026 · Personal Project

Home Server: Self-Hosted Linux NAS & Game Server

  • Converted a Dell OptiPlex into a self-hosted Linux NAS that replaces Google Drive for personal file storage.
  • Configured network shares and hosts dedicated multiplayer Minecraft and Palworld game servers.
LinuxNetworkingNAS File StorageServer Administration

Interactive Engineering Lab

Test My Models Live in Your Browser

Switch tabs below to run interactive versions of my Final Year Project, NLP model, 3D PWA engine, and LL(1) compiler.

Random Forest + TreeSHAP · Pure NumPy

Hourly Ridership & Additive Shapley Attribution

1,248 pax/hr
Base E[f(X)]: 880 pax · Test MAPE: 4.1%

Scenario & Weather Inputs

Departure Hour (85% RF importance)17:00
Day & Calendar Regime
Temp31°C
Rain2 mm

Exact TreeSHAP Contributions (φ₀ + Σφᵢ = f(x))

Trained on 2.2M+ hourly trip records across 21 districts joined with DOSM demographics & Open-Meteo weather. Verified against brute-force Shapley enumeration.

Contrastive PyTorch LaBSE · 11,000 Pantun Corpus

Malay Pantun Pembayang–Maksud Coherence Scorer

0.91 Coherence
Held-out AUC: 0.92 (vs 0.52 LLM Judge)

Sample or Edit Pantun Couplets

Pembayang (Lines 1–2)
Maksud (Lines 3–4)

Model & Prosody Breakdown

Custom WebGL 3D Engine · 2-Bone IK & Thermal Shaders

PulseLift 360° Anatomical Mannequin & Muscle Glow

Pectoralis Major & Anterior Delts
Real-Time WebGL GLSL · 0 External 3D Libraries

Select Exercise Pose (2-Bone IK)

Orbit 360° Camera (or drag 3D model)Auto-Rotate
▸ Barbell Bench Press · Primary: Pectoralis Major, Triceps Brachii, Anterior Deltoids
Drag on the 3D athlete to orbit, scroll to zoom, or hover any muscle to spotlight it.
Extended G17 Grammar · 10 Production Rules

LL(1) Latin & Arabic-Script Arithmetic Parser

ACCEPTED
Zero backtracking · Disjoint Selection Sets

Token Stream Input

Expression (+ - * / or و ط ض ق غ and ب)

Step-by-Step Derivation Trace

Track Record

Work Experience & Education

Prior 6-month industry internship in software development & IT support alongside Computer Science training at UiTM.

Work Experience

Eden Hafiz Group PLT — IT Intern

Kuantan, Pahang · Computer and IT equipment sales and repair
Sep 2024 – Feb 2025
  • Co-developed EdenHR, a web-based HR management system (PHP, CodeIgniter, Bootstrap, MySQL) covering employee records, attendance, leave, payroll, and company notices.
  • Produced full system design documentation (Context Diagram, DFD, ERD, relational schema) and wrote and executed test cases across 9 system modules.
  • Diagnosed and repaired printers, desktops, and laptops; formatted machines and installed software for customers across 3 branches.
  • Created promotional posters and videos using Photoshop, Premiere Pro, Canva, and CapCut; supported Unifi promotion events and in-store laptop sales.
Degree

Bachelor of Computer Science (Hons.)

Universiti Teknologi MARA (UiTM), Kampus Kuala Terengganu
Mar 2025 – Expected Jun 2027
  • CGPA: 3.04 (Latest Semester GPA: 3.19)
  • Top Coursework Grades: Enterprise Programming (A+), Special Topics in Computer Science / XAI (A), Software Engineering (A-), Project Formulation (A-), Technology Entrepreneurship (A-), Artificial Intelligence (B+).
Diploma

Diploma in Computer Science

Universiti Teknologi MARA (UiTM), Kampus Raub
Oct 2022 – Feb 2025
  • CGPA: 3.25
  • Dean's List Award, Semester 1 (GPA: 3.52)
  • MUET Band 4.0 (CEFR B2 Competent User, 2024)
Certifications & Co-Curricular

Verified Technical Certificates & 80+ University Programmes

  • Certification Course: Web-Based System Development (Level 2 – Intermediate), FSKM, UiTM (Jul 2026)
  • Certification Course: Web-Based System Development (Level 1 – Beginner), FSKM, UiTM (Jun 2026)
  • Active participant in 80+ university programmes & workshops (2025–2026), including AI Unlocked: Exploring the Future of AI (UiTM Library, Oct 2026), Smart System Engineering with IoT: Concept to Implementation (FSKM, Jun 2026), Elevate & Connect: Resume & LinkedIn Workshop (Jun 2026), Webinar Session with International Industry Expert (FSKM, May 2026), The Campus AI Roadshow: Elevate Your Learning Journey with NotebookLM (Awantec & Google Cloud, Apr 2026), and Scopus AI Literature Search (Apr 2026).
For Hiring Managers & HR (CST688)

Seeking a 14-week internship, 15 March – 18 June 2027.

Available for Software, Data, or AI Intern roles in the Klang Valley: Petaling Jaya, Shah Alam, or anywhere reachable by LRT / MRT. All official UiTM placement documents, resumes, and industrial training objectives are ready for immediate download below.

Candidate
Muhammad Aiman bin Jamaluddin
Programme
Bachelor of Computer Science (Hons.) CS230, UiTM
Duration
15 March 2027 – 18 June 2027 (14 Weeks)
Target Roles
AI / Machine Learning, Data Science, or Full-Stack Software Intern
Locations
Klang Valley (Petaling Jaya / Shah Alam), LRT / MRT-accessible
Reference
Available on request

Get in Touch

Direct Contact & Official Links

Send a quick message below via WhatsApp or Email, or connect directly on LinkedIn and GitHub.