Mingxuan Lu
About Mingxuan Lu
Mingxuan Lu is a Data Science R&D Intern at CCC Intelligent Solutions, with a background in Electrical and Computer Engineering. He has experience in research and software development roles at institutions like Shanghai Jiao Tong University and Intel Corporation, and has contributed to significant projects in machine learning and fraud detection.
Work at CCC Intelligent Solutions
Mingxuan Lu currently holds the position of Data Science R&D Intern at CCC Intelligent Solutions. He began this role in 2023 and has been working remotely from New York, United States. In this capacity, he engages in research and development activities focused on data science, contributing to the company's innovative projects.
Education and Expertise
Mingxuan Lu completed his Master of Science in Electrical Engineering at Columbia University from 2022 to 2023. Prior to this, he earned a Bachelor of Engineering in Electrical and Computer Engineering from the UM-SJTU Joint Institute at Shanghai Jiao Tong University, where he studied from 2018 to 2022. His educational background provides a strong foundation in engineering principles and data science methodologies.
Background
Before joining CCC Intelligent Solutions, Mingxuan Lu gained valuable experience through various internships. He worked as a Deep Learning Software Intern at Intel Corporation for four months in 2022 and as a Machine Learning Intern at eBay for four months in 2021. Additionally, he served as a Research Assistant at Shanghai Jiao Tong University for a total of seven months in 2021, where he contributed to academic research.
Achievements
Mingxuan Lu has received recognition for his contributions to the field of data science. He was awarded the HealthX Overachievement Award for his role in accelerating digital transformation in the healthcare industry. Furthermore, he published as the first author on a paper presented at CIKM 2022, detailing his work on BRIGHT, a graph neural network designed for real-time fraud detection.
Projects and Contributions
Mingxuan Lu has led an international team of nine engineers in developing and enhancing a graph neural network for fraud detection. He implemented a parallelized breadth-first search on the Million Song Dataset using Apache Spark and Hadoop, which significantly reduced data processing time. These projects highlight his technical skills and ability to collaborate effectively in diverse teams.