About Mingjie

Mingjie Tang works on LLM systems and algorithms. He previously served as tech lead at Ant Group and as a member of the technical staff at Hortonworks/Cloudera. His research interests include database systems, distributed machine learning, big data computation, and distributed deep learning.

He received his PhD in Computer Science from Purdue University, West Lafayette, Indiana, under the supervision of Professor Walid G. Aref. His doctoral research focused on distributed systems for spatial computation, machine learning, and artificial intelligence.

Industry Experience

2025.11 - present Researcher, Consultant, iQuest Research Lab
2018.10 - 2022.10 AI Engineer, Ant Group, CA, USA
2016.9 - 2018.10 Member of tech staff, Hortonworks, CA, USA
2015.5 - 2015.8 Research Intern, IBM Research Almaden, CA, USA
2012.5 - 2012.8 Software Engineer Intern, Microsoft, Seattle, USA

Education

2010.9 - 2016.9 PhD, Purdue University, IN, USA
2010.9 - 2012.12 M.S., Purdue University, IN, USA
2007.9 - 2010.7 M.S., University of Chinese Academy of Sciences, Beijing, China
2003.8 - 2007.7 B.S., Sichuan University, Chengdu, China

Publication (Recent)

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2026

  • DLRover-LM: LLM Pre-Training Framework with Thousands of Accelerators in AntGroup
    Ziling Huang, Zhengmao Ye, Qingsong Cai, Zelong Huang, Bo Sang, Haitao Zhang, Jian Sha, Tingfeng Lan, Hui Lu, Yuanchun Zhou, Mingjie Tang
    Proceedings of the IEEE International Conference on Data Engineering (ICDE '26), May 2026.

2025

  • Concise reasoning via reinforcement learning
    Mehdi Fatemi, Banafsheh Rafiee, Mingjie Tang, Kartik Talamadupula

2024

2023