MEng Computer Science at UCL
About Me
Syed Ali Abbas
MEng Computer Science at UCL
Computer Science | AI Systems | Robotics | Applied ML
I am a Computer Science MEng student at University College London with a First Class average and a strong focus on AI systems engineering, applied machine learning, and robotics. I build end-to-end, production-ready platforms that combine rigorous engineering, modern AI techniques, and thoughtful user experience from Retrieval-Augmented Generation systems to global EdTech platforms.
2023-2024
Featured Projects
Flagship projects spanning AI systems, robotics, and full-stack development.
Sapiens Nova Academy
End-to-end EdTech platform with AI-powered learning assistant
Sapiens Nova Academy is a global education and innovation platform designed to prepare students for careers in technology and entrepreneurship. Built with Next.js, TypeScript, Tailwind CSS, featuring a Retrieval-Augmented Generation (RAG) assistant powered by LangChain, integrated Stripe payment processing, and PostgreSQL database with pgvector for semantic search. The platform supports multi-programme education delivery, secure enrollment management, and real-time payment tracking.
Systems Engineering Intern at HP
Production RAG pipeline for intelligent document processing
Designed and implemented a Retrieval-Augmented Generation pipeline for enterprise document understanding at Hewlett-Packard. Built with Python, LangChain, Llama models, and Hugging Face embeddings. The system features document ingestion, intelligent chunking, semantic retrieval, and response generation workflows. Containerized using Docker for reproducibility and deployment, with comprehensive evaluation strategies to assess model accuracy and grounding.
Real Estate Platform — Other Dev
High-performance property showcase platform with lead generation
Developed a production-ready real estate platform designed to showcase premium properties and drive client engagement. Built with Astro, React, TypeScript, and Tailwind CSS, achieving sub-2-second load times through efficient rendering strategies and careful asset management. Implemented dynamic property filtering, GSAP-based animations, and intuitive navigation flows tailored to real estate browsing behaviour. Integrated lead-generation workflows to convert user interest into actionable business enquiries, balancing technical performance with user experience and real business requirements.
ML Computer Vision Systems
CNN-based image processing and neural texture synthesis
Implemented advanced machine learning systems for visual computing, including CNN-based image denoising using PyTorch, neural texture synthesis using Gram matrices, and object detection and segmentation pipelines. Applied advanced image processing techniques in MATLAB and PyTorch, combining theoretical understanding of convolutional architectures with practical implementation for real-world visual tasks.
Get In Touch
Let's Build Something Impactful
I'm actively seeking internship opportunities, industrial placements, and research collaborations in AI systems, applied machine learning, and robotics. Drop me a message and let's discuss how we can work together.