AboutEpistamai is an applied research company focused on the intersection of causality and machine learning to solve some of the most difficult problems in AI.
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Why We ExistEpistamai was created to address significant gaps in the way that academia and industry have been approaching AI ethics today. As new technologies like generative AI amplify existing ethical problems around fairness, bias, and inequality, more powerful approaches are needed to build AI systems that society can trust.
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Our StoryOur research has its origins at the Federal Reserve, where our founder was a data scientist studying how algorithmic bias can affect credit decisions. He discovered a novel way of modeling a causal Bayesian network as an abstraction of any supervised learning model, providing a basis for understanding fairness and discrimination in machine learning.
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Our Founder
Chris Lam
CEO
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Chris is a Chinese American computer scientist and entrepreneur who is focused on leveraging causality to improve data science. He previously worked at the Federal Reserve Bank of Chicago, Hewlett Packard, and Consumer Reports. Chris earned a BSE in computer science from Penn, an MS in electrical engineering from Columbia, and an MBA from Northwestern (Kellogg).
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