Economics · AI / Data Science · Philosophy
I'm Isaac, an economics student by training interested deeply in causal inference, AI / machine learning, ethics and human cognition. I'm currently completing an MSc in Social Data Science at the University of Oxford and previously worked as a predoctoral research fellow at the Manos Institute for Cognitive Economics.
My path runs from philosophy and ethics through First Class Honours in economics to applied ML. I'm interested in high-impact careers that involve understanding, predicting, or shaping complex social phenomena.
Description is temporarily withheld while the thesis is marked as an anonymous submission — it will return here once examination is complete.
Why did American economic sentiment stay grim while the fundamentals recovered? I replicated the most prominent academic explanation using a conceptually identical procedure — and found that the headline result failed to replicate. I then developed a partisan-asymmetry explanation that accounted for a larger share of the sentiment–reality gap than any competing account in the literature at the time of writing. Supervised by Prof. Richard Holden (UNSW).
Along the way I built a novel Google Trends–based real-time sentiment index that mechanically rules out salient forms of partisan signalling, and built on this work as a research assistant at the University of New South Wales (UNSW).
An economic-history paper used HSV colour histograms from European oil paintings to build high-frequency historical indices of economic growth. I replicated its core methodology (including PCA-based feature extraction) from the written description alone, then extended it with features from a pre-trained neural network to test whether composition, texture, and style encode growth signal beyond colour.
Working on the mathematics of database theory — dependency theory, conjunctive queries, expressive power, finite model theory — and applying it to theoretical models of cognitive reasoning for a working paper. I lead weekly presentations on these topics to a team of economics professors and conduct literature reviews across the neuroeconomics literature.
Building a real-time, end-to-end Australian economic sentiment index from Google Trends data — scraping, cleaning, and time-series construction in R, Python, and Stata, including forking and modifying an open-source R package to adapt its sampling behaviour to the project's needs.
Private academic tutor for high-school students, managing my own client roster; and ward assistant on the casual roster at RPA Hospital, working across the COVID-19 clinic, emergency department, and ICU.
Applied statistics, machine learning, data science, research design.
PhD-level coursework in econometrics, causal inference, micro, macro, and health economics.
Econometrics and empirical methods alongside applied ethics, political economy, and international relations.
Award for Academic Excellence and Scholars Award; distinguished achiever.
Essays coming soon.