实验室成员
刘礼
实验室 副主任
一直致力于从事传感大数据分析技术及其应用研究，主持国家基金委面上项目、青年基金，国家重大研发计划项目子课题，重庆市科委重大专项，教育部科研启动基金等10余项，主研完成欧盟框架7重大项目，国家重点基础研究项目(973计划)重大重点等项目近20项；已发表论文100余篇，其中SCI论文近40篇、SSCI论文4篇，其中JCR一区论文20余篇，ESI高被引论文2篇，CCF ABC列表论文40余篇，包括AAAI、CSCW、PR、INS等人工智能顶级期刊会议，Google引用2000+次；申请发明专利10余项；担任Sensors、Web Intelligence等国际SCI期刊的客座主编，在UbiComp、CSCW等CCF ABC类国际会议或研讨会任程序委员会主席、委员等，任全国可穿戴计算会议秘书长，以及IEEE Transactions on Cybernetics,IEEE Intelligent Systems,IEEE Transactions on Learning Technologies等人工智能顶级期刊的评审；重庆市高层次人才。
创立了重庆大学物联网体感大数据实验室；结合大数据技术实际应用于建筑、医疗、制造等行业，与重庆本地企事业单位合作，研发完成大数据驱动的智慧建筑工地信息管理平台、肿瘤风险等级预测模型、长安汽车发动机生产质量预测等一系列实际上线应用，实现了技术创新与科技成果转化。
主要研究方向：
1. 大数据分析：因果学习技术、数据分析应用（医疗健康、教育、工业制造等）
2. 人工智能：① AI艺术（设计图、艺术图等自动生成技术）② 人机交互技术（智能穿戴技术、VR/AR交互技术）。
项目成果展示：
1. 人机交互技术应用
【项目1 - Project I】 穿戴式手套及其应用
【项目2 - Project II】 穿戴设备与VR结合的教育技术应用
【项目3 - Project III】 AR术中导航系统
2. AI设计
【项目1 - Project I】 汽车造型智能设计
【项目2 - Project II】 脸谱艺术智能设计
3. 数据分析应用
【项目1 - Project I】 发动机生产性能预测
【项目2 - Project II】 肿瘤风险预测
近期主要项目：
1. 国家自然科学基金委面上项目 “基于生理特征感知的具身学习认知负荷智能测评研究” 2020.01-2023.12 主持
2. 国家“新一代人工智能”重大科技专项 “基于跨媒体知识图谱的因果计算 （课题：基于因果图谱的跨媒体创意设计）” 2020.01-2022.12 子课题主持
3. 国家自然科学基金委青年项目 “普适环境下支持生物电信号的多模态情感特征建模和推理研究” 2011.01-2013.12 主持
4. 国家重点研发计划 “综合科技服务资源集成应用关键技术研究” 2018.05-2020.11 主研
5. 工信部科技计划项目 “长安汽车智能柔性高速冲压新模式应用” 2017.06-2018.06 主研
代表性论文：数据分析、因果学习技术及其应用
1.刘礼，吴飞，李廉，因果关系学习的思维取向和概念分析，中国大学教学，(10),35-42，2021.
2. Luo, H., Liao, J., Yan, X.W., Liu, L.*. Oversampling by a constraint-based causal network in medical imbalanced data classification, 2021 International Conference on Multimedia and Expo, ICME 2021. (CCF B)
3. Su, G.X., Liu, L.*,Zhang, M.J., Rosenblum, D.S., Quantitative Verification for Monitoring Event-Streaming Systems, IEEE Transactions on Software Engineering, 2020. (accepted) (JCR一区, CCF A)
4. Liao, J., Hu, J.F., Liu, L.*, Recognizing Complex Activities by a Temporal Causal Network-Based Model, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020. (CCF B)
论文：
5. Yan, X.W., Liao, J., Luo, H., Liu, L.*, Predicting cancer risks by a constraint-based causal network, 2020 IEEE International Conference on Multimedia and Expo, ICME 2020. (CCF B)
5. Zhang, S.P., Dong, J.Q., Liu, L., Huang, Z.G., Huang, L., Lai, Y.C., Reinforcement learning meets minority game: Toward optimal resource allocation, Physical Review E, 99(032302), 2019. (JCR一区)
6. He, S., Deng, K., Li, L., Shu, S., Liu, L., Discriminatively Relabel for Partial Multi-label Learning, 2019 IEEE International Conference on Data Mining, ICDM 2019, 280-288, 2019. (CCF B)
代表性论文：交互技术及智能识别方法
1. Li, X., Liao, J., Liu, L.*. Recognizing Skeleton-Based Hand Gestures by a Spatio-Temporal Network, The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2021.(CCF B)
2. Hu, J.F., Liao, J., Fan, Z.C., Liu, L.*, Predicting Long-Term Skeletal Motions by a Spatio-Temporal Hierarchical Recurrent Network, The 24th European Conference on Artificial Intelligence, ECAI 2020. (CCF B)
3. Liu, L., Wang, S., Hu, B., Qiong, Q.Y., Wen, J.H., Rosenblum, D.S., Learning structures of interval-based Bayesian networks in probabilistic generative model for human complex activity recognition, Pattern Recognition 81:545-561, 2018. (JCR一区, CCF B)
4. Liu, L., Wang, S., Su, G.X., Huang, Z.G., Liu, M., Towards complex activity recognition using a Bayesian network-based probabilistic generative framework, Pattern Recognition, 68:295–309, 2017 (JCR一区, CCF B)
5. Lu, Y.G., Wei, Y., Liu, L.*, Zhong, J., Sun, L.T., Liu, Y., Towards Unsupervised Physical Activity Recognition Using Smartphone Accelerometers, Multimedia Tools and Applications, 76(8):10701-10719, 2017. (ESI高被引论文，JCR二区, CCF C)
6. Liu, L., Wang, S., Su, G.X., Hu, B., Peng, Y.X., Xiong, Q.Y., Wen, J.H., A framework of mining semantic-based probabilistic event relations for complex activity recognition, Information Sciences, 418-419:13-33, 2017. (JCR一区, CCF B)
7. Liu, L., Wang, S., Peng, Y.X., Huang, Z.G., Liu, M., Hu, B., Mining intricate temporal rules for recognizing complex activities of daily living under uncertainty, Patten Recognition, 60:1015-1028, 2016. (JCR一区, CCF B)
8. Liu, L., Peng, Y.X., Wang, S., Huang, Z.G., Liu, M., Complex Activity Recognition Using Time Series Pattern Dictionary Learned from Ubiquitous Sensors, Information Sciences, 340–341:41–57, 2016. (JCR一区, CCF B)
9. Liu, Y., Nie, L.Q., Liu, L., Rosenblum, D.S., Action to Activity: Sensor-Based Activity Recognition, Neurocomputing, 181:108–115, 2016. (ESI高被引论文，JCR一区, CCF C)
10. Liu, L., Cheng, L., Liu, Y., Jia, Y.P., Rosenblum, D.S., Recognizing Complex Activities by a Probabilistic Interval-Based Model, The 30th AAAI Conference on Artificial Intelligence, AAAI 2016, pp. 1266- 1272, AAAI press, 2016. (CCF A)
11. Jia, Y.P., Song, X.M., Zhou, J.B., Liu, L.*, Nie, L.Q., Rosenblum, D.S., Fusing Social Networks with Deep Learning for Volunteerism Tendency Prediction, The 30th AAAI Conference on Artificial Intelligence, AAAI 2016, pp. 165- 171, AAAI press, 2016. (CCF A)
代表性论文：智能教育技术应用
1. Liu, M., Rus, V., Liu, L., Automatic Chinese multiple choice question generation using mixed similarity strategy, IEEE Transactions on Learning Technologies, 11(2):193-202, 2018. (JCR一区, SSCI)
2. Liu, M., Liu, L.P., Rus, V., Liu, L., Group awareness increases student engagement in online collaborative writing, The Internet and Higher Education, 38:1-8, 2018. (JCR一区, SSCI)
3. Liu, M., Rus, V., Liu, L., Automatic Chinese Factual Question Generation, IEEE Transactions on Learning Technologies, 10(2):194-204, 2017. (JCR一区, SSCI)
4. Liu, M., Rus, V., Liao, Q., Liu, L., Encoding and Ranking Similar Chinese Characters, Journal of Information Science and Engineering, 33(5): 1195-1211, 2017. (JCR四区)
5. Liu, M., Li, Y., Xu, W.W., Liu, L., Automated Essay Feedback Generation and Its Impact in the Revision, IEEE Transactions on Learning Technologies, 10(4): 502-513, 2017. (JCR一区, SSCI)