معرفی
Yinan Wang serves as an Assistant Professor in the Department of Industrial and Systems Engineering at Renssela Polytechnic Institute (RPI), focusing on engineering-driven machine learning applications for advanced manufacturing and robotics systems.
Education:
- Ph.D., Industrial and Systems Engineering, Virginia Tech, 2022
- M.S., Electrical Engineering, Columbia University, 2019
- B.S., Electrical Engineering and Automation, Xi'an Jiaotong University, 2017
Research Interests: Dr. Wang's work bridges machine learning with industrial engineering through deep learning, uncertainty quantification, and system intelligence. His research targets advanced manufacturing challenges including robotic path planning, 3D anomaly detection, and environmental monitoring systems. Key application areas span aerospace assembly, toxic plume prediction, and quality control in industrial settings.
Publication Trends: His 2024-2025 publications reveal three dominant themes: (1) transformer model compression for time-series forecasting (Smartformer), (2) geometric contrast learning for industrial point cloud segmentation (GeoContrast), and (3) multimodal physiological signal analysis for aviation safety prediction. These works consistently integrate physics-based constraints with deep learning architectures.
Scientific Awards:
- Mary G. and Joseph Natrella Scholarship, American Statistical Association (ASA), 2022
- Featured Article in ISE Magazine, Institute of Industrial and Systems Engineers (IISE), 2022
- SPES + Q&P Best Student Paper Award, American Statistical Association (ASA), 2022
- Educational Foundation Scholarship and Analysis Division Scholarship, International Society of Automation (ISA), 2021
- Gilbreth Memorial Fellowship, Institute of Industrial and Systems Engineers (IISE), 2021
- Data Mining & Decision Analytics (DMDA) Best Theoretical Paper Award, INFORMS, 2021
- Finalist of Best Student Paper Award, Quality, Statistics & Reliability (QSR) Section, INFORMS, 2021
- Best Poster Award, Manufacturing Science & Engineering Conference (MSEC), ASME, 2021
Advising and Grants: No publicly listed advisees or specific grant awards appear in the source material, though his extensive publication record and research center affiliations suggest active grant-supported projects.
Labs and Teams: Dr. Wang contributes to RPI's Institute for Data Exploration and Applications (IDEA) and Center for Materials, Devices, and Integrated Systems (CMDIS), participating in interdisciplinary teams focused on data-driven engineering solutions.
