AI researcher, Software Developer and Master's Computer Science graduate, based in London 🚀 🧑💻
About Me
I'm a passionate and experienced Software Developer with 5+ years industry experience, a published researcher in Artificial Intelligence and Master's of Comp Sci graduate 🌱.
I specialise in helping organisations unlock the full potential of their data through cutting-edge, scalable and reliable end-to-end solutions. Streamlining operations, enhancing decision-making, & driving measurable client-centric business impact 🚀.
What I Do
AI & Bioinformatics Research
Developing machine learning models for protein analysis and biological data interpretation.
Full-Stack Development
Developing scalable web applications and APIs with modern frameworks and tools.
Data Engineering & Analytics
Creating big data platforms and real-time analytics solutions for stakeholders.
Enterprise Consulting
Leading digital transformations and system integrations for Fortune 500 companies.
Cloud & DevOps
Architecting scalable cloud infrastructure and automated deployment pipelines.
Open Source Development
Creating and maintaining open-source packages for the scientific computing community.
Featured Projects
Click for more info
pySAR
Python library for analysing Sequence Activity Relationships (SARs)/Sequence Function Relationships (SFRs) of protein sequences.
DCBLSTM_PSP
Secondary Protein Structure Prediction using deep convolutional long-short-term memory (LSTM) and other deep learning techniques.
iso3166-2
A lightweight Python package, and API, for accessing all of the world's most up-to-date and accurate ISO 3166-2 subdivision data, including: name, local/other name, parent code, type, latitude/longitude, flag and history.
iso3166-flags
Dataset of all ISO 3166-1 and ISO 3166-2 country and regional flags 🌎
protPy
Calculating a range of protein descriptors using their physicochemical, biological and structural properties. Built alongside and for use in pySAR research project.
aaindex
Python package for working with the verbose AAIndex database, providing easy access to amino acid indices and their biochemical, physicochemical and structural properties.
Professional Experience
Senior Analyst
Accenture
Jun 2022 – Present • London, UK
- ▸Designed and deployed scalable real-time big data applications and dashboards for a public healthcare client using the Palantir Foundry platform, enabling data-driven insights for 100+ stakeholders
- ▸Managed an Enterprise-grade SAP transformation for several multi-billion-dollar pharmaceutical clients, heading the tech & data team involving key processes such as AI strategy, data quality, cleansing, harmonisation, ETL and migration, achieving a ~20% improvement in operational efficiency and reduced time to market through strategic data implementations
- ▸Developed POCs and prototypes for clients, partnering with C-suite and senior stakeholder to translate business requirements into technical roadmaps, ensuring alignment between engineering solutions and enterprise objectives.
- ▸Drove the delivery of release schedules, release notes, documentation and CI/CD pipeline code deployments across multiple dev and test environments for a FinTech client via Azure DevOps
Software Analyst
Deloitte
Aug 2021 – May 2022 • Belfast, UK
- ▸Served as a front-end web developer in an engineering team of 4 people at a leading global law firm, contributing as a contractor to innovative legal tech solutions used by hundreds of internal stakeholders
- ▸Built, tested and redesigned user-centric front-end components and web tools in close collaboration with client stakeholders, ensuring alignment with functional and non-functional requirements
- ▸Achieved 25% reduction in stakeholder review time and 20% reduction in page load time through optimized solutions
- ▸Took ownership of feature development from concept to deployment, delivering maintainable front-end solutions that integrated with back-end APIs and databases
Machine Learning Research Intern
Manipal Institute of Technology
Jul 2020 – Oct 2020 • Manipal, India / Remote
- ▸Researched and developed an AI deep learning model to accurately predict the secondary structure of a protein from its initial primary sequence, using LSTM recurrent neural networks
- ▸Built a custom Python software package leveraging the TensorFlow/Keras framework for training and testing the model on real-world protein datasets
- ▸Awarded a grant of ~$900 from Google to use their platform for building, testing, tuning and deploying complex ML models
- ▸Co-authored a research paper published in a peer-reviewed bioinformatics journal, contributing to scientific understanding of protein folding through AI
Service Desk Engineer
Adobe
Sep 2018 – Sep 2019 • Dublin, Ireland
- ▸Provided enterprise-level technical support for Adobe Experience Cloud, working as part of a 50+ person global service desk across multiple time zones
- ▸Resolved high-severity incidents and complex service requests for Fortune 100 clients
- ▸Maintained high customer satisfaction scores while handling critical technical escalations
- ▸Collaborated with cross-functional teams to ensure rapid resolution of client issues
Education
Master's of Engineering in Computer Science
Queen's University of Belfast (QUB)
Belfast
2016 – 2021
Graduated with First Class Honours.
Master's thesis in Bioinformatics – building an ML framework and software package to encode protein sequences to identify a relationship between their sequence and their function, a process known as SAR (Sequence Activity Relationship), the software developed is called pySAR and was published in a scentific journal: View Publication.
Skills & Technologies
Programming Languages
8 skills
Frameworks & Libraries
15 skills
Tools & Technologies
16 skills
Specializations
16 skills
Published Works & Articles
Academic research publications and technical articles sharing insights on bioinformatics, machine learning, and software development.
📚 Academic Research Papers
Machine learning based predictive model for the analysis of sequence activity relationships using protein spectra and protein descriptors
Journal of Biomedical Informatics • 2022
A. McKenna, et al.
This research presents a comprehensive machine learning approach for analyzing sequence activity relationships (SARs) of protein sequences and their mutants using digital signal processing techniques and protein physiochemical descriptors.
DCBLSTM—Deep Convolutional Bidirectional Long Short-Term Memory neural network for Q8 secondary protein structure prediction
Computers in Biology and Medicine • 2021
A. McKenna, et al.
This research presents a deep learning model for Q8 protein secondary structure prediction using deep learning architecture via bidirectional convolutional and long-short term memory components to map local and long-distance dependancies, respectively.
✍️ Technical Articles on Medium
Get In Touch
Send me a message
Let's connect!
I'm always interested in discussing new opportunities, collaborating on research projects, or just having a chat about tech. Feel free to reach out!
London, UK
