Graduate Teaching Assistant (KCL) — 5CCS2PEP
Supported labs and tutorials for 200+ students in Practical Experiences of Programming. Guided work in C++, Scala, and software engineering to strengthen coding proficiency and problem-solving.
Computer Science student at King's College London, pursuing an MSci degree with First-class Honours. With a strong academic foundation in Artificial Intelligence, Full-stack Web Development, Software Engineering, Data Structures and Algorithms, paired with a passion for innovation, the focus is on building impactful and efficient technological solutions of real-world problems.
Proficient in multiple programming languages such as Python, Java, C++, Scala, JavaScript, as well as frameworks like Vue.js, Node.js, and Django. This expertise is underpinned by hands-on work experience in Grupo Newport and several projects. Recognized for a unique ability to merge technical knowledge with creativity, consistently delivering innovative solutions. Dedicated to leveraging advanced technologies to create transformative tools that optimize performance and enhance user experiences.
Supported labs and tutorials for 200+ students in Practical Experiences of Programming. Guided work in C++, Scala, and software engineering to strengthen coding proficiency and problem-solving.
Fine-tuned LLMs on 500k+ documents (+35% relevance). Built a RAG chatbot (90%+ query accuracy, 60% faster support). Trained DL models on 50k+ images (92% accuracy, 70% less labeling). Ran EDA on 1M+ rows (40% faster reporting). Delivered a churn model (+25% forecast accuracy). Automated Python/SQL pipelines (hours → minutes). Improved generative outputs using BLEU/ROUGE/perplexity (+25% coherence).
Led 6 engineers to ship the company’s first website ahead of schedule on AWS. Built 80%+ of the front end (Vue.js + React Native). Achieved 100% responsive design, 35% faster page loads, +40% client inquiries, and +25% average session duration.
Computer-vision pipeline captures Chess.com boards; CNN detects pieces and reconstructs the position. Stockfish suggests best moves (+20% vs baseline). Deployed on AWS EC2 & S3 for scalable inference.
Google-Maps-style app using MapLibre and a Fastify + TypeScript backend. Smooth zoom/pan/search with optimized tile loading (~30% faster). Modern UI with React and Tailwind animations.
Multi-threaded Java (Maven) exchange with real-time order books and matching. Simulated 1000+ concurrent trades with synchronization, PnL tracking, and market/limit orders for realistic dynamics.
Full-stack platform where employers post roles and applicants apply. Matchmaking algorithm improved job–candidate fit by 30%. CV parser (Python + spaCy) auto-extracts structured resume data.
Python + ROS state machine for autonomous navigation across rooms. YOLOv5 integration achieved 95%+ real-time object recognition in dynamic environments.
Java/JavaFX frontend with a Python analytics backend. Processed 60k+ records using NumPy, Pandas, and Matplotlib. Built an ETL pipeline on the Ignitus LMS database, improving reporting efficiency by 40%.
Trained an animal recognition model on the iNaturalist 2017 dataset with Pandas and TensorFlow. Applied overfitting-reduction techniques (27% performance gain). Achieved 99% accuracy on the latest model.
Performed penetration testing on two websites, identifying 17 critical issues aligned with OWASP Top 10. Authored a 20-page report and a long-term roadmap targeting a 50% reduction in exploitable vulnerabilities.
Full-stack app for membership management and class scheduling, increasing sales and enrollments by 40%. Built with C# and Swift (iOS), backed by MySQL.
Completed projects in search, machine learning, neural networks, and NLP; applied core AI techniques to practical problems.
King's College London, UK | September 2023 - June 2026
Arenas Atlantic, Spain | September 2021 - July 2023
Diploma Programme | September 2022 - July 2023