Zhibin Lu
About Zhibin Lu
Zhibin Lu is an AI Developer at Stradigi AI in Montreal, Quebec, Canada, where he has worked since 2021. He has a strong background in machine learning and natural language processing, with previous experience at Nuance Communications and a Master's degree from Université de Montréal.
Work at Stradigi AI
Zhibin Lu has been employed at Stradigi AI as an AI Developer since 2021. His role involves leveraging artificial intelligence technologies to develop innovative solutions. Based in Montreal, Quebec, Canada, he has contributed to various projects that utilize advanced machine learning techniques.
Previous Experience at Nuance Communications
Before joining Stradigi AI, Zhibin Lu worked at Nuance Communications as an NLU Researcher for a period of seven months in 2020. His work focused on natural language understanding, contributing to the development of technologies that enhance user interaction through improved language processing.
Education and Expertise
Zhibin Lu holds a Master's degree in Machine Learning and Natural Language Processing from Université de Montréal, where he studied from 2017 to 2019. He also completed a Cours de francisation at the same university from 2016 to 2017. His undergraduate studies were at Beijing Jiaotong University, where he earned a Bachelor's degree in Computer Science from 1999 to 2003.
Technical Skills and Contributions
Zhibin Lu has extensive experience in machine learning and deep learning, utilizing frameworks such as PyTorch and TensorFlow for over three years. He has over eight years of experience in ETL and SQL script programming, working with databases like MySQL, Oracle, SQL Server, and MongoDB. Additionally, he has over six years of experience in MTV/MVC application development using frameworks including Flask, Spring Boot, and Angular.
Achievements in AI and Competitions
Zhibin Lu contributed to the development of VGCN-BERT, a model designed to enhance BERT with graph embedding for improved text classification. He also achieved third place in the HASOC2019 Competition, demonstrating his skills in offensive content detection.