PhD student specializing in machine learning and mechanistic interpretability. Experienced in building end-to-end ML systems with deep learning architectures such as transformers and RNNs. Curious to understand how neural networks work on a fundamental level and passionate about developing more transparent and safe AI systems.
NSCAN is a novel deep learning model for predicting multiple stock returns simultaneously using financial news data and cross-attention mechanisms. Unlike traditional approaches that predict returns for individual stocks in isolation, our model captures cross-asset relationships and market interactions.
The rapid and accelerating progress of development in the field of artificial intelligence may profoundly reshape the global economy by both increasing productivity and automating away many jobs. This paper explores how households adjust their economic behavior today in anticipation of transformative AI (TAI). Building on previous research, I introduce a novel mechanism where the future reallocation of labor from humans to AI systems owned by wealthy households creates a zero-sum contest for control over AI resources, affecting current savings decisions and asset prices.
States match federal SBIR grants to incentivize local R&D, but do they work? Looking at Kentucky's aggressive state match program using synthetic control methods, I find mixed results, including a large yet statistically insignificant increase in private R&D, and a surprising negative effect on new business formation.
Previous research shows religious people are happier, but correlation isn't causation. Using novel econometric techniques and World Values Survey data, I show both believing in God and attending religious services actually make people happier across seven countries.
Cognitive biases fundamentally alter how negotiators behave in conflicts. Unlike standard bargaining theory which predicts costly conflicts should never occur, prospect theory shows that when parties have conflicting reference points, fighting can become unavoidable.