As a researcher and creator, I work at the intersection of analysis, writing, and digital tools to explore ideas with clarity and depth.
Bridging bioscience and artificial intelligence to shape the future of healthcare and drug discovery.
I am an MSc student in Drug Discovery with Artificial Intelligence at the University of Liverpool, building on an academic foundation in Bioscience and Biotechnology and developing a growing focus on the application of AI in healthcare. My work is driven by an interest in how computational and data‑driven approaches can support drug discovery, clinical research, and broader healthcare innovation.
I am currently strengthening my practical skills in deep learning through hands‑on projects, including work with Variational Autoencoders (VAEs) and AI agents. Alongside technical development, I am committed to understanding how AI can be applied responsibly, safely, and effectively within scientific and clinical environments.
In addition to my academic work, I serve as a Tutor at OE Tuition Liverpool, supporting students with diverse learning needs. This role has helped me develop strong communication, empathy, adaptability, and problem‑solving skills, and has reinforced my commitment to accessibility and inclusion in education.
I am actively seeking opportunities in the UK where I can contribute to AI‑driven healthcare and drug discovery. I am particularly interested in roles involving computational drug discovery, clinical research, CRO operations, and medical writing, where I can apply my interdisciplinary background and continue developing as both a researcher and practitioner
A combination of scientific knowledge, technical learning, and communication skills that support my journey into AI-driven healthcare and drug discovery.
My approach is driven by precision, efficiency, and a commitment to delivering high-quality outcomes that align with client objectives and professional standards.
I am proficient in Python, Java and C++ applying these languages to develop computational solutions for biological research. My expertise includes bioinformatics and computational approaches to drug discovery, enabling me to bridge biology with modern computing technologies
Experienced STEM tutor specialising in A Levels, GCSE (Years 9–11), SATs, and 11+ Grammar School entrance examination preparation within the British education system. Skilled in delivering personalised, results-driven lessons tailored to individual learning needs, including providing SEN support for students with autism and Tourette syndrome.
Specialist in Harvard, Vancouver, RSC, and APA referencing styles, with extensive experience in accurately formatting, reviewing, and editing academic and technical documents to ensure compliance with institutional and publication standards
A collection of projects demonstrating expertise in software development, AI, data science, and technical documentation. Explore my GitHub repository to view the complete projects. Here are my projects list below:
Phenotypic Virtual Screening — Built a data‑driven workflow using machine learning and Jupyter notebooks to analyze phenotypic datasets and identify patterns relevant to early‑stage drug discovery.
Ortholog Discovery & Phylogenetic Analysis of PMP34 — Conducted comparative genomics and phylogenetic analysis to identify PMP34 orthologs across species, using sequence alignment, evolutionary tree construction, and bioinformatic workflows to study functional conservation
RAG Clinical Agent — Developed an AI‑assisted clinical information retrieval system using Retrieval‑Augmented Generation (RAG) to extract, organize, and summarize medical knowledge from structured and unstructured sources, improving clarity and decision‑support for healthcare workflows
Bluecoat PWA — Built a Progressive Web App (PWA) with offline support, responsive UI, and installable app features to deliver a fast, mobile‑friendly user experience using modern web technologies.
Static Website — Designed and deployed a clean, responsive static website using modern HTML/CSS practices, focusing on lightweight performance, structured layout, and accessible front‑end design
Clinical AI Agent — Built an AI‑powered clinical assistant using Retrieval‑Augmented Generation (RAG) to process medical text, retrieve relevant information, and generate clear, structured summaries that support clinical decision‑making and workflow efficiency
Docking and Molecular Simulations — Targeting smoothened homology precursor protein in sonic hedgehog pathway with selected phytochemicals [daidzein, curcumin and pinosylvin]: an in-silico screening and identification of novel drug candidate/s against medulloblastoma disease
I’m always open to connecting about tech, AI, bioinformatics, or collaborative projects. Feel free to reach out if you’d like to discuss ideas or work together