Intelligent soft sensing
Robust latent-variable and probabilistic learning for quality variables that cannot be measured online.
Industrial intelligence · Measurement · Learning
Reliable learning for
complex industrial systems.
I am an associate professor in the School of Information Engineering at Beijing Institute of Petrochemical Technology. My work develops reliable data-driven methods for complex industrial processes, with an emphasis on intelligent soft sensing, process monitoring and fault diagnosis, and structured-light 3D measurement.
Research
Focused questions, practical impact.
Process monitoring
Condition-aware representations for fault diagnosis, early warning, and dynamic industrial processes.
Structured-light 3D
Adaptive learning and geometric reconstruction for accurate fringe-projection profilometry.
Selected publications
Recent work.
2026
Causal-stabilized latent regression for robust industrial soft sensors
Engineering Applications of Artificial Intelligence, 170, 114185
DOI2025
Generalized collaborative relevance vector regression for soft sensors
Information Sciences, 686, 121311
DOI2025
Geometric-Temporal Potential Warping for Multidimensional Dynamic Trajectory Alignment in Industrial Processes
Industrial & Engineering Chemistry Research, 64(29), 14590–14600
DOI2024
A Novel Generalized Adaptive Domain Fusion Framework for Structured Light 3-D Measurement
IEEE Sensors Journal, 24(3), 3223–3231
DOIStudents & people
Learning through collaboration.
News
Selected updates.
Causal-stabilized latent regression for robust industrial soft sensors was published in Engineering Applications of Artificial Intelligence.
New work on geometric-temporal potential warping appeared in Industrial & Engineering Chemistry Research.
Received a Science and Technology Progress Award and was recognized for outstanding undergraduate thesis supervision in Beijing.