Kevin Xu

Head Of Machine Learning at Quora

Kevin Xu has a diverse work experience in the field of machine learning and quantitative research. Kevin started their career as a Research Assistant at the University of Chicago, where they worked on various machine learning algorithms and theories. Kevin'sresearch results were published at a top machine learning conference and received significant recognition.

After their stint at the University of Chicago, Kevin joined NEC Laboratories America as a Research Intern. Here, they gained hands-on experience in the research and development of cutting-edge technologies.

Kevin then moved on to work as a Quantitative Researcher at a private fund. In this role, they leveraged their expertise in machine learning, data mining, and technical analysis to analyze market data and develop trading models.

Following their time at the private fund, Kevin joined TradeLink as a Quantitative Developer. Here, they focused on developing quantitative strategies for trading, utilizing their strong mathematical and programming skills.

Most recently, they have been working at Quora, initially as a Staff Software Engineer and then as a Senior Engineering Manager. Currently, they hold the position of Head of Machine Learning. In this role, Kevin leads a talented team of engineers in tackling complex problems in natural language processing, recommendation systems, and ads CTR prediction.

Overall, Kevin Xu's work experience showcases their proficiency in machine learning, quantitative research, and team management, making him a valuable asset in the field.

Kevin Xu attended Tsinghua University from 2006 to 2010, where they earned a B.S. degree in Computer Software. In 2008, they briefly studied as a visiting student at Kyung Hee University, focusing on Information Technology. From 2010 to 2012, they pursued a Master of Science (M.S.) degree in Computer Science at the University of Chicago.

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Sunnyvale, United States

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Quora

28 followers

Quora’s mission is to share and grow the world’s knowledge. A vast amount of the knowledge that would be valuable to many people is currently only available to a few — either locked in people’s heads, or only accessible to select groups. We want to connect the people who have knowledge to the people who need it, to bring together people with different perspectives so they can understand each other better, and to empower everyone to share their knowledge for the benefit of the rest of the world.


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501-1,000

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