Ignacio Vigil Cardenal

Co‑designed a 4‑session academy on Machine Learning for Quantitative Investing, covering Python for data analysis, supervised learning (linear/logistic regression, regularisation), neural networks, natural language processing, time‑series models, and portfolio applications for the Warwick Business School Society. ​ Led live, hands‑on sessions in Python using NumPy, Pandas, Matplotlib,scikit‑learn and PyTorch, guiding students through building and evaluating return‑prediction and classification models on historical financial data. ​ Developed course materials, Jupyter notebooks, and a graded group project where participants designed their own ML‑driven trading signal or portfolio strategy. ​ Coordinated logistics, attendance, and a final event with certificates and project recognition, helping position the society as a serious platform for quantitative finance and machine learning education.

During the summer of 2025, I have conducted research on the effectiveness of various machine learning models for brain tumour diagnosis under the supervision of Linda Nichols and Rasseeda Virgo, both members of the research staff at Warwick. The models I applied to the dataset are: • Support Vector Machine (SVM) – a classical machine learning algorithm used as a baseline for comparison • Convolutional Neural Networks (CNNs) – deep learning models particularly effective in image-based medical diagnosis • Bayesian Convolutional Neural Networks (BCNNs) – probabilistic models that, unlike CNNs, also estimate uncertainty in their predictions, which is especially valuable in clinical settings This project aims to assess the accuracy, reliability, and uncertainty of each model when classifying MRI brain scan images. The research will contribute to the broader goal of improving early detection tools for brain tumours using AI. Link to article: https://urss.warwick.ac.uk/items/show/846

I have written an article on the use of Monte Carlo Methods for options trading. The article consists of showing the reader how to create code to develop stock price simulations and by doing so, calculate the price of options. Furthermore, we delved into the mathematics behind stock price simulations by using tools from stochastic calculus.

Tutored IB Mathematics individually since 2022. I have tutored 10 students in the past 3 years. Improved a marketing student’s grade by 60% in a calculus course. I have learned how to explain complex topics such as calculus, probability, algebra and geometry. Developed time management skills and enhanced my knowledge of Mathematics.

First Year Modules: Maths by Computer (Python), Programming for Scientists (Java), Probability, Statistical Laboratory (R), Calculus, Multivariable Calculus, Differential Equations, Abstract and Linear Algebra.

Attended an online course on artificial intelligence and machine learning offered by Lady Margaret Hall College at the University of Oxford, equivalent to 15 CATS. Developed practical skills in AI and Machine Learning, covering Python (NumPy, classes, objects), foundational algorithms (regression, neural networks with PyTorch, CNNs), and advanced NLP techniques (LSTMs, GRUs).

HL: - Mathematics AA 7 - Economics 7 - English B 6 SL: - Physics 7 - Geography 6 - Spanish Lang & Lit 6 - Tok B - Extended Essay A Overall: 42/45