Artificial Intelligence

AI Theory

[1] The Geometric Structure of Generalized Softmax Learning
Xiangxiang Xu and Shao-Lun Huang and Lizhong Zheng and Lin Zhang. In IEEE Information Theory Workshop, ITW 2018, Guangzhou, China, November 25-29, 2018. 2018. Link
[2] An Information Theoretic Interpretation to Deep Neural Networks
Shao-Lun Huang and Xiangxiang Xu and Lizhong Zheng and Gregory W. Wornell. In IEEE International Symposium on Information Theory, ISIT 2019, Paris, France, July 7-12, 2019. 2019. Link
[3] On the Robustness of Noisy ACE Algorithm and Multi-Layer Residual Learning
Shao-Lun Huang and Xiangxiang Xu. In IEEE International Symposium on Information Theory, ISIT 2019, Paris, France, July 7-12, 2019. 2019. Link
[4] An Information Theoretic Interpretation to Deep Neural Networks
Shao-Lun Huang and Xiangxiang Xu and Lizhong Zheng and Gregory W. Wornell. In CoRR. 2019. Link
[5] On the Sample Complexity of HGR Maximal Correlation Functions
Shao-Lun Huang and Xiangxiang Xu. In CoRR. 2019. Link
[6] An Information-Theoretic Metric of Transferability for Task Transfer Learning
Bao, Yajie and Li, Yang and Huang, Shao-Lun and Zhang, Lin and Zamir, Amir R and Guibas, Leonidas J. In 26th IEEE International Conference on Image Processing (ICIP). 2019. Link
[7] Info-Detection: An Information-Theoretic Approach to Detect Outlier
Feng Zhao and Fei Ma and Yang Li and Shaolun Huang and Lin Zhang. In International Conference on Neural Information Processing. 2019. Link
[8] An efficient approach to informative feature extraction from multimodal data
Wang, Lichen and Wu, Jiaxiang and Huang, Shao-Lun and Zheng, Lizhong and Xu, Xiangxiang and Zhang, Lin and Huang, Junzhou. In Proceedings of the AAAI Conference on Artificial Intelligence. 2019. Link
[9] Maximal Correlation Regression
Xu, Xiangxiang and Huang, Shao-Lun. In IEEE Access. 2020.
[10] An information-theoretic approach to unsupervised feature selection for high-dimensional data
Huang, Shao-Lun and Xu, Xiangxiang and Zheng, Lizhong. In IEEE Journal on Selected Areas in Information Theory. 2020.
[11] Reproducing Scientific Experiment with Cloud DevOps
F. Zhao and X. Niu and S. -L. Huang and L. Zhang. In 2020 IEEE World Congress on Services (SERVICES). 2020. Link
[12] Exact Recovery of Stochastic Block Model by Ising Model
Feng Zhao and Min Ye and Shao-Lun Huang. In Entropy. 2021.

AI Analytics

[1] An Information-Theoretic Metric of Transferability for Task Transfer Learning
Bao, Yajie and Li, Yang and Huang, Shao-Lun and Zhang, Lin and Zamir, Amir R and Guibas, Leonidas J. In 26th IEEE International Conference on Image Processing (ICIP). 2019. Link
[2] Unsupervised anomaly detection via generative adversarial networks
Wang, Hanling and Li, Mingyang and Ma, Fei and Huang, Shao-Lun and Zhang, Lin. In 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 2019.
[3] An efficient approach to informative feature extraction from multimodal data
Wang, Lichen and Wu, Jiaxiang and Huang, Shao-Lun and Zheng, Lizhong and Xu, Xiangxiang and Zhang, Lin and Huang, Junzhou. In Proceedings of the AAAI Conference on Artificial Intelligence. 2019. Link
[4] A maximal correlation embedding method for multilabel human context recognition
Li, Lu and Li, Yang and Xu, Xiangxiang and Zhang, Lin. In Proceedings of the 18th International Conference on Information Processing in Sensor Networks. 2019.
[5] Less Is Better: Unweighted Data Subsampling via Influence Function
Wang, Zifeng and Zhu, Hong and Dong, Zhenhua and He, Xiuqiang and Huang, Shao-Lun. In 34th AAAI Conference on Artificial Intelligence (AAAI). 2020. Link
[6] Information Theoretic Counterfactual Learning from Missing-Not-At-Random Feedback
Wang, Zifeng and Chen, Xi and Wen, Rui and Huang, Shao-Lun and Kuruoglu, Ercan E. and Zheng, Yefeng. In Thirty-fourth Conference on Neural Information Processing Systems. 2020. Link
### AI Analytics [1] A maximal correlation embedding method for multilabel human context recognition
Li, Lu and Li, Yang and Xu, Xiangxiang and Zhang, Lin. In Proceedings of the 18th International Conference on Information Processing in Sensor Networks. 2019.
[2] An efficient approach to informative feature extraction from multimodal data
Wang, Lichen and Wu, Jiaxiang and Huang, Shao-Lun and Zheng, Lizhong and Xu, Xiangxiang and Zhang, Lin and Huang, Junzhou. In Proceedings of the AAAI Conference on Artificial Intelligence. 2019. Link
[3] Unsupervised anomaly detection via generative adversarial networks
Wang, Hanling and Li, Mingyang and Ma, Fei and Huang, Shao-Lun and Zhang, Lin. In 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 2019.
[4] An Information-Theoretic Metric of Transferability for Task Transfer Learning
Bao, Yajie and Li, Yang and Huang, Shao-Lun and Zhang, Lin and Zamir, Amir R and Guibas, Leonidas J. In 26th IEEE International Conference on Image Processing (ICIP). 2019. Link
[5] Less Is Better: Unweighted Data Subsampling via Influence Function
Wang, Zifeng and Zhu, Hong and Dong, Zhenhua and He, Xiuqiang and Huang, Shao-Lun. In 34th AAAI Conference on Artificial Intelligence (AAAI). 2020. Link
[6] Data-driven Risk Assessment on Urban Pipeline Network Based on a Cluster Model
Wang, Zifeng and Li, Suzhen. In Reliability Engineering and System Safety. 2020. Link

AI Application

[1] Knowledge-based trajectory completion from sparse GPS samples
Li, Yang and Li, Yangyan and Gunopulos, Dimitrios and Guibas, Leonidas. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2016.
[2] Hap: Fine-grained dynamic air pollution map reconstruction by hybrid adaptive particle filter
Chen, Xinlei and Xu, Xiangxiang and Liu, Xinyu and Noh, Hae Young and Zhang, Lin and Zhang, Pei. In Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM. 2016.
[3] Urban travel time prediction using a small number of gps floating cars
Li, Yang and Gunopulos, Dimitrios and Lu, Cewu and Guibas, Leonidas. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2017.
[4] EV charging behaviour analysis and modelling based on mobile crowdsensing data
Yang, Tianyu and Xu, Xiangxiang and Guo, Qinglai and Zhang, Lin and Sun, Hongbin. In IET Generation, Transmission & Distribution. 2017.
[5] Speech Emotion Recognition via Attention-based DNN from Multi-Task Learning
Ma, Fei and Gu, Weixi and Zhang, Wei and Ni, Shiguang and Huang, Shao-Lun and Zhang, Lin. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 2018. Link
[6] Generative model based fine-grained air pollution inference for mobile sensing systems
Ma, Rui and Xu, Xiangxiang and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 2018.
[7] Guiding the Data Learning Process with Physical Model in Air Pollution Inference
Ma, Rui and Xu, Xiangxiang and Wang, Yue and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In 2018 IEEE International Conference on Big Data (Big Data). 2018.
[8] PiMi: two-month indoor/outdoor PM 2.5 concentrations along with behavior labels through large-scale participatory sensing
Ma, Rui and Zhang, Lin. In Proceedings of the First Workshop on Data Acquisition To Analysis. 2018.
[9] Pga: Physics guided and adaptive approach for mobile fine-grained air pollution estimation
Chen, Xinlei and Xu, Xiangxiang and Liu, Xinyu and Pan, Shijia and He, Jiayou and Noh, Hae Young and Zhang, Lin and Zhang, Pei. In Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. 2018.
[10] Personalized Travel Time Prediction Using a Small Number of Probe Vehicles
Li, Yang and Gunopulos, Dimitrios and Lu, Cewu and Guibas, Leonidas J. In ACM Transactions on Spatial Algorithms and Systems (TSAS). 2019.
[11] An Information-Theoretic Metric for Transferability in Task Transfer Learning
Bao, Yajie and Li, Yang and Huang, Shao-Lun and Zhang, Lin and Zamir, Amir and Guibas, Leonidas. In Proceedings of the The 26th IEEE International Conference on Image Processing (ICIP). 2019.
[12] A Hybrid Technique for Travel Time Estimation In Sparse Data Environments
Zygouras, Nikolaos and Panagiotou, Nikolaos and Gunopulos, Dimitrios and Li, Yang and Guibas, Leonidas. In Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2019.
[13] An End-to-End Learning Approach for Multimodal Emotion Recognition: Extracting Common and Private Information
Ma, Fei and Zhang, Wei and Li, Yang and Huang, Shao-Lun and Zhang, Lin. In 2019 IEEE International Conference on Multimedia and Expo (ICME). 2019. Link
[14] Info-Detection: An Information-Theoretic Approach to Detect Outlier
Feng Zhao and Fei Ma and Yang Li and Shaolun Huang and Lin Zhang. In International Conference on Neural Information Processing. 2019.
[15] MSSTN: Multi-Scale Spatial Temporal Network for Air Pollution Prediction
Wu, Zhiyuan and Wang, Yue and Zhang, Lin. In Proceedings of IEEE International Conference on Big Data 2019. 2019. Link

Internet of Things

IoT Environment

[1] Delay Effect in Mobile Sensing System for Urban Air Pollution Monitoring
Liu, Xinyu and Chen, Xinlei and Xu, Xiangxiang and Mai, Enhan and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. 2017.
[2] Individualized Calibration of Industrial-Grade Gas Sensors in Air Quality Sensing System
Liu, Xinyu and Xu, Xiangxiang and Chen, Xinlei and Mai, Enhan and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems. 2017.
[3] One-month beijing taxi GPS trajectory dataset with taxi IDs and vehicle status
Lian, Jing and Zhang, Lin. In Proceedings of the First Workshop on Data Acquisition To Analysis. 2018.
[4] SRC: extracting commute patterns for customized bus service area design
Lian, Jing. In SIGSPATIAL Special. 2018.
[5] Joint Mobility Pattern Mining with Urban Region Partitions
Lian, Jing and Li, Yang and Gu, Weixi and Huang, Shao-Lun and Zhang, Lin. In Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services. 2018.
[6] Mining Regional Mobility Patterns for Urban Dynamic Analytics
Lian, Jing and Li, Yang and Gu, Weixi and Huang, Shao-Lun and Zhang, Lin. In Mobile Networks and Applications. 2019.
[7] Mining Mobility Patterns with Trip-Based Traffic Analysis Zones: A Deep Feature Embedding Approach
Lian, Jing and Li, Yang and Huang, Shao-Lun and Zhang, Lin. In 2019 22nd International Conference on Intelligent Transportation Systems (ITSC). 2019.

IoT Smart Building

[1] E-loc: indoor localization through building electric wiring
Zhou, Tian and Zhang, Yue and Chen, Xinlei and Zhang, Pei and Zhang, Lin. In Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks. 2017.
[2] Occupant Activity Level Estimation Using Floor Vibration
Zhang, Yue and Pan, Shijia and Fagert, Jonathon and Mirshekari, Mostafa and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. 2018.
[3] Vibration-Based Occupant Activity Level Monitoring System
Zhang, Yue and Pan, Shijia and Fagert, Jonathon and Mirshekari, Mostafa and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 2018.
[4] Real-Time Emotion Detection via E-See
Gu, Weixi and Zhang, Yue and Ma, Fei and Mosalam, Khalid and Zhang, Lin and Ni, Shiguang. In Proceedings of the 16th ACM Conference on Embedded Networked Sensor Systems. 2018.
[5] P-Loc: a device-free indoor localization system utilizing building power-line network
Zhou, Tian and Zhang, Yue and Chen, Xinlei and Mosalam, Khaild M and Noh, Hae Young and Zhang, Pei and Zhang, Lin. In Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers. 2019.

• Yiming Liu, Victor Li, Ka-cheong Leung, Lin Zhang, “Performance Improvement of Topology-Transparent Broadcast Scheduling in Mobile Ad Hoc Networks, IEEE Transactions on Vehicular Technology (IEEE TVT) (Accepted)
• Xinyu Mao, Shiyu Liu, Lin Zhang, "Energy-Delay Region of Low Duty Cycle Wireless Sensor Networks for Critical Data Collection," in Proc. Information Theory and Application Workshop, UCSD, Feb. 2014
• Yiming Liu, Victor Li, Ka-cheong Leung, Lin Zhang, “Distributed Multi-Channel Topology-Transparent Broadcast Scheduling in Ad Hoc Networks,”Proceedings of the IEEE Wireless Communications and Networking Conference (IEEE WCNC 2014), Istanbul, Turkey, 6-9 April 2014.
• Yiming Liu, Victor Li, Ka-cheong Leung, Lin Zhang, “Is Topology-Transparent Scheduling Really Inefficient in Static Multihop Networks?,”IEEE Wireless Communications Letters, Vol. 2, No. 6, Dec. 2013.
• Yiming Liu, Victor Li, Ka-cheong Leung, Lin Zhang, “Topology-Transparent Broadcast Scheduling with Erasure Coding in Wireless Networks,”IEEE Communications Letters, Vol. 17, No. 8, pp. 1660-1663, August 2013.
• Yiming Liu, Victor Li, Ka-cheong Leung, Lin Zhang, “Topology-Transparent Distributed Multicast and Broadcast Scheduling in Mobile Ad Hoc Networks,” Proc. of IEEE VTC 2012 Spring, yokuhama, Japan.
• Yiming Liu, Lin Zhang, Victor Li, Ka-cheong Leung, Wenzhu Zhang, “Topology-Transparent Scheduling in Mobile Ad Hoc Networks Supporting Heterogeneous Quality of Service Guarantees,” Proc. of CISS 2012, Princeton, New Jersey.
• Shuai Fan, Lin Zhang, Wei Feng, Wenzhu Zhang, Yong Ren, “Optimization-based Design of Wireless Link Scheduling with Physical Interference Model,” in IEEE Transaction on Vehicular Technology, Vol. 61, Issue 8, pp. 3705 - 3717, Oct. 2012.
• Xingyang Chen, Lin Zhang, Yuhan Dong, Xuedan Zhang, Yong Ren, “Achieving Fairness without Loss of Performance in Selection Cooperation of Wireless Networks,” IEICE Trans. on Communications, E94.B no. 8, pp. 2406-2410
• Shuai Fan, Lin Zhang, Yong Ren, Bhaskar Krishnamachari, “Approximation algorithms for link scheduling with physical interference model in wireless multi-hop networks,” Proc. of 2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp.522-529, Sept. 2010
• Haoxiang Zhang, Lin Zhang, Xiuming Shan, Victor O.K. Li, “Locating Highly Connected Nodes in P2P Networks with Heterogeneous Structures,” Tsinghua Science and Technology, Vol. 14, No. 4, pp. 465-469, August, 2009.
• Xuedan Zhang, Jun Hong, Lin Zhang, Xiuming Shan and Victor O. K. Li. “CPTDMA: coloring- and probability-based TDMA scheduling for wireless ad hoc networks.” IEICE Transaction on Communications, 2008, Vol. E91-B, No. 1.
• Xuedan Zhang, Jun Hong, Lin Zhang, Xiuming Shan, Victor O.K. Li, “CC-TDMA: Coloring- and Coding-based Multi-channel TDMA Scheduling for Wireless Ad Hoc Networks,” Proc. of IEEE WCNC 2007, March, 2007, Hong Kong, pp.133-137.
• 张学聃，洪珺，张林，李安国，山秀明，“并行图染色的无线网状网络媒体接入控制”《北京邮电大学学报》， 2007 年第6 期。
• Meng Li, Lin Zhang, Yongkang Xiao, Xiuming Shan, “Power Controlled MAC Protocol with Dynamic Neighbor Prediction for Ad hoc Networks,” Journal of China University of Posts and Telecommunications, vol.11, no.1, 2004, pp.29-37.
• Yongkang Xiao, Lin Zhang, Yong Ren, Xiuming Shan, “Neighbor-Medium-Aware MAC Protocol with Fairness for Wireless Ad Hoc Networks,” IEICE Transaction on Communication, vol.87, no.9, Sep. 2004, pp.2738-2746.
• Bin Li, Wei Feng, Lin Zhang, Costas Spanos, "DEPEND: DEnsity adaptive Power Efficient Neighbor Discovery for wearable body sensors", IEEE CASE 2013, Madison, WI, USA, August 2013.
• Qiao Fu, Bhaskar Krishnamachari, and Lin Zhang. DAWN: a density adaptive routing for deadline-based data collection in vehicular delay tolerant networks [J]. Tsinghua Science and Technology, 2013, 18(3).
• Qiao Fu,Behnam Banitalebi, Lin Zhang, Michael Beigl, "Energy-Efficient Collaborative Data Collection in Mobile Wireless Sensor Networks," IEEE CISS 2013, Baltimore, MD, USA, April 2013.
• Qiao Fu, Wei Feng, Yixin Zheng, Lin Zhang, “DAWN: A Density Adaptive Routing Algorithm for Vehicular Delay Tolerant Sensor Networks,” Proc. of 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton), Sept. 2011
• Yiqun Wu, Lin Zhang, Yihong Wu, Zhisheng Niu, “Motion-Indicated Interest Dissemination With Directional Antennas for Wireless Sensor Networks With Mobile Sinks,” IEEE Transaction on Vehicular Technology, Vol.58, No.2, pp.977-989, Feb. 2009.
• Tianshi Gao, Lin Zhang, Yi Gai, Xiuming Shan, “Load-Balanced Cluster-Based Cooperative MIMO Transmission for Wireless Sensor Networks,” Proc. of IEEE 4th International Symposium on Wireless Communication Systems 2007 (ISWCS07), Oct. 2007,Trondheim, Norway, pp.602-606.
• Yihong Wu, Lin Zhang, Yiqun Wu, Zhisheng Niu, “Interest Dissemination with Directional Antennas for Wireless Sensor Networks with Mobile Sinks,” Proc. of ACM SenSys 2006, Nov. 2006, Boulder, CO, USA, pp.99-111.
• Meng Li, Lin Zhang, Victor Li, Xiuming Shan, "An Energy-Aware Multipath Routing Protocol for Mobile Ad Hoc Networks," Proc of Sigcomm Asia Workshop 2005, April 2005, Beijing, China, pp.166 - 174.
• Lin Zhang, Dongxu Shen, Victor Li, Xiuming Shan, "Receiver Initiated Soft-state Probabilistic Multicasting Protocol in Wireless Ad Hoc Network", Proc of IEEE ICC 2005, May 2005, Seoul, Korea, pp. 3365-3369.
• Lin Zhang, Dongxu Shen, Victor Li, Xiuming Shan, “An Ant-based Multicasting Protocol in Mobile Ad Hoc Networks”, International Journal on Collective Intelligence and its Application, vol.5, no.2, 2005, pp. 185-199.
• Lin Zhang, Yong Ren, Xiuming Shan, “Pheromone based ant routing system for IP networks,” Tsinghua Science and Technology, vol.9, no.2, April 2004, pp.213-218.
• 张林，任勇，山秀明，“负载均衡的人工生命路由”，《通信学报》， vol.25，no.4a，2004年4月， pp.290-297.
• 张林，任勇，山秀明，“多主体协同人工生命路由” ，《全国首届人工生命学术研讨会会议录》，2003年11月，北京邮电大学
• P. Wang, L. Zhang, Victor O.K. Li, "A Stratified Acoustic Model Accounting for Phase Shifts for Underwater Acoustic Networks." Sensors 13, no. 5: 6183-6203.
• P. Wang, L. Zhang, Victor O.K. Li, "Ray-model-based Routing for Underwater Acoustic Sensor Networks Accounting For Anisotropic Sound Propagation." IEICE Transaction on Communication, 2013, Vol.E96-B, No.08, to appear.
• P. Wang, L. Zhang, Victor O.K. Li, “Asynchronous Cooperative Transmission in Three-Dimensional Underwater Acoustic Networks”, IET Communications, to appear.
• P. Wang, W. Feng, L. Zhang, and Victor. O.K. Li, “Asynchronous Cooperative Transmission in Underwater Acoustic Networks”, International Symposium on Underwater Technology 2011 and International Workshop on Scientific Use of Submarine Cables and Related Technologies 2011 (UT’11 and SSC’11), Tokyo, Japan, 2011.
• Ping Wang, Lin Zhang, Bhaskar Krishnamachari, Victor O.K. Li, “Token-based Data Collection Protocols for Multi-Hop Underwater Acoustic Sensor Networks,” Proc. of the 4th ACM International Workshop on Underwater Networks (WUWNet), in conjunction with ACM SenSys 2009, November 3, 2009, Berkeley, California, USA.
• Haoxiang Zhang, Lin Zhang, Xiuming Shan, and Victor. O. K. Li, “Performance Evaluation of Adaptive Probabilistic Search in P2P Networks”, IEICE Transaction on Communications, 2008, Vol. E91-B, No. 4. pp.1172-1175, 2008.
• Haoxiang Zhang, Lin Zhang, Xiuming Shan, Victor O.K. Li, “Probabilistic Search in P2P Networks with High Node Degree Variation,” Proc. of IEEE ICC 2008, June, 2007, Glasgow, Scotland, pp. 1710 - 1715.
• Haoxiang Zhang, Lin Zhang, Xiuming Shan, Victor O.K. Li, “An Adaptive Resource-Based Probabilistic Search Algorithm for P2P Networks,” IEICE Trans. on Communications, vol. E90-B, no.7, July, 2007, pp.1631-1639.
• 秦宁宁，张林，山秀明，徐保国，“无线传感器网络启发式移动轨迹策略的研究”，《电子与信息学报》，Vol 30, No.3, pp.707-711., 2008
• 秦宁宁， 盖祎，张林，蒋敏峰，徐保国，“Voronoi图在无线传感器网络栅栏覆盖中的应用研究”，《计算机应用研究》，Vol.25, No.3, pp.863-865, 2008
• Yu Zhang, Lin Zhang, Xiuming Shan, “Ranking-Based Statistical Localization for Wireless Sensor Networks,” Proc. of IEEE WCNC 2008, Las Vegas NV, Apr. 2008
• Yu Zhang, Lin Zhang, Xiuming Shan, “Robust Distributed Localization with Data Inference for Wireless Sensor Networks,” Proc. of IEEE ICC 2008, Beijing CHN, May. 2008
• 杨磊，张林，山秀明，“一种基于路由信息的传感器网络定位算法，”《微计算机信息》， 2007，（2）：126-128
• Ningning Qin, Lin Zhang, Baoguo Xu, “A Novel Locomotion Trajectory Algorithm in Wireless Sensor Networks,” Journal of China University of Posts and Telecommunications, 2007 14 (2): 64-68.
• Yong Ding, Martin Alexander Neumann, Michael Beigl, Per Goncalves Da Silva, Lin Zhang, "A Control Loop Approach for Integrating The Future Decentralized Power Markets and Grids" in Proc. IEEE Smart Grid Communication 2013, Vancouver, Canada, September 2013.
• Xiaoxiao Yu, Wenzhu Zhang, Lin Zhang, Victor O.K. Li, Jian Yuan, Ilsun You, “Understanding Urban Dynamics based on Pervasive Sensing: An Experimental Study on Traffic Density and Air Pollution,” Mathematical and Computer Modelling Special issue on “Advances in mobile, ubiquitous and cognitive computing”, Elsevier, 2013.
• Wenzhu Zhang, Bing Zhu, Lin Zhang, Jian Yuan, I. You, “Exploring urban dynamics based on pervasive sensing: Correlation analysis of traffic density and air quality,” Proc. of The Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS‘12), 2012.
• Wenzhu Zhang, Lin Zhang，“ Understanding City Dynamics by Manifold Learning Correlation Analysis,” in proc. of IPSN 2012 Workshop on Urban Sensing, April 2012, Beijing, China.
• Wenzhu Zhang, Lin Zhang, Yong Ding, T. Miyaki, D. Gordon, M. Beigl, “Mobile sensing in metropolitan area: Case study in Beijing,” Proc. of Mobile Sensing Workshop in 13th International Conference on Ubiquitous Computing (UbiComp’11), 2011.
• Lin Zhang, Wenzhu Zhang, Xinyu Mao, Jiantao Jiao, Shijie Zheng, Linglong Li, Yujie Liu, Teng Wang, and Ming Gu, “NOMAD: networked-observation and mobile-agent-based scene abstraction and determination,” in Proc. of the 8th ACM Conference on Embedded Networked Sensor Systems (SenSys '10). pp. 415-416, Zurich, Switzerland, Nov. 2010. (Best Demo Award)
• 罗双武，张林，山秀明，“无线传感器网络在农业监测领域的应用，”《计算机科学》 2008年，35（11）：387-390.
• 杨磊，盖祎，张林，山秀明，王耀希，“灵活低成本无线传感器网络平台FLOWS的设计，”《计算机应用研究》2006，（增刊） ：1267-1268
• 李萌，杨卫华，张林，“虚拟网卡的实现及其在蓝牙无线网络中的应用”，《计算机工程》，vol.29, no.21, 2003, pp.125-128.
• Qiang Su, Lin Zhang, et al., “ISDN-Based Personal Video Communication,” Journal of Tsinghua University, vol.28, no.11, Nov. 1998. pp.121 – 124.
• Lin Zhang, Yong Ren, Xiuming Shan, "1/f noise in the multi-agent cooperative routing," Proc of International Conference of Noise and Fluctuation 2001, Oct. 2001, Florida, USA, pp.541-545.
• Jiantao Jiao, Lin Zhang, Robert Nowak, “Minimax Optimal Bounds for Detectors Based on Estimated Prior Probabilities,” in IEEE Transaction on Information Theory, Vol. 58, Issue 9, 2012 , pp.6101- 6109.
• Xiaoxiao Yu, Yujie Liu, Yixuan Zhu, Wei Feng, Lin Zhang, H. F. Rashvand, Victor O.K. Li, “Efficient Sampling and Compressive Sensing for Urban Monitoring Vehicular Sensor Networks,” IET Wireless Sensor Systems, volume 2, issue 3, pp. 214-221, September 2012.
• Xiaoxiao Yu, Huasha Zhao, Lin Zhang, Shining Wu, Bhaskar Krishnamachari, Victor Li, “Cooperative Sensing and Compression in Vehicular Sensor Networks for Urban Monitoring," Proc. of 2010 IEEE International Conference on Communications (ICC), pp.1-5, 23-27 May 2010
• 秦宁宁，张林，徐保国，“无线传感器网络中的新型入侵轨迹算法”，《计算机工程》，Vol.34, No.3, pp.21-24, 2008
• Kevin Weekly, Donghyun Rim, Lin Zhang, Alexandre M. Bayen, William W. Nazaroff, Costas J. Spanos,"Low-cost coarse airborne particulate matter sensing for indoor occupancy detection", IEEE CASE 2013, Madison, WI, USA, August 2013.
• Yuxun Zhou, Zhaoyi Kang, Lin Zhang, Costas Spanos, "Causal Analysis for Non-stationary Time Series in Sensor Rich Smart Buildings", IEEE CASE 2013, Madison, WI, USA, August 2013
• Bing Zhu, Wenzhu Zhang, Wei Feng, Lin Zhang: Distributed faulty node detection and isolation in delay-tolerant vehicular sensor networks. PIMRC 2012: 1497-1502.
• Yixin Zheng, Jiantao Jiao, Wenzhu Zhang, Lin Zhang, "Understanding Building Vibration with Event Detection and Directed Information based Causal Analysis", in Proc. Stanford Workshop on Building Structure Analysis, Stanford, CA, USA, September 2013
• Bing Zhu, Peter Huang, Leo Guibas, Lin Zhang, "Urban Population Migration Pattern Mining Based on Taxi Trajectories", Mobile Sensing Workshop at CPSWeek 2013, Philadelphia, April 8, 2013.
• Zhaoyi Kang, Yuxun Zhou, Lin Zhang, Costas Spanos, "Virtual Power Sensing Based on a Multiple-Hypothesis Sequential Test" in Proc. IEEE Smart Grid Communication 2013, Vancouver, Canada, September 2013.
• Yang Li, Qixin Huang, Michael Kerber, Lin Zhang, Leo Guibas, "Large-Scale Joint Map Matching of GPS Traces", in Proc. ACM SIGSPATIAL GIS 2013, Orlando, FL, USA, Nov. 2013.
• Chen Chen, Hao Su, Qixin Huang, Lin Zhang, Leo Guibas, "Pathlet Learning for Compressing and Planning Trajectories" in Proc. ACM SIGSPATIAL GIS 2013, Orlando, FL, USA, Nov. 2013.