The Laboratory of Cognitive Computation and Applied Technology (LCCAT) was founded in July, 2016, and is based at Xi’an Jiaotong Liverpool University, Suzhou, China. LCCAT currently has 37 researchers, and the main research interests of the Lab are pattern recognition, cognitive learning, machine learning, and their applications in text, image, sound, and video. Research in LCCAT has been supported by many grants from organisations such as the National Natural Science Foundation of China, Jiangsu Science and Technology Programme-Key Research & Development Project , and industrial cooperation. The laboratory has published 8 academic monographs with internationally renowned publishers such as Springer and has contributed over 200 high-quality academic papers. These include publications in top-tier conferences such as ICML, NeurIPS, ICLR, UAI, CVPR, ICCV, SIGIR, and WSDM, as well as in leading journals such as IEEE T-PAMI, IEEE T-NNLS, IEEE T-Cybernetics, IEEE T-IP, IJCV, JMLR, and Machine Learning.
Research Areas
The laboratory is dedicated to innovative research in artificial intelligence and computational technologies. Its core focuses include foundational theoretical research in pattern recognition, machine learning, and computer vision, along with explorations in cutting-edge areas such as high-performance computing and cognitive machine learning. The laboratory is particularly attentive to breakthroughs in key technologies for processing massive multimedia information and actively promotes the practical application of novel technologies in industry. This has enabled the development of a comprehensive research system that spans from fundamental research to applied innovation.
2018 Technical Committee Meeting of LCCAT
2019 Technical Committee Meeting of LCCAT
LCCAT has published eight books with Springer and about 200 papers. In particular, LCCAT members have published high-quality papers in top conferences such as NeurlPS, ICDM, IJCAI, UAI, ICML, CVPR, SIGIR, ECML and the WSDM, as well as in top journals like IEEE T-PAMI, IEEE-T-NNLS, IEEE-T Cybernetics, IEEE-T IP, JMLR, Neural Computation, Machine Learning.
Overview
The Laboratory of Cognitive Computation and Applied Technology (LCCAT) was founded in July, 2016, and is based at Xi’an Jiaotong Liverpool University, Suzhou, China. LCCAT currently has 37 researchers, and the main research interests of the Lab are pattern recognition, cognitive learning, machine learning, and their applications in text, image, sound, and video. Research in LCCAT has been supported by many grants from organisations such as the National Natural Science Foundation of China, Jiangsu Science and Technology Programme-Key Research & Development Project , and industrial cooperation. The laboratory has published 8 academic monographs with internationally renowned publishers such as Springer and has contributed over 200 high-quality academic papers. These include publications in top-tier conferences such as ICML, NeurIPS, ICLR, UAI, CVPR, ICCV, SIGIR, and WSDM, as well as in leading journals such as IEEE T-PAMI, IEEE T-NNLS, IEEE T-Cybernetics, IEEE T-IP, IJCV, JMLR, and Machine Learning.
Research Areas
The laboratory is dedicated to innovative research in artificial intelligence and computational technologies. Its core focuses include foundational theoretical research in pattern recognition, machine learning, and computer vision, along with explorations in cutting-edge areas such as high-performance computing and cognitive machine learning. The laboratory is particularly attentive to breakthroughs in key technologies for processing massive multimedia information and actively promotes the practical application of novel technologies in industry. This has enabled the development of a comprehensive research system that spans from fundamental research to applied innovation.
2018 Technical Committee Meeting of LCCAT
2019 Technical Committee Meeting of LCCAT
LCCAT has published eight books with Springer and about 200 papers. In particular, LCCAT members have published high-quality papers in top conferences such as NeurlPS, ICDM, IJCAI, UAI, ICML, CVPR, SIGIR, ECML and the WSDM, as well as in top journals like IEEE T-PAMI, IEEE-T-NNLS, IEEE-T Cybernetics, IEEE-T IP, JMLR, Neural Computation, Machine Learning.