Women in Machine Learning: Negar Rostamzadeh

The recent debacle surrounding <a href="https://gizmodo.com/exclusive-heres-the-full-10-page-anti-diversity-screed-1797564320" rel="noopener ugc nofollow" target="_blank">Google’s James Damore</a>’s memo and subsequent firing illustrates that the source of gender imbalance in tech is still hotly disputed in certain quarters. But many organisations think it’s pretty clear that this gender imbalance stems from current social and cultural norms, and are putting their weight behind the people trying to do something about it. <a href="https://mila.quebec/en/person/negar-rostamzadeh/" rel="noopener ugc nofollow" target="_blank">Negar Rostamzadeh</a>, a fundamental research scientist at Element AI, is one of those toiling away at the grassroots level to help grow the number of successful women in computer science. When she’s not working on deep learning for video classification and generation, she’s organizing this year’s <a href="http://wimlworkshop.org/2017/" rel="noopener ugc nofollow" target="_blank">Women in Machine Learning (WiML) workshop at NIPS</a>, <a href="https://wicvworkshop.github.io/" rel="noopener ugc nofollow" target="_blank">Women in Computer Vision</a> <a href="https://wicvworkshop.github.io/" rel="noopener ugc nofollow" target="_blank">(WiCV) at CVPR</a> and <a href="https://www.facebook.com/events/210738812737108/" rel="noopener ugc nofollow" target="_blank">Women in Deep Learning</a> (WiDL). We sat down to discuss her role in these organisations and her perspective making our community more diverse and inclusive. <a href="https://medium.com/element-ai-research-lab/women-in-machine-learning-negar-rostamzadeh-dbb58dc75e81">Website</a>