I am currently working as a Research Scientist at Google Cloud AI. My current work is motivated by the mission of democratizing AI and bringing it to the most impactful use cases, from Healthcare, Finance, Retail, Media, Education, Communications and many other industries. Towards this goal, I focus on how to make AI more high-performance for the most-demanded data types, interpretable, trustable, data-efficient, robust and reliable. I led research projects that were launched as major Google Cloud products and yielded significant business impact, such as TabNet and Covid-19 forecasting.
Before joining Google, I was a Research Scientist at Baidu Silicon Valley AI Lab. At Baidu, I have focused on deep learning research, particularly for applications in human-technology interfaces. I co-developed deep learning-based state-of-the-art speech synthesis (Deep Voice 1, Deep Voice 2 and Deep Voice 3), keyword spotting, voice cloning, and neural architecture search systems. Some of my recent work has been featured in mainstream and scientific media, including The Next Web, Futurism, Engadget, The Register, MIT Technology Review, and The Verge.
Prior to Baidu, I completed my PhD degree in Electrical Engineering at Stanford University in 2016. My past experiences in AI and machine learning include applications in digital communications and networking, quantitative finance, image processing and medical diagnosis. In a broad sense, my background lies at the intersection of computer sciences, information sciences and physical sciences, motivated by both fundamental problems and high-impact applications. I have co-authored more than 50 journal and conference publications. Please see my Google Scholar page or CV for a complete list and more details.
Copyright © Sercan Arik 2020.