Exploring the intersection of artificial intelligence, quantum mechanics, and data science
I'm a Computer Science graduate with First Class Honours, specialising in Artificial Intelligence from the University of Suffolk. My academic journey was 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.
BSc Computer Science, University of Suffolk
AI & Bioinformatics
Data Science & Machine Learning
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.
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.
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.
Implemented and evaluated various clustering algorithms to analyse NASA's meteorite dataset, identifying patterns and relationships within extraterrestrial material samples.
Analysis of the Open University Learning Analytics Dataset to predict student withdrawal patterns based on virtual learning environment engagement metrics.
Comprehensive review of current artificial intelligence approaches to facial recognition and identification, exploring methodologies, ethical considerations, and future directions in the field.
Industry Experience
Currently in this role I am leveraging AI, LLMOps, and Python expertise to craft innovative solutions. My role involves advancing machine learning pipelines, aligning with the company's focus on data-driven problem-solving.
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.
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.
Predictive modelling of student withdrawal based on virtual learning environment engagement metrics.
Deep learning approach using transfer learning with ResNet-18 for medical image classification.
Unsupervised machine learning methods to analyze and cluster NASA meteorite data.
Collaborative research developing machine learning pipeline for mRNA structure analysis.
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.
Białka Tatrzańska, Poland
Peclet, Val Thorens
La Folie Douce, Val Thorens
Eze, France
Nice, France
Antibes, France
Monte Carlo, Monaco
Brugges, Belgium
Brussels, Belgium
Step into the quantum world where physics meets visualization. Explore interactive 3D representations of quantum mechanics principles and dive deep into the mathematical beauty of the universe.
Interactive 3D visualization of qubit states in quantum mechanics. Manipulate quantum states and apply quantum gates in real-time.
Coming soon: Explore quantum wave functions and probability distributions in various potential wells.
Coming soon: Visualize particles tunneling through energy barriers in 3D space.
work@jackmilton.net
Norfolk, United Kingdom