LU Yu, Ph.D., Associate Professor

  卢 宇, 副教授,博士生导师

   Director of Artificial Intelligence Lab, Advanced Innovation Center for Future Education

   School of Educational Technology, Faculty of Education

   Beijing Normal University, Beijing, China

   Address: No.19, St. Xinjiekouwai, Haidian District, Beijing, 100875, China

   Tel: (+8610) 5880 6750(Office)


Research Interests

  • Learner Modeling, Robotics for Education

  • Intelligent Tutoring System, Educational Data Mining

  • Data Analytics and Ubiquitous Computing

  • Short Biography

    LU Yu received the Ph.D. degree from National University of Singapore in computer engineering, and B.S./M.S. degrees from Beijing University of Aeronautics and Astronautics (Beihang University). He is currently an Associate Professor with the School of Educational Technology, Faculty of Education, Beijing Normal University (BNU), where he also serves as the director of the artificial intelligence lab at the advanced innovation center for future education (AICFE). He has published more than 60 academic papers in the prestigious journals and conferences (e.g., IEEE TKDE, TMC, ICDM, AIED, AAAI, CIKM, EDBT, IJCAI, ICDE), and currently serves as the PC member for multiple international conferences (e.g., AAAI, AIED, EMNLP, CIKM). Before joining BNU, he was a research scientist and principle investigator at the Institute for Infocomm Research (I2R), A*STAR, Singapore.

    Academic Service

  • Program Committee (PC) member, International Conference on Artificial Intelligence in Education (AIED)

  • Program Committee (PC) member, AAAI Conference on Artificial Intelligence (AAAI)

  • Program Committee (PC) member, International Conference on Empirical Methods in Natural Language Processing (EMNLP)

  • Program Committee (PC) member, International Conference on Information and Knowledge Management (CIKM)

  • Reviewer, IEEE TKDE, IEEE TLT, ACM TIST, Elsevier PMC, EDM, etc.

  • Selected Publications  (* Corresponding author  )

        Selected Journal Papers:

  • Thyago Tenório, Seiji Isotani, Ig Ibert Bittencour, Yu Lu, “The State-of-the-Art on Collective Intelligence in Online Educational Technologies,” IEEE Transactions on Learning Technologies (IEEE TLT), vol.14, no.2, pp.257-271, 2021. [PDF]

  • Penghe Chen, Yu Lu*, Shengquan Yu, Qi Xu, Jiefei Liu, “A Dialogue System for Identifying Need Deficiencies in Moral Education," Journal of Pacific Rim Psychology (JPRP), vol.15, pp.1-15,2021. [PDF]

  • Muhammad Qasim Memon, Yu Lu*, Penghe Chen, et al., “An ensemble clustering approach for topic discovery using implicit text segmentation,” Journal of Information Science, vol.47, no.4, pp.431-457, 2021. [PDF]

  • Ig Ibert Bittencourt*, Leogildo Freires, Yu Lu*, et al., “Validation and psychometric properties of the Brazilian-Portuguese dispositional flow scale 2,” PLOS One, 16(7): e0253044, 2021. [PDF]

  • Hongye Tan, Chong Wang, Qinglong Duan, Yu Lu*, Hu Zhang, Ru Li, “Automatic short answer grading by encoding student responses via a graph convolutional network,” Interactive Learning Environments, vol.29, pp.1-15, 2020. [PDF]

  • Yu Lu, Huayu Wu, Xin Liu, Penghe Chen, “TourSense: A Framework for Tourist Identification and Analytics Using Transport Data," IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), vol.31, no.12, pp.2407-2422,2019. [PDF]

  • Yu Lu, Jingjing Zhang, Baoping Li, Penghe Chen, Zijun Zhuang, “Harnessing Commodity Wearable Devices to Capture Learner Engagement,” IEEE Access, vol.7, pp.15749-15757, 2019. [PDF]

  • Yu Lu, Archan Misra, Wen Sun, Huayu Wu, “Smartphone Sensing Meets Transport Data: A Collaborative Framework for Transportation Service Analytics,”IEEE Transactions on Mobile Computing (IEEE TMC), vol.17, no.4, pp.945-960, 2018. [PDF]

  • Yu Lu, Zeng Zeng, Huayu Wu, Jingjing Zhang, “An Intelligent System for Taxi Service: Analysis, Prediction and Visualization,” AI Communications, vol.31, no.1, pp.33-46, 2018. [PDF]

  • Penghe Chen, Yu Lu*, Vincent W Zheng, Xiyang Chen, Boda Yang, “KnowEdu: A System to Construct Knowledge Graph for Education,” IEEE Access, vol. 6, pp.31553-31563, 2018. [PDF]

  • Yu Lu, Sen Zhang, Zhiqiang Zhang, Wendong Xiao, Shengquan Yu, “A Framework for Learning Analytics Using Commodity Wearable Devices,” Sensors, vol. 17, no. 6. 2017. [PDF]

  • Yu Lu, Motani Mehul and W. C. Wong, “A QoE-Aware Resource Distribution Framework Incentivizing Context Sharing and Moderate Competition,” IEEE/ACM Transactions on Networking (IEEE TON), vol. 24, no.3, pp. 1364-1377, 2016. [PDF]

  • Yu Lu, Motani Mehul and W. C. Wong, “When Ambient Intelligence Meets the Internet: User Module Framework and its Applications,” Computer Networks (Elsevier COMNET), vol. 56, no.2, pp. 1763-1781, 2012. [PDF]

  • Jinkun Liu, Yu Lu, “Adaptive RBF neural network control of robot with actuator nonlinearities,” Control Theory and Applications (Springer), vol. 8, no. 2, pp. 249-256, 2010. [PDF]

  • 卢 宇, 王德亮, 章志, 陈鹏鹤,余胜泉. 智能导学系统中的知识追踪建模综述,现代教育技术,2021,31(11):87-95.[PDF]

  • 卢 宇, 汤筱玙, 宋佳宸, 余胜泉. 智能时代的中小学人工智能教育:总体定位与核心内容领域,中国远程教育,2021(05):22-37+11.[PDF]

  • 卢 宇, 马安瑶, 陈鹏鹤. 人工智能+教育:关键技术及典型应用场景,中小学数字化教学,2021(10):5-9.[PDF]

  • 卢 宇, 张黎楠, 夏梦雨, 余胜泉. 中小学人工智能课程的设计原则与实践范例,中小学数字化教学,2021(04):5-9.[PDF]

  • 卢 宇, 薛天琪, 陈鹏鹤, 余胜泉. 智能教育机器人系统构建及关键技术,开放教育研究,2020(02):83-91.[PDF]

  • 谭红叶, 午泽鹏, 卢 宇, 段庆龙, 李茹, 张虎. 基于代表性答案选择与注意力机制的短答案自动评分,中文信息学报, 2019(11):134-142.[PDF]

  • 余胜泉,彭 燕,卢 宇.基于人工智能的育人助理系统,开放教育研究,2019(01): 23-36, 2019.[PDF]

  •     Selected Conference Papers:

  • Yu Lu, Deliang Wang, Penghe Chen, Qinggang Meng, “Does Large Dataset Matter? An Evaluation on the Interpreting Method for Knowledge Tracing,” International Conference on Computers in Education. (ICCE'2021), 2021. [PDF]

  • Yu Lu, Yang Pian, Ziding Shen, Penghe Chen, Xiaoqing Li, “SLP: A Multi-Dimensional and Consecutive Dataset from K-12 Education,” International Conference on Computers in Education. (ICCE'2021), 2021. [PDF]

  • Yu Lu, Yang Pian, Penghe Chen, Qinggang Meng, Yunbo Cao, “RadarMath: An Intelligent Tutoring System for Math Education,” demo paper, AAAI Conference on Artificial Intelligence (AAAI'2021), 2021. [PDF]

  • Penghe Chen, Yu Lu, Jiefei Liu, Qi Xu, “An Intelligent Assistant for Problem Behavior Management,” demo paper, AAAI Conference on Artificial Intelligence (AAAI'2021), 2021. [PDF]

  • Jinglei Yu, Jiachen Song, Yu Lu*, Shengquan Yu, “Back to the Origin: An Intelligent System for Learning Chinese Characters,” International Conference on Artificial Intelligence in Education (AIED'2021), 2020. [PDF]

  • Xi Zhao, Jingjing Zhang, Wenshuo Li, Ken Kahn, Yu Lu*, Niall Winters, “Learners' non-cognitive skills and behavioral patterns of programming: A sequential analysis,” International Conference on Advanced Learning Technologies (ICALT'2021), 2020. [PDF]

  • Yu Lu, Deliang Wang, Qinggang Meng and Penghe Chen, “Towards Interpretable Deep Learning Models for Knowledge Tracing,” International Conference on Artificial Intelligence in Education (AIED'2020), 2020. [PDF]

  • Penghe Chen, Yu Lu*, Yan Peng, Jiefei Liu and Penghe Chen, “Identification of Students' Need Deficiency Through A Dialogue System,” International Conference on Artificial Intelligence in Education (AIED'2020), 2020. [PDF]

  • Yang Pian, Yu Lu*, Yuqi Huang and Ig Ibert Bittencourt, “A Gamified Solution to the Cold-Start Problem of Intelligent Tutoring System,” International Conference on Artificial Intelligence in Education (AIED'2020), 2020. [PDF]

  • Yan Peng, Penghe Chen, Yu Lu, Qinggang Meng, Qi Xu and Shengquan Yu, “A Task-Oriented Dialogue System for Moral Education,” International Conference on Artificial Intelligence in Education (AIED'2019), Chicago, U.S., 2019. [PDF]

  • Yu Lu, Chen Chen, Penghe Chen, Xiyang Chen, Zijun Zhuang, “Smart Learning Partner: An Interactive Robot for Education,” International Conference on Artificial Intelligence in Education (AIED'2018), London, UK, 2018. [PDF]

  • Yang Pian, Yu Lu*, Penghe Chen, Qinglong Duan, “CogLearn: A Cognitive Graph-Oriented Online Learning System”, IEEE Conference on Data Engineering (ICDE'2019), Demo Paper, Macau SAR, China, 2019. [PDF]

  • Penghe Chen, Yu Lu*, Vincent W. Zheng, Yang Bian, “Prerequisite-Driven Deep Knowledge Tracing”, IEEE Conference on Data Mining (ICDM'2018), Singapore, 2018. [PDF]

  • Penghe Chen, Yu Lu*, Vincent W. Zheng, et al., “An Automatic Knowledge Graph Construction System for K-12 Education,” ACM Conference on Learning at Scale (L@S'2018), London, UK, 2018. [PDF]

  • Yu Lu, Gim Guan Chua, Huayu Wu, Clement Ong Shi Qi, “An Intelligent System for Taxi Service Monitoring, Analytics and Visualization,” demo paper, International Joint Conference on Artificial Intelligence (IJCAI'2016), New York, U.S., 2016. [PDF]

  • Seong Ping Chuah, Huayu Wu, Yu Lu, Liang Yu, "Bus Routes Design and Optimization via Taxi Data Analytics,” ACM International Conference on Information and Knowledge Management (CIKM'2016), Indianapolis, U.S., 2016. [PDF]

  • Dheeraj Kumar, Huayu Wu, Yu Lu, Shonali Krishnaswamy, Marimuthu Palaniswami, “Understanding Urban Mobility via Taxi Trip Clustering,” IEEE International Conference on Mobile Data Management (MDM'2016), Porto, Portugal, 2016. [PDF]

  • Yu Lu, Shili Xiang and Wei Wu, "Taxi Queue, Passenger Queue or No Queue? - A Queue Detection and Analysis System using Taxi State Transition," International Conference on Extending Database Technology (EDBT'2015), Brussels, Belgium, 2015. [PDF]

  • Tadashi Okoshi, Yu Lu, Chetna Vig, Youngki Lee, Rajesh Krishna Balan and Archan Misra “QueueVadis: Queuing Detection and Analytics using Smartphones,” International Conference on Information Processing in Sensor Networks (IPSN'2015), Seattle, WA, USA, 2015. [PDF]

  • Yu Lu, Wei Wu, Shili Xiang, Huayu Wu, "A Queue Analytics System for Taxi Service Using Mobile Crowd Sensing," ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'2015), demo paper, Osaka, Japan, 2015. [PDF]

  • Dongxu Shao, Wei Wu, Shili Xiang, Yu Lu, "Estimating Taxi Demand-Supply Level using Taxi Trajectory Data Stream," IEEE International Conference on Data Mining (ICDM'2015), workshop paper, Atlantic City, U.S., 2015. [PDF]

  • Yu Lu, Wai-Choong Wong, "Towards Context-Aware Internet Services with Unselfish Clients," IEEE International Conference on Pervasive Computing and Communications (PerCom'2013), workshop paper, San Diego, U.S., 2013. [PDF]

  • Yu Lu, Mehul Motai, Wai-Choong Wong, "The User-Context Module: A New Perspective on Future Internet Design," International Conference on Ambient Systems, Networks and Technologies (ANT'2011), Niagara Fall, Canada, 2011. [PDF]

  • Yu Lu, Mehul Motai, Wai-Choong Wong, "When Ambient Intelligence Meets Internet Protocol Stack: User Layer Design," IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (EUC'2010), Hong Kong, SAR, China, 2010. [PDF]

  • Yu Lu, Mehul Motai, Wai-Choong Wong, "Intelligent Network Design: User Layer Architecture and its Application," IEEE International Conference on Systems, Man and Cybernetics (SMC'2010), Istanbul, Turkey, 2010. [PDF]

  • Yu Lu, Jinkun Liu, Fuchun Sun, "Actuator Nonlinearities Compensation Using RBF Neural Networks in Robot Control System," IMACS Multiconference on Computational Engineering in Systems Applications (CESA'2006), Beijing, China, 2006. [PDF]

  •     Books && Chapters:

  • Shengquan Yu, Yu Lu. An Introduction to Artificial Intelligence in Education. Springer, 2021.

  • 余胜泉,卢宇, 陈晨. 人工智能+教育蓝皮书, 北京师范大学出版社, 2020.

  • Yu Lu, “Enabling User Context Utilization in the Internet Communication Protocols: Motivation, Architecture and Examples,” Beyond the Internet of Things: Everything Interconnected, Springer, 2017.

  • Patents

  • “A Multi-Modal Data-Driven System and Approach for Knowledge Tracing and Prediction”, CN106779079A, China.

  • “A Recommender System and Approach for Student Development”, CN106997571A, China.

  • “An Academic Performance Prediction System and Approach using Collaborative Filtering”, CN107274020A, China.

  • “A Learning Resource Recommender System and Approach for Online Learning Environment”, CN107590232A, China.

  • “A Question-Anwswering Analytics System and Approach using Educational Knowledge Graph”, CN108846104A, China.

  • “An Automatic-Scoring System and Approach for Text-Answer Open-Ended Questions”, CN108763411A, China.

  • Selected Research Grants

  • China National Natural Science Foundation Grant: “Cross-subject Concept Map based Knowledge Tracing Model and its Interpretability”, Principle Investigator (PI).

  • China National Natural Science Foundation Grant: “Multimodal Long-Term Data based Model Design for Learning Obstacle”, Principle Investigator (PI).

  • The Humanities and Social Sciences Foundation of the Ministry of Education of China: “Harnessing Activity Data to Modeling Learning Engagement”, Principle Investigator (PI).

  • The Fundamental Research Funds for the Central Universities: "Task-Driven Intelligent Robot for Education", Principle Investigator (PI).

  • Singapore Joint Research Innovation Grant: “Fine-Grained Spatial-Temporal Analysis to Understand Driver Behaviour and Estimate Taxi Demand”, Principle Investigator (PI).

  • My research is also supported by multiple industry fundings from the leading companies, such as Tencent and China Mobile.


  • Data Structure, Undergraduate Course, Beijing Normal Univrsity.

  • Ariticial Intelligence and its Applications in Education, Undergraduate/Master Course, Beijing Normal University.

  • Frontiers on Eduational Technology, Ph.D. Course (in English), Beijing Normal University.

  • Industry Experiences

  • Software Engineer, Sopra Steria Group, Singapore & France, June 2012 - Aug. 2013.

  • Intern, Embedded System Institute, ESIGELEC, France, Oct. 2005 – Feb. 2006.

  • Selected Academic Awards

  • Best Robotic Video, "Smart Learning Partner: An Intelligent Robot for Education", IJCAI 2019.

  • Best Researcher, Advanced Innovation Center for Future Education, Beijing Normal University, 2018.

  • Outstanding Researcher, Institute for Infocomm Research (I2R), A*STAR, Singapore, 2015.

  • NGS Research Fellowship, National University of Singapore, Singapore, 2012.

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