Weikai Qi

Weikai Qi has extensive experience in the field of research and data science. Weikai currently works as a Data Scientist at Future Fertility, starting in May 2022. Prior to that, they held multiple roles at Zentrela Inc., including Director of AI from June 2020 to April 2022 and Sr. Machine Learning Scientist from July 2018 to April 2022.

Before joining Zentrela Inc., Weikai served as a Research Associate at the University of Guelph from March 2018 to August 2018 and as a Postdoctoral Researcher from March 2016 to February 2018. Weikai also worked as a Postdoctoral Researcher at the University of Saskatchewan from February 2014 to February 2016 and at Utrecht University from September 2011 to January 2014.

Early in their career, Weikai gained research experience as a Research Assistant at The Hong Kong Polytechnic University from October 2008 to September 2010.

Overall, Weikai has built a strong foundation in research and data science through their diverse work experience in academia and industry.

Weikai Qi obtained a Bachelor of Science (BSc) degree in Theoretical Physics from Lanzhou University, starting in 2002 and graduating in 2006. Weikai continued their education at Lanzhou University, where they earned a Doctor of Philosophy (Ph.D.) degree in Theoretical Physics from 2006 to 2011.

In addition to their formal education, Weikai Qi has also obtained several certifications. In 2017, they completed the "Machine Learning" course on Coursera, followed by "Neural Networks and Deep Learning," "Structuring Machine Learning Projects," "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," and "Convolutional Neural Networks." In 2018, they completed the "Sequence Models" course. More recently, in 2020, they obtained a certification in "Natural Language Processing with Classification and Vector Spaces." In 2021, they obtained a certification in "Information Security" from CITI Program, A Division of BRANY. Finally, in 2022, they completed the "Introduction to Machine Learning in Production" course on Coursera.