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Daily Mirror
Daily Mirror
National
Amber O'Connor

Oxford graduate slams critics who question her success because of her beauty

An Oxford University graduate has slammed cruel trolls who accused of her faking her academic success because they did not believe she could be beautiful and clever.

Kate Wenqi Zhu, 28, graduated from her second master's degree at the prestigious university earlier this year. Unfortunately, though, not everyone celebrated her success.

The scholar received a torrent of online abuse after a video from her graduation in March went viral on Chinese social media.

Thankfully, she was not deterred by bullies who said she did not fit their incorrect stereotype of what a mathematician should look like, and she is continuing her passion by studying DPhil in Mathematics at Oxford.

The graduate has a very impressive CV (Weibo)

When she's not studying, Kate can be found enjoying a number of outdoor activities, including rock climbing, rowing and golf, and she enjoys sharing updates from her travels with her followers online.

Last week, she also defended herself in a video shared on Weibo addressing the attacks against her character. Her post revealed she has "experienced many emotions over the past half a year and had received plenty of encouragement and sincerity."

"Does releasing one's selfies mean the person is poor at studying? It's time to break this stereotype," she said. "I just want to say that as long as the stereotype exists, it should be slapped."

Kate grew up in China before she was admitted to Oxford University in 2010. She was President of a student society during her first Master's degree, and she went on to work for JP Morgan and Goldman Sachs before she returned to Oxford to complete her MSc, according to her LinkedIn.

She has also been awarded a number of prizes and scholarships during her studies, as outlined by her profile on Oxford University's Mathematical Institute website.

As part of her PhD, Kate's work will see her use "higher-order nonconvex optimization algorithms and machine learning to address the mathematical challenges arising from multidimensional big data." We wish her every success.

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