About

Sheng Chen is a highly skilled and experienced Software Engineer with expertise in Machine Learning and Web Data Processing. With over 11 years of relevant experience, he has worked with several renowned companies and has a strong publication record in the field of Machine Learning algorithm design and application. In his current role as a Software Engineer at Google, Sheng Chen is responsible for developing production models of Machine Learning for business applications. He is exceptionally good at programming in Python, Java, and C, and has extensive knowledge of Machine Learning algorithm design and application in text and web data processing. Prior to joining Google, Sheng Chen worked with Bank of America as a VP, where he gained valuable experience in the financial sector. He also worked with Demand Media as an Algorithm Engineer, where he developed an algorithmic ranking system to recommend relevant link sets for articles and videos on the ehow website. He also developed and deployed a non-blocking web service that enables clients to query databases through URLs asynchronously. Sheng Chen holds a Ph.D. in Computer Engineering/Machine Learning from Stevens Institute of Technology, where he worked on machine learning algorithm design to solve the problem of learning from stream data, such as video stream, and data with skewed class distribution, such as spam messages. He also holds an M.Sc. in Electrical Engineering from Huazhong University of Science and Technology, where he gained expertise in the field of Electrical Engineering. Sheng Chen is a Senior Software Engineer with a strong background in Machine Learning and Web Data Processing. He is a highly motivated individual with exceptional programming skills and a strong publication record. His specialties include Machine Learning algorithm design, application in text/web data processing, and developing production models of Machine Learning for business applications.