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Qingyun Wang has extensive experience in the field of machine learning. Starting in 2021, they are currently a Machine Learning Engineer at Sanctuary AI and Bluvec Technologies Inc, where they are responsible for building pipelines for data collection and cleaning, model training and deployment, researching state-of-the-art real-time object detection and tracking algorithms, and software development in Python, C++ and golang. Prior to this, they were a Data Science Fellow at Insight Data Science in 2020, a Paul Olum Research Scholar at the University of Oregon in 2016, a Postdoctoral Researcher at the University of Toronto in 2013, and a Dissertation Fellowship and Research Assistant at Washington University in St. Louis in 2012.

Qingyun Wang's education history includes a Doctor of Philosophy (Ph.D.) in Mathematics from Washington University in St. Louis from 2008 to 2013, a Bachelor in Mathematics from Zhejiang University from 2004 to 2008, and a High School diploma from High school attached to Hunan normal uniiversity from 2001 to 2004. Wang has also obtained certifications from Coursera in Data Structures and Algorithms Specialization (September 2019), TensorFlow in Practice Specialization (August 2019), Deep Learning Specialization (June 2019), and Machine Learning (March 2019).