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Hi There 👋

I'm a MSc in Artificial Intelligence student at the University of Malta

Recently I submitted and graduated with my thesis titled 'Mobile Gait Analysis', also winning Best ICT Project for Social Impact alongside a runners-up spot at Tech.mt's Best ICT Academic Project. Just a small outline, the thesis aims to classify regular and irregular 'gait cycles' using a smart-phone or smart-device. The thesis is now published by the International Journal of Semantic Computing following a presentation at the IEEE BigMM Conference.

Currently I am employed at iGolf.One as an AI Specialist in which I mainly work with Python. But past employments made me proficient in languages such as Javascript (Node and React) and C++

Although my academic inspiration in the AI in Medicine/Health Care bubble, I have experience working with NLP, Computer Vision and Machine/Deep Learning applications. Moreover, more published work includes experience with Dynamic Difficulty within an AI in Education solution.

About Me

I'm a 21 year old student currently reading for my Masters in Artificial Intelligence at the University of Malta. But besides that, I'm an avid cyclist and footballer. I also really enjoy listening to music.

Python Python Python Python


Languages

Jupyter Python Java C++ ReactJS

Tools

VS Code Anaconda Azure

Owen Agius's Projects

avl-and-rb-trees icon avl-and-rb-trees

Comparing the amount of rotations, comparisons and height when implementing a Red Black Tree against an Adelson-Velsky Landis Tree

banking-system-in-java icon banking-system-in-java

A CLI Banking System with integrated Card and Account handling with Administrator operations regrading the different types of accounts and transactions

building-a-nlp-language-model icon building-a-nlp-language-model

The project generates a sentence given a pre-defined starting phrase from the user such as "Ilbierah kont" and the script attempts to build a sentence off of that phrase. Structurally, the generator works in an n-gram fashion but the main structures used to generate the sentences were the unigram, bigram and trigram. The perplexity for each n-gram model was also calculated

cpp-bitwise-operators-and-quadtrees icon cpp-bitwise-operators-and-quadtrees

This repository consists of 2 folders. The first folder consists of a quadtree implementation in Cpp with Boolean and 'Black and White' representation. The second folder consists of an implementation of the bitwise operators on a binary string stored as an object of a big integer.

eggshell-for-linux icon eggshell-for-linux

Written in C as a 'Mini Linux Bash script' which handles both internal and external commands and command redirection. Preset environmental variables with the help of the linenoise package help in the functions of command and error handling

experimenations-in-reinforcement-learning icon experimenations-in-reinforcement-learning

Experiment 1: Comparison of key bandit algorithms; Experiment 2: Comparison of Q and SARSA Learning on Taxiv3 environment' ; Experiment 3: Comparison of Q, SARSA and CEM Learning on LunarLanderv2 Environment

human-activity-recognition-from-smartphones icon human-activity-recognition-from-smartphones

Using Android Phone inertia sensors such as gyroscopes and accelerometers to determine and identify human activity. Classified using SVMs, KNN, Decision Trees and Logistic Regression for Supervised Learning

management-system-in-java icon management-system-in-java

An object oriented management system for airplane maintenance with serializable classes written in Java for Advanced Matriculation Certificate

path-planning-and-pid-control icon path-planning-and-pid-control

A Two Part Project where in the first part a robot is localized using a particle filter whereas in the second part the robot is run through a PID Controller, A* Path Finding Algorithm and a Line Smoothener

phoneme-analysis-and-classification icon phoneme-analysis-and-classification

Given a very large dataset of speech from the British Isles, all were manually inputted into the .csv file attached by generating an average value for each of the 3 formants present in the audio. The scope of the project was to be able to classify the phonemes from one another. Therefore, a KNN was built in order to do just that. Resulting in an average accuracy of 89%

speaker-classification-with-cnns icon speaker-classification-with-cnns

Given a .WAV file, this experiment extracts the melspectogram of the audio in order to classify the speaker within the sound. For classification, this experiment compares the performance of the ShallowNet and VGG16 frameworks

tealang-compiler icon tealang-compiler

A compiler consisting of lexical analysis, syntactic analysis, semantic analysis and interpreting alongside an XML generation for a 'mock' language called TeaLang written in C++14.

tsp-in-machine-learning icon tsp-in-machine-learning

Applying the Ant Colony Optimization (ACO) and Simulated Annealing (SA) algorithms to solve the Travelling Salesperson Problem

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