Research & Insights
Technical essays, reading notes, and field observations on AI, quantitative finance, neuroscience, market behavior, and emerging deep-tech ideas.
From Notebooks to Applied AI Workflows
Applied AI requires more than model selection. It depends on problem framing, data quality, evaluation design, workflow integration, and clear technical documentation.
Quantitative Finance, Risk, and Market Systems
Quantitative finance increasingly sits at the intersection of risk modeling, market simulation, data engineering, and AI-assisted decision systems.
Reading Club Notes: "Attention Is All You Need" — Revisited
Seven years after the original transformer paper reshaped the field, we revisit its core ideas through the lens of what came next — from GPT to multimodal architectures. Notes from our May 2026 reading club session.
From Monte Carlo to Neural Networks: Modern Risk Modeling
Traditional Monte Carlo methods remain powerful, but neural network approaches to risk modeling are gaining ground — especially for high-dimensional portfolios and real-time applications. A comparative analysis of classical and modern approaches.
Quantum Computing for Finance: Separating Hype from Reality
Quantum computing promises to revolutionize financial modeling, but where do we actually stand? We survey the current landscape of quantum algorithms for finance, assess near-term feasibility, and identify the most promising use cases.
Neuroscience, Decision-Making, and Financial Markets
Notes on how cognitive science, decision-making, attention, uncertainty, and behavioral dynamics can help us think about markets and financial behavior.