The Gillmore Workshop Series: AI, Data, and Innovation in Finance
The Gillmore Workshop Series is an off-curriculum initiative designed to enrich the learning experience of postgraduate students. Delivered by the research assistants and research fellows of the Gillmore Centre for Financial Technology, the series provides a platform for early-career researchers to share their expertise and emerging research methods. Through these hands-on workshops, participants gain exposure to new technologies, data-driven approaches, and practical applications across various areas, including artificial intelligence, blockchain, data analytics, and digital innovation. The aim is to foster the technical skills and creative thinking essential for the future of finance and technology.
Term 1
Fridays 14.00 - 15.00
Gillmore Lab
Week 6 (14 November)
Tracking Innovation Trends with Patent Embedding Analysis
Amir Hosseini
This workshop introduces students to patent embedding analysis as a tool for tracking and interpreting innovation trends. Using Sentence-BERT to vectorise patent abstracts, PCA to uncover domains of technological change, and centroid shifts to capture emerging trajectories, participants learn how to quantify innovation dynamics over time. Finally, through retrieval-augmented generation (RAG), students connect abstract trend vectors to concrete technologies, producing interpretable reports on emerging innovation hotspots.
Week 7 (21 November)
Virtual Reality Programming
Afaf Mohamed
The Programming VR workshop introduces students to the principles and practices of developing immersive virtual reality applications. Drawing on my ongoing project, Evolution of Digital Payment, where I created a VR demo, the session will demonstrate how interactive environments can be designed and programmed. Students will gain hands-on experience in setting up a VR workspace, understanding the basic building blocks of VR development, and experimenting with simple interactive features using industry tools. Examples from research and practice will illustrate how VR can be applied in areas such as education, simulation, and digital innovation. By the end of the workshop, participants will have an overview of the VR development process and the confidence to begin creating their own immersive applications.
Week 8 (28 November)
Textual Analysis
Ivy Luo
Large volumes of unstructured text, such as news articles, social media interactions, and business reports, contain valuable signals for understanding complex social systems. This workshop introduces students to methods for extracting actionable insight from text using natural language processing and machine learning tools. We will draw on examples from various research projects, such as extracting signals from news articles for prediction tasks, sentiment analysis of corporate reports, and modelling emotion dynamics in online discussions, to demonstrate how to extract reliable insights from text. Students will gain an overview of techniques such as text pre-processing, embeddings, and sentiment analysis from text, and will see how these approaches can be applied in research and practice.
Week 10 (12 December)
Financial applications of alternative data and open-source intelligence (OSINT)
Louis Navaro-Jones
Open-source intelligence (OSINT) and alternative data are increasingly used in finance to gain informational advantages beyond traditional market data. Sources such as news articles, social media, Google Trends, satellite imagery, web traffic, and even blockchain on-chain data can be collected, processed, and transformed into actionable signals for investment, risk management, and market monitoring. This approach combines data engineering (collecting, processing, combining, and analysing data), natural language processing, geospatial analysis, and anomaly detection to extract hidden insights, but also requires careful handling of biases, noise, and legal considerations.