Senior Uber Executive Joins Zesty.ai as Technical Advisor in Artificial Intelligence

Zesty.ai, a leading Artificial Intelligence risk analytics platform for Property and Casualty insurance, announced the appointment of Mike Tamir, Ph.D. as a Technical Advisor in Artificial Intelligence and Machine Learning.  Zesty.ai leverages the latest advancements in computer vision and deep learning on billions of data points on residential and commercial properties and their inhabitants to better assess the risk of catastrophic events, such as hurricanes, wildfires and floods and non-catastrophic events at the individual property level.

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Ranked as the number one influencer for Machine Learning and AI by Onalytica, Mike Tamir currently serves as Head of Data Science at Uber Advanced Technologies Group, the ride sharing company’s autonomous vehicle division.  Mike is also a Data Science professor at the University of California, Berkeley and a former lecturer at Columbia University.  He has led and advised several Data Science teams at large multinational organizations and Silicon Valley startups, including InterTrust, a joint venture between Sony and Phillips, Udacity, Takt and Galvanize.  Mike holds a Ph.D. from the University of Pittsburgh where he focused on Modeling Applications in General Relativity and Quantum Statistical Mechanics.

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“At zesty.ai we are on a mission to accelerate the digital transformation of the trillion-dollar property insurance industry,” said Attila Toth, Founder & CEO of Zesty.ai.  “Mike has a proven track record of successfully applying AI to transform large industries, such as, transportation, retail and financial services.  We are fortunate to work with Mike and bring his experience to our insurance partners!”

“I’m honored to join zesty.ai,” stated Mike Tamir. “We are at a unique point in time when the combination of advances in machine learning, cloud computing and ubiquitous access to data allows insurance companies to tailor their service offering to an individual customer while more accurately assessing risk.”

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