Hi! My name is Emma and I'm a third year geography student at Trinity College Dublin.
I've been involved in activism for about 5 years now and I'm extremely passionate about education and climate change. My research project will analyse how my university engages with class and socioeconomic status, focusing in particular on progression from post-primary school to higher education.
Hello! I'm Crystal, a current third year medical student from Trinity College Dublin, and originally from Yangon, Myanmar. I think physicians are in a unique position where they are entrusted by patients, understand firsthand the shortcomings in patient care, and possess the biomedical knowledge and skills needed to drive meaningful change, placing them at the forefront of cutting-edge research that can directly benefit patient care. I would love to be a physician-scientist one day who can bridge scientific discovery with clinical practice.
My research explores the effects of smoking on innate immunity and Chronic Obstructive Pulmonary Disease (COPD). I am fortunate to be part of a great research lab that allows me to explore my own ideas, design my own experiments, and, most importantly, keep moving forward when things do not go as planned!
I also love cooking and baking -- I am always thinking of what I should have for my next meal!
Hi everyone! My name is Anna and I'm part of the 2026 Laidlaw Scholars cohort at Trinity College Dublin, where I study Mathematics with a minor in Statistics.
For my research project, I'll be exploring a question that is becoming more important as AI develops: who is better at predicting the future, humans or algorithms? I'll be comparing forecasts from machine learning models with those from prediction markets, where collective human judgement is turned into live probabilities. After the 2024 US elections, prediction markets rapidly gained attention for correctly predicting the outcome before many traditional forecasts. At the same time, AI is making data-driven forecasting more powerful than ever. Through quantitative analysis, I'm curious to see whether the best predictions come from human insight, algorithmic pattern recognition, or perhaps a combination of both.
More broadly, I am interested in using mathematics to better understand and solve real-world problems like this one. I'm especially drawn to the way it combines logic with creativity, allowing us to approach challenges from different angles and develop efficient and innovative solutions.
Feel free to reach out if you want to discuss research or simply chat!