Lingfei Mo

Release time:2019-09-06viewed:551

resume

   Lingfei Mo, Associate Professor. He received the B.S. degrees in Automation Engineering from Beijing Jiaotong University, Beijing, China, in 2004, and the Ph.D. degree in Control Science and Engineering from Zhejiang University, Hangzhou, China, in 2009. He worked as a Post-Doctoral Fellow in the Department of Mechanical Engineering at University of Connecticut, Storrs, CT, USA, from 2011 to 2012, before joining the school of Instrument Science and Engineering at the Southeast University in Fall 2012 as an associate professor.His research interests are focus on RFID tag and reader design, RFID sensing, wireless sensor network, wearable sensors, human health monitoring and physical activity assessment, machine learning and artificial intelligence, especially on brain-like intelligence and computational neuroscience. He has authored over 40 technical publications in standard journals and conferences. He also has more than 10 China patents pending in the area of RFID and wireless communication. He is a member of the IEEE and an AE of the IEEE Journal of RFID.

professional ranks and titles

associate professor

Tutor Information

Masters Supervisor

Teaching Work

Undergraduate: Technology of Sensors Postgraduate : Virtual Instrument

Part-time Academic Job

(1)Member of IEEE 

(2)Member of IEEE Instrumentation and Measurement 

(3)Member of IEEE Antennas and Propagation 

(4)Member of IEEE Computational Intelligence 

(5)Associate Editor, IEEE Journal of Radio Frequency Identification

Research direction

SCI Journal Papers

[2019] Lingfei Mo*, Lujie Zeng, Running gait pattern recognition based on cross-correlation analysis of single acceleration sensor, Mathematical Biosciences and Engineering,  2019, 16(6): 6242-6256. 

[2019] Chengyang Li, Lingfei Mo*, Dongkai Zhang, Review on UHF RFID Localization Methods, Journal of Radio Frequency Identification, 2019.2924346. 

[2019] Lingfei Mo*, Lujie Zeng, Shaopeng Liu, Robert X Gao, Multi-sensor Activity Monitoring Combination of Models with Class-specific Voting Weights, Information, Article ID 478283, 2019. 

[2019] Y. Qin, L. Mo* , C. Li , et al. Skeleton-based action recognition by part-aware graph convolutional networks[J]. The Visual Computer, 2019(3). 

[2019] Lingfei Mo*, Chenyang Li, “Double Loop Inductive Feed Patch Antenna Design for Anti-metal UHF RFID Tag," International Journal of Antennas and Propagation, vol. 2019, Article ID 2917619, 2019. 

[2018] Lingfei, Mo*, and Chenyang Li. "Passive UHF-RFID Localization Based on the Similarity Measurement of Virtual Reference Tags." IEEE Transactions on Instrumentation and Measurement (2018). 

[2018] Lingfei Mo,* Chenyang Li, Hualin Huang, and Yaxuan Dong,A Study of Walking Speed Measurement for Elderly Health Assessment Using Ultrahigh-frequency Radio-frequency Identification Tags,Sensors and Materials, Vol. 30, No. 5 (2018) 1039–1051 

[2017] Lingfei Mo,* Xu Lu, Zengtao Feng, and Wenqi Hua,Online Human Daily Activity Recognition with Rechargeable Wearable Sensors,Sensors and Materials, Vol. 29, No. 9 (2017) 1353–1365 

[2016] Yan Yu, Lingfei Mo and Jian Wang, Identifying Topic-Specific Experts on Microblog, KSII Transactions on Internet and Information Systems Vol.10, No.6, 2016. 

[2015] Yan Yu and Lingfei Mo, Investigating Correlation Between Strength of Social Relationship and Interest Similarity, LNCS 9197, Springer International Publishing, pp.172-181, 2015. 

[2015] Yan Yu, Lingfei Mo and Jiasheng Zhou, Social Friend Interest Similarity in Microblog and its Implication, International Journal of Control and Automation, Vol.8, No.11(2015), pp. 21-32. (EI) 

[2013] C. Qin, L. Mo, H. Zhou, H. Zhang, “Dual-Dipole UHF RFID Tag Antenna with Quasi-Isotropic Patterns Based on Four-Axis Reflection Symmetry, ” International Journal of Antennas and Propagation, vol. 2013, Article ID 194145, 2013. 

[2012] L. Mo, S. Liu, R. Gao and P. S. Freeson, " Wireless Design of a Multi-Sensor System for Physical Activity Monitoring," IEEE Transactions on Biomedical Engineering,Vol.59,pp.3230-3237,2012. 

[2012] L. Mo, S. Liu, R. Gao and P. S. Freeson, "Multi-Sensor Ensemble Classifier for Activity Recognition," A Journal of Software Engineering and Applications,Vol.5, pp.113-116,2012. 

[2012] L. Mo, C. Qin, “Tunable Compact UHF RFID anti-metal tag based on CPW open stub feed PIFA antenna," International Journal of Antennas and Propagation, vol. 2012, Article ID 167658, 2012. 

[2011] Q. Sun, H. Zhang, and L. Mo, "Dual reader wireless protocols for dense active RFID identification," International Journal of Communication Systems, Vol.24, pp.1431-1444, 2011. 

[2010] L. Mo and C. F. Qin, "Planar UHF RFID Tag Antenna With Open Stub Feed for Metallic Objects," IEEE Transactions on Antennas and Propagation, vol. 58, pp. 3037-3043, 2010. 

[2009] L. Mo, H. J. Zhang, and H. L. Zhou, "Analysis of dipole-like ultra high frequency RFID tags close to metallic surfaces," Journal of Zhejiang University-Science A, vol. 10, pp. 1217-1222, 2009. 

[2008] L. Mo, H. Zhang, and H. Zhou, "Broadband UHF RFID tag antenna with a pair of U slots mountable on metallic objects," Electronics Letters, vol. 44, pp. 1173-1174, 2008.

International Conference Papers

[2017] Yang Qin, Lingfei Mo*, Benyi Xie,Feature Fusion for Human Action Recognition based on Classical Descriptors and 3D convolutional networks,Sensing Technology (ICST), 2017 11th International Conference on. IEEE, 2017. 

[2016] Mo, Lingfei, Chenyang Li, and Xiujuan Xie. "Localization of passive UHF RFID tags on the assembly line." Flexible Automation (ISFA), International Symposium on. IEEE, 2016. 

[2016] Yang Qin, Lingfei Mo*, Jing Ye, Zhening Du,“Multi-channel Features Fitted 3D CNNs and LSTMs for Human Activity Recognition”,  Sensing Technology (ICST), 2016 10th International Conference on. IEEE, 2016. 

[2016] Mo, Lingfei, Zengtao Feng, and Jingyi Qian. "Human daily activity recognition with wearable sensors based on incremental learning." Sensing Technology (ICST), 2016 10th International Conference on. IEEE, 2016. 

[2016] Tao, Hongxing, Lingfei Mo, Fei Shen, Zhening Du, and Ruqiang Yan. "Multi-classifiers ensemble with confidence diversity for fault diagnosis in induction motors." In Sensing Technology (ICST), 2016 10th International Conference on, pp. 1-5. IEEE, 2016 

[2016] Jiang, Hongliang, Lingfei Mo, Xun, Xiaofang,Idle construction land prediction with gradient boosting machine,PIC 2016 - Proceedings of the 2016 IEEE International Conference on Progress in Informatics and Computing, 2016. 

[2016] Xun, Xiaofang, Lingfei Mo, and Yan Yu. "Discovery and prediction of the unused land for construction based on random forest." Agro-Geoinformatics (Agro-Geoinformatics), 2016 Fifth International Conference on. IEEE, 2016.

[2016] Li, Chenyang, Lingfei Mo, and XiuJuan Xie. "Localization of passive UHF RFID tags on assembly line based on phase difference." Instrumentation and Measurement Technology Conference Proceedings (I2MTC), 2016 IEEE International. IEEE, 2016. 

[2016] Mo, Lingfei, et al. "Human physical activity recognition based on computer vision with deep learning model." Instrumentation and Measurement Technology Conference Proceedings (I2MTC), 2016 IEEE International. IEEE, 2016. 

[2015] Feng, Zengtao, Lingfei Mo, and Meng Li. "Analysis of low energy consumption wireless sensor with BLE." SENSORS, 2015 IEEE. IEEE, 2015. 

[2015] Feng, Zengtao ,Mo, Lingfei ,Li, Meng,A Random Forest-based ensemble method for activity recognition,37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015,5074-5077 

[2015] Huang, Hua-Lin ,Mo, Ling-Fei ,Liu, Ying-Jie,Li, Cheng-Yang,Xu, Qi-Meng,Wu, Zhi-Tong,Preliminary exploration of the measurement of walking speed for the apoplectic people based on UHF RFID,37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015,8038-8041。 

[2013] L. Mo, S. Liu, R. Gao, P.S. Freedson, “Energy-efficient and data synchronized body sensor network for physical activity measurement,” Instrumentation and Measurement Technology Conference (I2MTC), 2013 IEEE, pp.1120-1124, 2013 

[2012] L. Tao, L. Mo, S.  Liu, R. Gao, “Optimal battery charge and discharge control scheme under solar power inflow,” Instrumentation and Measurement Technology Conference (I2MTC), 2012 IEEE, 2012, pp.849-854. 

[2011] C. Qin, L. Mo, H. Zhou and H. Zhang, "A single port dipole for UHF RFID tag antennas with eliminated read-orientation sensitivity," Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on, pp.998-1001, 2011. 

[2011] L. Mo, S. Liu, R. X. Gao, D. John, J. Staudenmayer, and P. Freedson, "ZigBee-Based Wireless Multi-Sensor System for Physical Activity Assessment," in Proc. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, USA, 2011, pp. 846-849. 

[2011] J. Zhou, H. Zhang, and L. Mo, "Two-dimension localization of passive RFID tags using AOA estimation," Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE, 2011, pp. 1-5. 

[2010] Q. Sun, H. Zhang and L. Mo, "Master-slave dual readers enhanced aloha anti-collision mechanism for dense active RFID," Instrumentation and Measurement Technology Conference (I2MTC), 2010 IEEE, 2010, pp. 1414-1417. 

[2010] L. Mo, C. Qin, and X. Tang, "Velocity analysis for UHF RFID vehicle license plate," Optoelectronics and Image Processing (ICOIP), 2010 International Conference on, 2010, pp. 722-725. 

[2007] L. Mo and H. Zhang, "RFID antenna near the surface of metal," in Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2007 International Symposium on, 2007, pp. 803-806 招生计划

Recruitment Plan

3 Master/year. Welcome the students majoring in Instrument Science and technology, Measurement, Automation, Electronics and Computer to apply to join the laboratory. Welcome excellent visiting and exchange students from the world to join in the Lab.

Contact information

Office Telephone:025-83751512
mailbox:lfmo@seu.edu.cn

Postal address:School of Instrument Science and Engineering, Southeast University, Nanjing, China

Other

Based on the research of the Internet of Things, Robots and Artificial Intelligence, the laboratory provides intelligent industry/intelligent transportation/intelligent city/intelligent agriculture/intelligent animal husbandry solutions. Partners from various areas are welcome to exchange and cooperate with us.