Fenglin Yuan

Fenglin Yuan, PhD has a diverse work experience in machine learning and data science. Their most recent role is as a Senior Software Engineer at Tubi, where they focus on NLP embedding for recommendation systems and unsupervised learning for creating diverse content. Prior to that, they worked as a Machine Learning Engineer at American Express, leading the development of Aquila ML library and working on natural language processing, topic modeling, time series analysis, and building recommendation systems. They also have experience working as a freelance data scientist and Python developer. Earlier in their career, they served as a Postdoctoral Fellow at Johns Hopkins University, a Postdoctoral Research Associate at the University of Tennessee, a Visiting Scholar at Oak Ridge National Laboratory, and a Research Assistant at Rensselaer Polytechnic Institute.

Fenglin Yuan, PhD has a strong educational background. Fenglin obtained a Bachelor of Science (B.S.) degree in Materials Physics from Wuhan University, where they studied from 2004 to 2008. Following this, they pursued a Doctor of Philosophy (Ph.D.) degree in Materials Science and Engineering from 2008 to 2013 at Rensselaer Polytechnic Institute. In addition to their formal education, Fenglin Yuan has also obtained several certifications to enhance their knowledge and skills. Fenglin completed courses such as "Machine Learning on Google Cloud Platform" by Cloud Academy, Inc. and "Stanford Natural Language Processing with Deep Learning" from Stanford University in February 2020. Fenglin Yuan also received certifications in "MongoDB Basics" by MongoDB in July 2018 and completed various machine learning-related courses from Coursera, including "Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization," "Neural Networks and Deep Learning," and "Structuring Machine Learning Projects" in September 2017. Prior to that, they attended the "Certificate of Machine Learning for Materials Research Bootcamp & Workshop" at the University of Maryland in July 2016 and completed a course on "Machine Learning" through Coursera in September 2014. These additional certifications demonstrate Fenglin Yuan's dedication to continuous learning and professional development in their field.