Computer Science Masters student focused on applied NLP, machine learning, and game development. Experienced in building local-first ML pipelines, and implementing gameplay and networked systems in production game engines. Currently seeking opportunities in game development, software engineering, ML engineering, or applied NLP.

Currently building:

• LLM applications
• AI-powered search
• NLP tools
• Open source projects
• Unity projects
• UE5 projects

Bachelor of Computer Science — Mobile and Game Development University of Wollongong in Dubai (UOWD)

Master's in Digital Transformation — in progress University of Wollongong in Dubai (UOWD)

Machine Learning & NLP

• Building retrieval-augmented generation (RAG) pipelines, including HyDE retrieval and DSPy-based question answering
• Named entity recognition and knowledge graph construction (GLiNER, REBEL, spaCy), including RDF graph construction and SPARQL querying
• Training and evaluating models from scratch (PyTorch CNNs, NLTK-based text classification)
• Running and serving local LLMs (Ollama) on GPU hardware for offline inference
• Comparative pipeline evaluation and error analysis (e.g., divergence in passive voice, coreference, and combinatorial over-generation)

Software Development

• Full-stack pipeline development in Python, including data processing, dashboarding (Streamlit), and modular codebase refactoring
• Version control and collaborative development workflows (Git/GitHub)
• Jupyter-based experimentation and reproducible analysis

Game Development

• Gameplay systems and networked multiplayer implementation in Unreal Engine
• Engine scripting and systems design in Unity
• C++ and C# for engine-level and gameplay programming

Engineering Practices

• Iterative debugging and root-cause diagnosis of complex system issues
• Technical documentation and report writing
• Working effectively in small collaborative teams on multi-person projects

Programming Languages

AI & Machine Learning

Data Science

Backend Development

Databases

Game Development

Computer Science Foundations

Tools & Platforms

Local NLP/RAG pipeline analyzing YouTube comment sentiment and entities using Ollama, HyDE retrieval, GLiNER NER, and DSPy-based QA, with a Streamlit dashboard. Runs fully offline on local GPU hardware.

Automated cryptocurrency arbitrage monitoring platform. Video Demo

Comparative NLP project evaluating REBEL vs. GLiNER+spaCy pipelines for relation extraction, including RDF graph construction and SPARQL querying.

Image classification model built in PyTorch, trained and evaluated from scratch.

Virtual reality MRI training application built in Unity for Meta Quest. Features an AI-powered virtual instructor using Convai, immersive interaction mechanics with XR Interaction Toolkit, guided MRI procedures, and realistic medical workflow simulation.

VR cooking simulation built in Unity for Meta Quest featuring physically-based food preparation and real-time thermal cooking simulation. Food is cooked dynamically based on localized heat exposure, allowing individual surfaces and regions to brown independently rather than using a simple progress bar. Includes realistic object interactions, physics, and interactive kitchen gameplay.

• Email: izt1607@gmail.com
• LinkedIn: TBA
• Discord: humuhumunukunukuapua