个人简历

葛志强，教授，博士生导师。分别于2004年和2009年于浙江大学获工学学士和工学博士学位。2010年7月至2011年12月，任香港科技大学化学与生物分子工程学系研究助理，2013年1月至2013年5月为加拿大Alberta大学化工系访问教授，2014年11月至2017年1月于德国Duisburg-Essen大学从事“洪堡学者”研究工作，2018年6月至2018年8月为日本JSPS研究学者在京都大学从事合作研究

研究领域

工业大数据
机器智能
知识自动化
数据驱动技术

近期论文

Guangjie Chen, Zhiqiang Ge*. Robust Bayesian Networks for Low-Quality Data Modeling and Process Monitoring Applications. Control Engineering Practice, 2020, 97, 104344.
Le Yao, Zhiqiang Ge*. Refining Data-driven Soft Sensor Modeling Framework with Variable Time Reconstruction. Journal of Process Control, 2020, 87, 91-107.
Qingqiang Sun, Zhiqiang Ge*. Deep Learning for Industrial KPI Prediction: When Ensemble Learning Meets Semi-Supervised Data. IEEE Transactions on Industrial Informatics, 2020, 10.1109/TII.2020.2969709.
Bingbing Shen, Zhiqiang Ge*. Supervised Nonlinear Dynamic System for Soft Sensor Application aided by Variational Auto-encoder. IEEE Transactions on Instrumentation & Measurement, 2020, 10.1109/TIM.2020.2968162.
Le Yao, Weiming Shao, Zhiqiang Ge*. Hierarchical Quality Monitoring for Large-scale Industrial Plants with Big Process Data. IEEE Transactions on Neural Networks and Learning Systems, 10.1109/TNNLS.2019.2958184.
Zeyu Yang, Le Yao, Zhiqiang Ge*. Streaming Parallel Variational Bayesian Supervised Factor Analysis for Adaptive Soft Sensor Modeling with Big Process Data. Journal of Process Control, 2020, 85, 52-64.
Bingbing Shen, Le Yao, Zhiqiang Ge*. Nonlinear probabilistic latent variable regression models for soft sensor application: From shallow to deep structure. Control Engineering Practice, 2020, 94, 104198.
Xinyu Zhang, Zhiqiang Ge*. Automatic Deep Extraction of Robust Dynamic Features for Industrial Big Data Modeling and Soft Sensor application. IEEE Transactions on Industrial Informatics, 2019, 10.1109/TII.2019.2945411.
Gecheng Chen, Yue Liu, Zhiqiang Ge*. K-means Bayes algorithm for imbalanced fault classification and big data application. Journal of Process Control, 2019, 81, 54-64.
Le Yao, Zhiqiang Ge*. Scalable learning and probabilistic analytics of industrial big data based on parameter server: framework, methods and applications. Journal of Process Control, 2019, 78, 13-33.
Le Yao, Zhiqiang Ge*. Distributed parallel deep learning of Hierarchical Extreme Learning Machine for multimode quality prediction with big process data. Engineering Applications of Artificial Intelligence, 2019, 81, 450-465.
Xinyu Zhang, Zhiqiang Ge*. Local Parameter Optimization of LSSVM for Industrial Soft Sensing with Big Data and Cloud Implementation. IEEE Transactions on Industrial Informatics, 2019, 10.1109/TII.2019.2900479
Le Yao, Zhiqiang Ge*. Scalable Semisupervised GMM for Big Data Quality Prediction in Multimode Processes. IEEE Transactions on Industrial Electronics, 2019, 66(5), 3681-3692.
Zhiqiang Ge*, Xinru Chen. Dynamic probabilistic latent variable model for process data modeling and regression application. IEEE Transactions on Control Systems Technology, 2019, 27(1), 323-331.
Zhiqiang Ge*, Yue Liu. Analytic Hierarchy Process Based Fuzzy Decision Fusion System for Model Prioritization and Process Monitoring Application. IEEE Transactions on Industrial Informatics, 2019, 15(1), 357-365.
Jinlin Zhu, Zhiqiang Ge*, Zhihuan Song, Furong Gao. Review and big data perspectives on robust data mining approaches for industrial process modeling with outliers and missing data. Annual Reviews in Control, 2018, 46, 107-133.
Guangjie Chen, Zhiqiang Ge*. Hierarchical Bayesian Network Modeling Framework for Large-scale Process Monitoring and Decision Making. IEEE Transactions on Control Systems Technology, 2018, DOI: 10.1109/TCST.2018.2882562.
Zhiqiang Ge*. Process data analytics via probabilistic latent variable models: A tutorial review. Industrial & Engineering Chemistry Research, 2018, 57, 12646-12661.(期刊封面论文)
Le Yao, Zhiqiang Ge*. Big data quality prediction in the process industry: a distributed parallel modeling framework. Journal of Process Control, 2018, 68, 1-13.
Zhiqiang Ge*. Distributed predictive modeling framework for prediction and diagnosis of key performance index in plant-wide processes. Journal of Process Control, 2018, 65, 107-117.
Le Yao, Zhiqiang Ge*. Deep Learning of Semi-supervised Process Data with Hierarchical Extreme Learning Machine and Soft Sensor Application. IEEE Transactions on Industrial Electronics, 2018, 65, 1490-1498.
Jinlin Zhu, Zhiqiang Ge*, Zhihuan Song, Le Zhou, Guangjie Chen. Large-Scale Plant-wide Process Modeling and Hierarchical Monitoring: A Distributed Bayesian Network Approach. Journal of Process Control, 2018, 65, 91-106.
Le Zhou, Jiaqi Zheng, Zhiqiang Ge*, Zhihuan Song, S Shan. Multimode Process Monitoring Based on Switching Autoregressive Dynamic Latent Variable Model. IEEE Transactions on Industrial Electronics, 2018, 65, 8184-8194.
Zhiqiang Ge*, Zhihuan Song, Steven X Ding, Biao Huang. Data mining and analytics in the process industry: the role of machine learning. IEEE Access, 2017, 5, 20590-20616.
Zhiqiang Ge*. Review on data-driven modeling and monitoring for plant-wide industrial processes. Chemometrics & Intelligent Laboratory Systems, 2017, 171, 16-25.\