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Keith Lee

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Keith Lee is Professor of AI and Finance at the Gordon School of Business, Swiss Institute of Artificial Intelligence (SIAI). His primary research lies in financial mathematics and AI-driven computational science, with a focus on quantitative modeling of complex economic and financial systems. His work integrates machine learning, stochastic modeling, and data-centric methods to study structural transformations in markets and institutions.

His recent work examines the broader socioeconomic consequences of artificial intelligence, including labor markets, public finance, demographic change, institutional adaptation, and the distributional effects of technological progress.

He holds a PhD in Mathematical Finance from Boston University, and previously earned an MSc in Finance and Economics from the London School of Economics. He completed his undergraduate studies in Economics at Seoul National University under the Korea Foundation for Advanced Studies scholarship program.


Keith Lee
SNS heavy users have lower income?

One-variable analysis can lead to big errors, so you must always understand complex relationships between various variables. Data science is a model research project that finds complex relationships between various variables. Obsessing with one variable is a past way of thinking, and you need to improve your way of thinking in line with the era of big data. When providing data science speeches, when employees come in with wrong conclusions, or when I give external lectures, the point I always emphasize is not to do 'one-variable regression.'

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Keith Lee
High accuracy with 'Yes/No' isn't always the best model

With high variance, 0/1 hardly yields a decent model, let alone with new set of dataWhat is known as 'interpretable' AI is no more than basic statistics

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