About us

Yinyin is responsible for designing and building the technology roadmap to achieve the business and technology goals of XOKind. Through her years of experience in the machine learning domain, Yinyin has collaborated with CSPs and enterprises in various verticals to apply AI/Data Science to build/deploy AI systems and services, and has always been passionate about designing and packaging the right AI algorithms to solve problems for enterprises and end-users.Previously, Yinyin was the Head of Data Science in the Artificial Intelligence Products Group at Intel where she led a global team of deep learning researchers and data scientists that is engaged in in-depth data science for AI product engineering, as well as Natural Language Processing (NLP) and Reinforcement Learning (RL) research. She was responsible for setting the strategy and leading the execution of connecting data science and AI research with AI hardware, enabling AI use cases through open-source data science tools in NLP, RL, model compression, and working with Intel partners and customers on innovative AI solutions across industry domains. Yinyin has also driven algorithmic design for the Intel Nervana NNP-L, one of the first Deep learning training ASICs, and contributed to neon (open source DL framework) and nGraph (open source DL compiler). Yinyin represented Intel at the Partnership on AI, a multi-stakeholder organization that brings together around 100 academic, industry, and civil society organizations working on making AI beneficial for people and society. Prior to working at Intel, Yinyin was a Principal Data Scientist at Nervana Systems (acquired by Intel in 2016), where she was responsible for developing deep learning algorithms and frameworks, and AI solutions for enterprises. She also previously worked at Qualcomm Research as a ML/neuroscience researcher working on Deep Learning, Robotics and Neuromorphic computing.

Yinyin was named one of the 9 women in Silicon Valley to watch who are leading in AI by Silicon Valley Business Journal, and one of the top 30 Women in AI in US by RE.WORK. She has a Bachelor’s degree in Electrical Engineering from Northeastern University, China, and a Ph.D. focused in Machine Learning from Ohio University.