About 

The number of everyday smart devices (e.g., Nest, Notion,  Samsung SmartThings) is projected to grow to the billions in the coming decade. The Cyber-Physical Systems or Internet of Things systems that consist of these devices obtain human information for various smart applications.

    From the system perspective, my research focuses on non-intrusive human information acquisition through ambient sensing. Due to the complexity of the physical world, sensing data distributions can change significantly under different sensing conditions. Therefore, from the data perspective, my research addresses the challenges of limited labeled data by combining physical and data-driven knowledge to model the change.

    UC Merced is located between Silicon Valley and beautiful Yosemite National Park, allowing us to work closely with our industrial collaborators. 

I'm looking for highly motivated PhD students. Please contact me via email.

 

News

  • Our paper "A Signal Quality Assessment Metrics for Vibration-based Human Sensing Data Acquisition" will appear at the SenSys/BuildSys workshop DATA 2019.

  • Our paper "Device-free Sleep Stage Recognition through Bed Frame Vibration Sensing." will appear at the BuildSys workshop DFHS 2019.

  • Our paper "Device-free Multiple People Localization through Floor Vibration" will appear at the BuildSys workshop DFHS 2019.

  • Our workshop CPD 2019 and CML-IoT 2019 will be held as part of Ubicomp 2019 in London in September.

 

Projects

Task-based sensing signal and data quality assessment
Signal quality directly affects the information representative as well as the modeling accuracy in many applications for real-world deployed cyber-physical systems. We combine physical and data-driven knowledge to design metrics to assess the signal and dataset quality for particular sensing tasks. The assessments are used for:
  • Fair dataset quality comparison for system performance evaluation and dataset sharing
  • Collaboratively sensing system adaptation to optimize data quality.
Publication: [W16]
Elderly monitoring with heterogeneous IoT systems
Collaborator: HAA

​Monitoring ​older adults walking pattern and analyzing their fall risk is essential for fall prevention. Prior technologies such as computer vision or audio sensing raise privacy issues for long term home monitoring scenarios. We look into an alternative solution through structural (e.g., floor) vibration (infrastructural sensing) and wearables (mobile sensing). By utilizing their complimentary sensing properties and shared context, we can obtain high-fidelity data for older adults' information learning and modeling.

Pig monitoring through structural vibration
Collaborator: CMU, CMKL, Betagro

Pigs behavior and health condition directly affect farms' profit as well as meat product quality. However, wearables are often easily destroyed by pigs and cameras often suffer from occlusion situations. We look into the structural vibration induced by pigs, and placed vibration sensor underneath the floor slab of pig pens for pig activity monitoring.

Publication: [W12]

Sleep stage monitoring through contact-less sensing
Collaborator: NCH, CMU

Sleep disorder impairs people's health. To accurately analyze patients' sleep quality, it is important to monitor their sleep stages in their natural status. Prior methods, such as  polysomnography (PSG) and Fitbit, are often intrusive and having potential to change user's daily sleep routine. We non-intrusively identify sleep stages through bed-frame vibrations. Our system detects patients' movements  during their sleep and estimates their sleep stages via their movements induced vibration on the bed frame.

 

Publication: [W14]

 

People

PI: Shijia Pan (cv pdf, Google scholar)

Dr. Shijia Pan received her Bachelor's degree in Computer Science and Technology from the University of Science and Technology of China (USTC) and her Ph.D. degree in Electrical and Computer Engineering at Carnegie Mellon University (CMU). Her research interests include cyber-physical systems, Internet-of-Things (IoT), and ubiquitous computing. She worked in multiple disciplines and focused on indoor human information acquisition through ambient sensing. 

Research Specialist: Yue Zhang

Yue Zhang received his Master's degree and Bachelor's degree in the Department of Electronic Engineering at Tsinghua University in 2019 and 2016. At present, he is a visiting researcher in the school of Engineering, University of California, Merced. His research interests include sensor networks, embedded systems, indoor human information acquisition.

Supervised Students:

Zhizhang Hu, Master Student,

School of Architecture, CMU

Laixi Shi, PhD Student

Electrical and Computer Engineering, CMU

 

Courses

2020 Spring: EECS 283 Advanced Topics in Intelligent Systems

(syllabus)

 

Publications

Journal Publication

[M12] Pei Zhang, Shijia Pan, Mostafa Mirshekari, Jonathon Fagert and Haeyoung Noh, "Structures as Sensors: Indirect Sensing for Inferring Users and Environments" in Computer, vol. 52, no. 10, pp. 84-88, 2019.

 

[J11] Mostafa Mirshekari, Jonathon Fagert, Shijia Pan, Pei Zhang and Hae Young Noh. Step-Level Occupant Detection across Different Structures through Footstep-Induced Floor Vibration using Model Transfer. Accepted by Journal of Engineering Mechanics.
Impact factor 2.264.

[J10] Xinlei Chen, Yu Wang, Jiayou He, Shijia Pan, Yong Li, Pei Zhang. CAP: Context-aware App Usage Prediction with Heterogeneous Graph Embedding. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2019.

[J9] Ji Jia, Chengtian Xu, Shijia Pan, Stephen Xia, Peter Wei, Hae Young Noh, Pei Zhang, and Xiaofan Jiang. Conductive Thread-Based Textile Sensor for Continuous Perspiration Level Monitoring. Sensors, 18(11), 3775.
Impact factor 2.475.

[J8] Shijia Pan, Mostafa Mirshekari,  Jonathon Fagert, Carlos Ruiz,  Hae Young Noh,  and Pei Zhang. Area Occupancy Counting through Sparse Ambient Structural Vibration Sensing. IEEE Pervasive Computing Special Issue - IoT Communication. 

[J7] Carlos Ruiz, Shijia Pan, Adeola Bannis, Xinlei Chen, Carlee Joe-Wong, Hae Young Noh, Pei Zhang. IDrone: Robust Drone Identification through Motion Actuation Feedback. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 2018.

[J6] Jun Han, Shijia Pan, Manal Kumar Sinha, Hae Young Noh, Pei Zhang and Patrick Tague. Smart Home Occupant Identification via Sensor Fusion Across On-Object Devices. Fast-tracked at ACM Transactions on Sensor Networks (TOSN) - Special Issue on Systems for Smart and Efficient Built Environments, 2018.
Impact factor 2.313.

[J5] Mostafa Mirshekari, Shijia Pan, Jonathon Fagert, Eve Schooler, Pei Zhang and Hae Young Noh. Occupant Localization using Footstep-Induced Structural Vibration. Mechanical Systems and Signal Processing 112 (2018): 77-97.
Impact factor 3.99.

[J4] Shijia Pan, Mostafa Mirshekari, Jonathon Fagert, Ceferino Gabriel Ramirez, Albert Jin Chung, Chih Chi Hu, John Paul Shen, Pei Zhang, and Hae Young Noh. Characterizing human activity induced impulse and slip-pulse excitations through structural vibration. Journal of Sound and Vibration 414 (2018): 61-80.
Impact factor 2.593.

[J3] Xinlei Chen, Aveek Purohit, Shijia Pan, Carlos Ruiz, Jun Han, Zheng Sun, Frank Mokaya, Patrick Tague and Pei Zhang. Design Experiences in Minimalistic Flying Sensor Node Platform through SensorFly. Transactions on Sensor Networks (TOSN), vol. 13, no. 4 (2017).
Impact factor 2.313.

[J2] Shijia Pan, Tong Yu, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, Hae Young Noh, and Pei Zhang. FootprintID: Indoor Pedestrian Identification through Ambient Structural Vibration Sensing. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 1, no. 3 (2017): 89. 
Acceptance rate = 23.9%

[J1] Shijia Pan, Susu Xu, Mostafa Mirshekari, Pei Zhang, and Hae Young Noh. Collaboratively Adaptive Vibration Sensing System for High Fidelity Monitoring of Structural Responses Induced by Pedestrians. Frontiers in Built Environment 3 (2017): 28.

Fully Peer-Reviewed Conference Publication

[C12] Shijia Pan, Mario Berges, Juleen Rodakowski,   Pei Zhang, and Hae Young Noh. Fine-Grained Activities of Daily Living Recognition through Structural Vibration and Electrical Sensing. In the Proceeding of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys' 19), November, 2019.
Acceptance rate = 30%

 

[C11] Carlos Ruiz, Joao Falcao, Shijia Pan, Hae Young Noh, and Pei Zhang.    AIM3S: Autonomous Inventory Monitoring through Multi-Modal Sensing for Cashier-Less Convenience Stores. In the Proceeding of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys' 19), November, 2019.
Acceptance rate = 30%

[C10] Jun Han, Albert Chung, Manal Kumar Sinha, Madhumitha Harishankar, Shijia Pan, Hae Young Noh, Pei Zhang, and Patrick Tague. Do You Feel What I Hear? Enabling Autonomous IoT Device Pairing using Different Sensor Types. In the Proceedings of the IEEE Symposium on Security & Privacy, May 2018.
Acceptance rate = 11.5%

[W9] Shijia Pan, Carlos Ruiz, Jun Han, Adeola Bannis, Patrick Tague, Hae Young Noh and Pei Zhang. UniverSense: IoT Device Pairing through Heterogeneous Sensing Signals. In Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications. ACM, 2018.
 Acceptance rate = 29.2%

[W8] Amelie Bonde, Shijia Pan, Zhenhua Jia, Yanyong Zhang, Hae Young Noh and Pei Zhang. VRRM: Vehicular Vibration-based Heart RR-Interval Monitoring System. In Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications, ACM, 2018. 
Acceptance rate = 29.2%

[C7] Jun Han, Shijia Pan, Manal Kumar Sinha, Hae Young Noh, Pei Zhang and Patrick Tague. SenseTribute: Smart Home Occupant Identification via Fusion Across On-Object Sensing Devices. In Proceedings of the 4th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys 2017). 
Acceptance rate = 31.3%, Audience's Choice Award

[C6] Shijia Pan, Ceferino Gabriel Ramirez, Mostafa Mirshekari, Jonathon Fagert, Albert Jin Chung, Chih Chi Hu, John Paul Shen, Hae Young Noh, and Pei Zhang. "SurfaceVibe: vibration-based tap \& swipe tracking on ubiquitous surfaces." In Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2017), pp. 197-208. 2017.
Acceptance rate = 18.3%

[W5] Shijia Pan, Ningning Wang, Yuqiu Qian, Irem Velibeyoglu, Hae Young Noh, and Pei Zhang. "Indoor person identification through footstep induced structural vibration." In Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications. ACM, 2015. 
Acceptance rate = 28.8%

[C4] Aveek Purohit, Zheng Sun, Shijia Pan, and Pei Zhang. "Sugartrail: Indoor navigation in retail environments without surveys and maps." In Proceedings of the 10th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2013 , pp. 300-308. IEEE, 2013.
Acceptance rate = 29.5%

[C3] Zheng Sun, Shijia Pan, Yu-Chi Su, and Pei Zhang. "Headio: zero-configured heading acquisition for indoor mobile devices through multimodal context sensing." In Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing (Ubicomp 2013), pp. 33-42. ACM, 2013.
Acceptance rate = 23.4%

[W2] Zheng Sun, Aveek Purohit, Shijia Pan, Frank Mokaya, Raja Bose, and Pei Zhang. "Polaris: getting accurate indoor orientations for mobile devices using ubiquitous visual patterns on ceilings." In Proceedings of the Twelfth Workshop on Mobile Computing Systems \& Applications, p. 14. ACM, 2012.
Acceptance rate = 21.6%

[C1] Zheng Sun, Aveek Purohit, Kaifei Chen, Shijia Pan, Trevor Pering, and Pei Zhang. "PANDAA: physical arrangement detection of networked devices through ambient-sound awareness." In Proceedings of the 13th international conference on Ubiquitous computing (Ubicomp 2011), pp. 425-434. ACM, 2011.
Acceptance rate = 16.6%

Other Conference Publication

[W16] Yue Zhang, Lin Zhang, Hae Young Noh, Pei Zhang, and Shijia Pan. A Signal Quality Assessment Metrics for Vibration-based Human Sensing Data Acquisition. In the 2nd Workshop on Data Acquisition to Analysis. November 10, 2019, New York, NY, USA.

[W15] Laixi Shi, Mostafa Mirshekari, Jonathon Fagert, Yuejie Chi, Hae Young Noh, Pei Zhang, and Shijia Pan. Device-free Multiple People Localization through Floor Vibration. In the 1st ACM International Workshop on Device-Free Human Sensing, November 10, 2019, New York, NY, USA.

[W14] Zhizhang Hu, Emre Sezgin, Simon Lin, Pei Zhang, Hae Young Noh, and Shijia Pan. Device-free Sleep Stage Recognition through Bed Frame Vibration Sensing. In the 1st ACM International Workshop on Device-Free Human Sensing, November 10, 2019, New York, NY, USA.

[W13] Carlos Ruiz, Shijia Pan, Hae Young Noh, and Pei Zhang. WhereWear: Calibration-free Wearable Device Identification through Ambient Sensing. In The 5th ACM Workshop on Wearable Systems and Applications (WearSys’19), June 21, 2019, Seoul, Republic of Korea.

[W12] Amelie Bonde, Shijia Pan, Orathai Sangpetch, Akkarit Sangpetch, Woranun Woramontri, and Pei Zhang. "Structural vibration sensing to evaluate animal activity on a pig farm." In the 1st Workshop on Data Acquisition to Analysis. pp. 25-26. 2018.

[W11] Yue Zhang, Shijia Pan, Jonathon Fagert, Mostafa Mirshekari, Hae Young Noh, Pei Zhang, and Lin Zhang. "Occupant Activity Level Estimation Using Floor Vibration." In Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, pp. 1355-1363. ACM, 2018.

[W10] Tong Yu*, Shijia Pan*, Susu Xu Mostafa Mishakeri, Jonathon Fagert, Xinlei Chen, Haeyoung Noh, Pei Zhang and Ole J. Mengshoel. ILPC: Iterative Learning using Physical Constraints in Real-world Sensing Data. AAAI Workshop SmartIoT 2018.
*equal contribution among authors.

[W9] Jonathon Fagert, Mostafa Mirshekari, Shijia Pan, Pei Zhang, and Hae Young Noh. "Monitoring Hand-Washing Practices using Structural Vibrations." In Proceedings of the 11th International Workshop on Structural Health Monitoring, Stanford University, Stanford, CA, USA, September 2017.

[C8] Jonathon Fagert, Mostafa Mirshekari, Shijia Pan, Pei Zhang, and Hae Young Noh. "Characterizing Left-Right Gait Balance Using Footstep-Induced Structural Vibrations." In SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring, pp. 1016819-1016819. International Society for Optics and Photonics, Portland, Oregon, United States, March 2017.

[W7] Ji Jia, Chengtian Xu, Shijia Pan, Stephen Xia, Peter Wei, Hae Young Noh, Pei Zhang, and Xiaofan Jiang. Moisture Based Perspiration Level Estimation. Ubicomp Workshop CPD 2018.

[W6] Xinlei Chen, Xiangxiang Xu, Xinyu Liu, Shijia Pan, Jiayou He, Hae Young Noh, Lin Zhang, Pei Zhang. PGA: Physics Guided and Adaptive Approach for Mobile Fine-Grained Air Pollution Estimation. Ubicomp Workshop CPD 2018.

[C5] Shijia Pan, Mostafa Mirshekari, Pei Zhang, and Hae Young Noh. "Occupant traffic estimation through structural vibration sensing." SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring (2016): 980306-980306.

[C4] Mostafa Mirshekari, Shijia Pan, Pei Zhang, and Hae Young Noh. "Characterizing wave propagation to improve indoor step-level person localization using floor vibration." SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring (2016): 980305-980305.

 

[C3] Lam, Mike, Mostafa Mirshekari, Shijia Pan, Pei Zhang, and Hae Young Noh. "Robust occupant detection through step-induced floor vibration by incorporating structural characteristics." In Dynamics of Coupled Structures, Volume 4, pp. 357-367. Springer International Publishing, 2016.

[C2] Shijia Pan, Amelie Bonde, Jie Jing, Lin Zhang, Pei Zhang, and Hae Young Noh. "Boes: building occupancy estimation system using sparse ambient vibration monitoring." SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring (2014): 90611O-90611O.

[W1] Shijia Pan, An Chen, and Pei Zhang. "Securitas: user identification through RGB-NIR camera pair on mobile devices." In Proceedings of the Third ACM workshop on Security and privacy in smartphones \& mobile devices, pp. 99-104. ACM, 2013.
 

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