Gurjeet Singh is Ayasdi’s executive chairman and co-founder. He leads a technology movement that emphasizes the importance of extracting insight from data, not just storing and organizing it.
Singh developed key mathematical and machine-learning algorithms for Topological Data Analysis (TDA) and their applications during his tenure as a graduate student in Stanford’s mathematics department, where he was advised by Ayasdi co-founder Professor Gunnar Carlsson.
He is the author of numerous patents and has been published in a variety of top mathematics and computer-science journals. Before starting Ayasdi, he worked at Google and Texas Instruments. Singh was named by Silicon Valley Business Journal as one of their “40 Under 40” in 2015.
He holds a B.Tech. degree from Delhi University, and a Ph.D. in Computational Mathematics from Stanford University. He lives in Palo Alto with his wife and two children and develops multi-legged robots in his spare time.
Like Achilles or Sampson, the power and potential of AI has a weakness, a vulnerability. In the case of financial services that weakness is its opacity. In general, the better the machine learning system, the blacker the box - that is, the harder it is to decipher what is going on inside the model.
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A Much-Needed Intelligent Approach to Segmentation Anti-money laundering (AML) is a complex and persistent challenge for financial institutions. AI is transforming key elements of the AML workflow and delivering an order of magnitude in performance improvements in the process. Money laundering has become the leading source of compliance fines for North American and European institutions. In 2016 alone, regulators levied more than...
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