Lei Zhang (张雷) is an associate professor in the School of Electric and Autumation Engineerning, Nanjing Normal University (NNU) . His research interests mainly lie in machine learning, data mining, human motion recognition, and service computing.He received his B.E. degree from Zhengzhou University in 2001, and M.E. degree from Chinese Academy of Sciences (CAS) in 2004, and doctoral degree from Southeast University respectively. He has published more than 60 technical papers at prominent journals and conferences such as IEEE T-NNLS, IEEE T-TKDE, IEEE T-MC, IEEE T-IE, IEEE T-II, IEEE T-NSM, IEEE T-SC, IEEE T-IM, IEEE T-HMS, IEEE T-ETCI, IEEE JBHI, ACM T-ECS, KBS, PRE, etc. He serves as the reviewer for more than 50 international journals such as ACM T-KDD, ACM T-ECS, IEEE T-NNLS, IEEE T-MC, IEEE T-AI, IEEE T-IE, IEEE T-IP, IEEE T-IM, IEEE T-CDS, IEEE IOT, Pervasive and Mobile Computing, etc., and also the PC member or reviewer of several top-tier conferences such as ICML, AAAI, UbiComp, etc. He received the “Outstanding Reviewing Contribution” from the journal “Signal Processing” and “Chinese Journal of Physics”, respectively.

🔥 News

2023.05: 🎉 One paper is accepted by IEEE TKDE
2023.05: 🎉 One paper is accepted by IEEE JBHI
2023.04: 🎉 One paper is accepted by IEEE TMC
2023.04: One paper is accepted by IEEE TIM
2023.04: One paper is accepted by IEEE TNNLS
2022.10: One paper is accepted by ACM TECS
2022.07: One paper is accepted by IEEE JBHI
2022.07: One paper is accepted by IEEE TIM
2022.07: One paper is accepted by Elsevier ESWA
2022.05: One paper is accepted by IEEE TII
2022.05: One paper is accepted by IEEE TMC
2022.04: One paper is accepted by Springer Supercomputing
2022.03: One paper is accepted by IEEE TIE
2022.03: One paper is accepted by IEEE TIM
2022.02: One paper is accepted by IEEE Sensors
2022.01: One paper is accepted by IEEE TETCI

📝 Publications

🎙 2023

IEEE TKDE Channel Attention for Sensor-based Activity Recognition: Embedding Features into All Frequencies in DCT Domain, Xu S, Zhang L*, Tang Y, Han C, Wu H, Song A
IEEE JBHI ProtoHAR: Prototype Guided Personalized Federated Learning for Human Activity Recognition, Cheng D, Zhang L*, Bu C, Wang X, Wu H, Song A
IEEE TMC A Collaborative Compression Scheme for Fast Activity Recognition on Mobile Devices Via Global Compression Ratio Decision, Liang J, Zhang L*, Han C, Bu C, Wu H, Song A
IEEE TIM An Efficient Diverse-branch Convolution Scheme for Sensor-Based Human Activity Recognition, Han C, Zhang L*, Xu S, Wang X, Wu H, Song A
IEEE TNNLS Diversifying Collaborative Filtering via Graph Spreading Network and Selective Sampling, Y Fang, H Wu, Y Zhao, Zhang L*, S Qin, X Wang
E KBS Modeling and predicting user preferences with multiple item attributes for sequential recommendations, L Xu, J Zeng, W Peng, H Wu, K Yue, H Ding, Zhang L*, X Wang
IEEE TNSM Towards Effective Personalized Service QoS Prediction from the Perspective of Multi-Task Learning, H Lian, J Li, H Wu, Y Zhao, Zhang L*, X Wang

🎙 2022

ACM TECS Deep ensemble learning for human activity recognition using wearable sensors via filter activation, W Huang, Zhang L*, S Wang, H Wu, A Song
IEEE JBHI Dual-Branch Interactive Networks on Multichannel Time Series for Human Activity Recognition, Y Tang, Zhang L*, H Wu, J He, A Song
IEEE TIM Understanding and improving channel attention for human activity recognition by temporal-aware and modality-aware embedding, C Han, Zhang L*, Y Tang, S Xu, F Min, H Wu, A Song
E ESWA Human activity recognition using wearable sensors by heterogeneous convolutional neural networks, C Han, Zhang L*, Y Tang, W Huang, F Min, J He
IEEE TII Keyword-Driven Service Recommendation via Deep Reinforced Steiner Tree Search, H Chen, H Wu, J Li, X Wang, Zhang L*
IEEE TMC Channel-Equalization-HAR: a light-weight convolutional neural network for wearable sensor based human activity recognition, W Huang, Zhang L*, H Wu, F Min, A Song
S Supercomputing A lightweight neural network framework using linear grouped convolution for human activity recognition on mobile devices, T Liu, S Wang, Y Liu, W Quan, Zhang L*
IEEE TIE Multiscale deep feature learning for human activity recognition using wearable sensors, Y Tang, Zhang L*, F Min, J He
IEEE TIM Deformable convolutional networks for multimodal human activity recognition using wearable sensors, S Xu, Zhang L*, W Huang, H Wu, A Song
IEEE Sensors Real-time human activity recognition using conditionally parametrized convolutions on mobile and wearable devices, X Cheng, Zhang L*, Y Tang, Y Liu, H Wu, J He
IEEE TETCI Triple cross-domain attention on human activity recognition using wearable sensors, Y Tang, Zhang L*, Q Teng, F Min, A Song

🎙 2021

IEEE TIM Deep Convolutional Networks With Tunable Speed–Accuracy Tradeoff for Human Activity Recognition Using Wearables, X Wang, Zhang L*, W Huang, S Wang, H Wu, J He, A Song
ASC DanHAR: Dual attention network for multimodal human activity recognition using wearable sensors, W Gao, Zhang L*, Q Teng, J He, H Wu
IEEE TIM Deep neural networks for sensor-based human activity recognition using selective kernel convolution, W Gao, Zhang L*, W Huang, F Min, J He, A Song
IEEE TSC Mashup-oriented web api recommendation via multi-model fusion and multi-task learning, H Wu, Y Duan, K Yue, Zhang L*
IEEE JBHI The convolutional neural networks training with channel-selectivity for human activity recognition based on sensors, W Huang, Zhang L*, Q Teng, C Song, J He
IEEE TIM Shallow convolutional neural networks for human activity recognition using wearable sensors, W Huang, Zhang L*, W Gao, F Min, J He
IEEE THMS Sequential weakly labeled multiactivity localization and recognition on wearable sensors using recurrent attention networks, K Wang, J He, Zhang L*
IEEE Sensors Block-wise training residual networks on multi-channel time series for human activity recognition, Q Teng, Zhang L*, Y Tang, S Song, X Wang, J He

🎙 2020

IEEE Sensors Layer-wise training convolutional neural networks with smaller filters for human activity recognition using wearable sensors, Y Tang, Q Teng, Zhang L*, F Min, J He
IEEE Sensors The layer-wise training convolutional neural networks using local loss for sensor-based human activity recognition, Q Teng, K Wang, Zhang L*, J He

🎙 Before 2020

IEEE Sensors Attention-based convolutional neural network for weakly labeled human activities’ recognition with wearable sensors, K Wang, J He, Zhang L*
IEEE GRSL Using diffusion geometric coordinates for hyperspectral imagery representation, J He, Zhang L, Q Wang, Z Li
IET SP Adaptive stochastic gradient descent on the Grassmannian for robust low‐rank subspace recovery, J He, Y Zhang, Y Zhou, Zhang L
PRE Effect of the correlation between internal noise and external noise on logical stochastic resonance in bistable systems, Zhang L*, W Zheng, F Xie, A Song
PHYSA Realizing reliable logical stochastic resonance under colored noise by adding periodic force , Zhang L*, A Song
Chaos Adaptive logical stochastic resonance in time-delayed synthetic genetic networks, Zhang L*, W Zheng, A Song
PHYLETA Realizing reliable logic and memory function with noise-assisted Schmitt trigger circuits, Zhang L*, W Zheng, F Min, A Song
PRE Effect of the correlation between internal noise and external noise on logical stochastic resonance in bistable systems, Zhang L*, W Zheng, F Xie, A Song

👪 Group Members

Long-term Enrollment

I mainly study how to design advanced machine learning algorithms using mathematical tools, which can be further applied to computer vision, data mining, and other related fields. I prefer the students who have solid mathematical foundations, strong programming skills, and good English abilities. The experiences in research (e.g. academic competition, publications, extracurricular academic activities, etc.) will be a benefit. I will provide you a full range of effective guidance in algorithm design, coding, experimental verification, paper writing, presentation, etc.
E-mail：leizhang AT njnu DOT edu DOT cn

Research Partners

Students

2023

On the way…

2022

2021

Alumini

2020

Chaolei Han: 国家奖学金、校级优秀毕业生、校级优秀研究生，Now Ph.D. Candidate in Southeast University，
Shige Xu: 阿里、字节跳动、腾讯优图，国家奖学金、校级优秀毕业生、校级优秀研究生，Now at SHEIN
Xing Wang: 中国广核集团、Phoenix Contact
Peitian Chen: Now at Shanghai Municipal Tax Service

2019

Yin Tang: 国家奖学金、校级优秀毕业生、校级优秀研究生，Now Ph.D. Candidate in Central South University
Wenbo Huang: 国家奖学金、校级优秀毕业生、校级优秀研究生，Now Ph.D. Candidate in Southeast University
Tianyi Liu: 小米，Now Ph.D. Candidate in Southeast University
Wenbin Gao: 中兴、南京银行，Now at Xiaomi
Xin Cheng: Now at State Grid of China(Shandong)
Weiming Quan: Now at State Grid of China(Anhui)

2018

Qi Teng: 国家奖学金、校级优秀毕业生、校级优秀研究生，Now Ph.D. Candidate in Nanjing University
Kun Wang: 国家奖学金、校级优秀毕业生、校级优秀研究生，Now Ph.D. Candidate in Southeast University
Zhenyu Wang: 网易，Now Ph.D. Candidate in Nanjing University
Jinwei Mao: Now at NARI Group

2017

Zhihao Zhang: Now at NARI Group

Undergraduate

Zhixiang Wang: Ph.D. in University of Tokyo
Shuoyuan Wang: Now Ph.D. Candidate in University of Macau

🎖 Academic Services

Conference Reviewer/PC Member

Association for the Advancement of Artificial Intelligence (AAAI):2021,2022,2023
International Conference on Machine Learning (ICML):2021
UbiComp/ISWC:2022

Journal Reviewer

ACM transactions on Embedded Computing Systems (TECS)
ACM transactions on Knowledge Discuvery from Data (TKDD)
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Artificial Intelligence
IEEE Transactions on Mobile Computing
IEEE Transactions on Industrial Electronics
IEEE Transactions on Signal Processing
IEEE Journal of Selected Topics on Signal Processing
IEEE Transactions on Instrumentation and Measurement
IEEE Transactions on Cognitive and Developmental System
IEEE Transactions on Circuits and Systems II: Express Briefs
IEEE Transactions on Circuits and Systems I: Regular Papers
IEEE Internet of Things Journal
IEEE Sensors Journal
Expert System an Applications
The Visual Computer
Journal of Supercomputing
Data in Brief
Scientific Data
International Journal of Bifurcation and Chaos
Chaos: An Interdisciplinary Journal of Nonlinear Sciences
Nonlinear Dynamics
Physics Letters A
Measurement Science and Technology
Electronic Letters
Chinese Journal of Physics

📖 Educations

1997.09 - 2001.06, B.S., Zhenzhou University (ZZU), Zhenzhou, Henan.
2001.09 - 2004.06, M.S., Chinese Academy of Sciences (CAS), Shenyang Institute of Automation, Shenyang, Liaoning.
2007.03 - 2011.03, Ph.D, Southeast University (SEU), Nanjing, Jiangsu.

💻 Work Experiences

2008.09 - 2009.01, University of California, Los Angeles (UCLA),Institute of Pure and Applied Mathematics (IPAM), Los Angeles, USA.
2004.09 - 2014.09, Associate Professor, Computer Department School of Information Engineering , China Jiliang University (CJLU), Hangzhou, Zhejiang, China.
2016.10 - 2017.10, Visiting Scholar, Department of Mechanical Engineering, University of Northumbria at Newcastle (NU), Newcastle upon Tyne, UK.
2014.10-Now, Associate Professor, Institute of Infirmation and Control Technologies, School of Electrical Engineering and Automation, Nanjing Normal University (NJNU), Nanjing, Jiangsu, China.

💬 Teaching

Data Structures and Algorithms (C language)
Digital Image Processing
Pattern Recognition and Machine Learning, Deep Learning