Ran Jin

Ran Jin is a Professor in the Department of Industrial and Systems Engineering at Virginia Tech, leading the Data Science and Visualization Lab. He holds academic appointments in the College of Engineering. His research focuses on integrating data science with manufacturing systems engineering, emphasizing system informatics, quality control, and process optimization. He has contributed to advancements in profile modeling, defect detection, and statistical process monitoring in industries like additive manufacturing.

Education:

• Ph.D., Georgia Institute of Technology, 2011
• M.A. and M.S., University of Michigan, 2009 and 2007
• B.Eng., Tsinghua University, 2005

Research Interests: Jin's work bridges statistical methodologies with engineering systems, particularly in high-definition profile data analysis, ensemble modeling for manufacturing scale-up, and cybermanufacturing challenges. He develops algorithms for process variation reduction and real-time monitoring. His recent focus includes AI-driven solutions for manufacturing resilience and distributed data systems.

Recognition: Jin has received awards such as the Best Applied Paper Award (IIE Transactions) and NSF grants for projects like 'EAGER: AM: CoFedAI' and 'QQ Models' for mixed quality responses. His contributions span academic journals and industry partnerships, including collaborations with JSME Co. Ltd. and the Commonwealth Center for Advanced Manufacturing.

Grants & Projects: Key initiatives include 'Distributed Data Filtering for Fog Manufacturing' and 'AI Incubation in Manufacturing.' He has served as PI or Co-PI on NSF-funded projects addressing experimental design, anomaly detection, and thermal spray process modeling.

Labs & Teams: Directs the Data Science and Visualization Lab, fostering innovation in AI applications for smart manufacturing and system informatics. Engages in interdisciplinary research through roles like Co-Chair of the Commission on Research at Virginia Tech.