Jack Milton

About Me

I'm a Computer Science student specialising in Artificial Intelligence at the University of Suffolk. My academic journey is driven by a passion for understanding complex systems and developing innovative solutions through AI.

Beyond computer science, I have a deep fascination with physics and quantum mechanics, which informs my interdisciplinary approach to research and problem-solving.

Currently, I'm collaborating on research projects that bridge theoretical computer science with practical applications in various industries.

Education

BSc Computer Science, University of Suffolk

Research

AI & Bioinformatics

Interest

Data Science & Machine Learning

Research Work

mRNA Grammar

Research Collaborator with University of Suffolk & MultiplAI

Ongoing research project focusing on designing a machine learning pipeline for mRNA analysis. Collaborating with Dr. Kakia Chatsiou and MultiplAI to develop computational approaches for understanding mRNA structures.

Clustering DNA Sequencing Data

Dissertation Research

Developing a machine learning pipeline for Glioma Analysis using DNA sequencing data. This ongoing research forms the basis of my dissertation project, exploring unsupervised learning methods for medical data analysis.

Brain Tumour MRI Classification

Transfer Learning with ResNet-18

Technical analysis of medical diagnosis capabilities using deep learning. Investigated the application of transfer learning with ResNet-18 architecture for accurate classification of brain tumours from MRI scans.

Unsupervised Methods to Cluster NASA Meteorite Data

Machine Learning Research

Implemented and evaluated various clustering algorithms to analyse NASA's meteorite dataset, identifying patterns and relationships within extraterrestrial material samples.

Predicting Withdrawal Based on Student VLE Engagement

Educational Data Mining

Analysis of the Open University Learning Analytics Dataset to predict student withdrawal patterns based on virtual learning environment engagement metrics.

Artificial Intelligence In Face Identification

Review Paper

Comprehensive review of current artificial intelligence approaches to facial recognition and identification, exploring methodologies, ethical considerations, and future directions in the field.

Professional Experience

BT

Technical Intern

Internship Experience

Gained hands-on experience in telecommunications technology, network architecture, and data management. Worked alongside industry professionals to understand enterprise-level IT infrastructure and operations.

Sizewell C

Brand Ambassador

Industry Experience

Served as a brand ambassador for Sizewell C, promoting awareness and understanding of the nuclear industry through the application of physics principles. Engaged with diverse audiences to enhance knowledge about nuclear energy.

Projects

Open University Learning Analytics

Predictive modelling of student withdrawal based on virtual learning environment engagement metrics.

Machine Learning Education Data Analysis

View on GitHub

Brain Tumour MRI Classification

Deep learning approach using transfer learning with ResNet-18 for medical image classification.

Deep Learning Medical Imaging Transfer Learning

View on GitHub

NASA Meteorite Clustering

Unsupervised machine learning methods to analyze and cluster NASA meteorite data.

Clustering Unsupervised Learning Data Science

View on GitHub

mRNA Grammar Research

Collaborative research developing machine learning pipeline for mRNA structure analysis.

Computational Biology Machine Learning Research Project

View on GitHub

Life Offline

When I'm not coding or researching, I enjoy exploring the world beyond screens and algorithms. Here's a glimpse into my life away from the digital realm.