ALGOLABS - Key Persons

David Lindsay holds an undergraduate degree in Mathematics and Computer Science. He completed his PhD at Royal Holloway University of London, focusing on effective probability forecasting using Machine Learning algorithms. During his doctoral studies, he developed a passion for teaching, earned a college certificate in Teaching, and became an Associate Fellow of the Higher Education Academy (HEA). He was also recognized with an award for his teaching materials in the third-year Machine Learning course module in Computer Science. David has held various front-office quantitative roles, working with investment banks, hedge funds, and retail brokerages to develop fully automated trading models and analytics across diverse asset classes. Throughout his career, he has mentored and trained over 30 students in quantitative finance and data science through various internship programs. Additionally, he has served as an industry supervisor for three PhD students, two of whom have recently passed their viva. David has also co-authored research on the application of machine learning to quantitative financial datasets. Currently David is working with the University of Reading and Quantum-h on a short term research project to investigate the use of Large Language Models in Research and Development.

Si n Lindsay holds an undergraduate degree in Molecular Biology and Genetics and a PhD from Royal Holloway, University of London, where she researched potential drug targets for parasitic diseases. She is a Fellow of Advance HE and has earned a Master's in Academic Practice from City, University of London. Si n has held numerous strategic roles within Higher Education, focusing on the development of teaching, learning, and assessment practices. She currently works at the University of Reading as an Academic Developer where she is co-chair for the University's Generative AI working group. As cofounder of AlgoLabs with David, she has been instrumental in establishing partnerships with academia, mentoring and supervising students, and co-authoring numerous research papers on machine learning.