Publications

2025

• Yatong Chen, Chenzhi Hu, Tomoyoshi Kimura, Shengzhong Liu, Fan Wu, Guihai Chen, “SemiCMT: Contrastive Cross-Modal Knowledge Transfer for IoT Sensing with Semi-Paired Multi-Modal Signals”, in Proc. ACM IMWUT/UbiComp 2025.

2024

• Yuhang Xu, Zixuan Liu, Xinzhe Fu, Shengzhong Liu, Fan Wu, Guihai Chen, “FLEX: Adaptive Task Batch Scheduling with Elastic Fusion in Multi-Modal Multi-View Machine Perception”, in Proc. IEEE RTSS, York, UK, December 2024.
• Denizhan Kara, Tomoyoshi Kimura, Yatong Chen, Jinyang Li, Ruijie Wang, Yizhuo Chen, Tianshi Wang, Shengzhong Liu, Lance Kaplan, Joydeep Bhattacharyya, Tarek Abdelzaher, “PhyMask: An Adaptive Masking Paradigm for Efficient Self-Supervised Learning in IoT”, in Proc. ACM SenSys 2024, Hangzhou, China, November 2024.
• Tomoyoshi Kimura, Jinyang Li, Tianshi Wang, Yizhuo Chen, Ruijie Wang, Denizhan Kara, Maggie Wigness, Joydeep Bhattacharyya, Mudhakar Srivatsa, Shengzhong Liu, Mani Srivastava, Suhas Diggavi, Tarek Abdelzaher, “VibroFM: Towards Micro Foundation Models for Robust Multimodal IoT Sensing”, in Proc. IEEE MASS, Seoul, South Korea, September 2024.
• Ruijie Wang, Jingyuan Huang, Yutong Zhang, Jinyang Li, Yufeng Wang, Wanyu Zhao, Shengzhong Liu, Charith Mendis, Tarek Abdelzaher, “TGOnline: Enhancing Temporal Graph Learning with Adaptive Online Meta-Learning”, in Proc. ACM SIGIR, Washington DC, USA, July 2024.
• Ruijie Wang, Yutong Zhang, Jinyang Li, Shengzhong Liu, Dachun Sun, Tianchen Wang, Tianshi Wang, Yizhuo Chen, Denizhan Kara, Tarek Abdelzaher, “MetaHKG: Meta Hyperbolic Learning for Few-shot Temporal Reasoning”, in Proc. ACM SIGIR, Washington DC, USA, July 2024.
• Tomoyoshi Kimura, Jinyang Li, Tianshi Wang, Denizhan Kara, Yizhuo Chen, Yigong Hu, Ruijie Wang, Maggie Wigness, Shengzhong Liu, Mani Srivastava, Suhas Diggavi, Tarek Abdelzaher, “On the Efficiency and Robustness of Vibration-based Foundation Models for IoT Sensing: A Case Study”, in Proc. FM-Sys Workshop (at CPS-IoT Week), Hong Kong, China, May 2024.
• Yigong Hu, Ila Gokarn, Shengzhong Liu, Archan Misra, Tarek Abdelzaher, “Algorithms for Canvas-based Attention Scheduling with Resizing”, in Proc. IEEE RTAS, Hong Kong, May 2024.
• Denizhan Kara, Shengzhong Liu, Jinyang Li, Dongxin Liu, Tianshi Wang, Ruijie Wang, Yizhuo Chen, Yigong Hu, Tarek Abdelzaher, “FreqMAE: Frequency-Aware Masked Autoencoder for Multi-Modal IoT Sensing”, in Proc. WWW, Singapore, May 2024.
• Shengzhong Liu, Shuochao Yao, Xinzhe Fu, Rohan Tabish, Simon Yu, Ayoosh Bansal, Heechul Yun, Lui Sha, Tarek Abdelzaher, “Taming Algorithmic Priority Inversion in Mission-critical Perception Pipelines”, in Communications of ACM - Research Highlights, Volume 67, Issue 2, January 2024.

2023

• Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li, Suhas Diggavi, Mani Srivastava, Tarek Abdelzaher, “FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space”, in Proc. NeurIPS, New Orleans, USA, December 2023.
• Shengzhong Liu, Xinzhe Fu, Yigong Hu, Maggie Wigness, Philip David, Shuochao Yao, Lui Sha, Tarek Abdelzaher, “Generalized Self-Cueing Real-Time Attention Scheduling with Intermittent Inspection and Image Resizing”, in Springer Journal of Real-Time Systems, Volume 59, June 2023.
• Tianshi Wang, Jinyang Li, Ruijie Wang, Denizhan Kara, Shengzhong Liu, Davis Wertheimer, Antoni Martin, Raghu Ganti, Mudhakar Srivatsa, Tarek Abdelzaher, “SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach”, in Proc. ACM SenSys, Istanbul, Turkey, November 2023.
• Ruijie Wang, Baoyu Li, Yichen Lu, Dachun Sun, Jinning Li, Yuchen Yan, Shengzhong Liu, Hanghang Tong Tarek Abdelzaher, “Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning”, in Proc. ACL, Toronto, Canada, July 2023.
• Deepti Kalasapura, Jinyang Li, Shengzhong Liu, Yizhuo Chen, Ruijie Wang, Tarek Abdelzaher, Matthew Caesar, Joydeep Bhattacharyya, Jae Kim, Guijun Wang, Greg Kimberly, Josh Eckhardt, Denis Osipychev, “TwinSync: A Digital Twin Synchronization Protocol for Bandwidth-limited IoT Applications”, in Proc. IEEE ICCCN, Honolulu, USA, July 2023.
• Yigong Hu, Ila Gokarn, Shengzhong Liu, Archan Misra, Tarek Abdelzaher, “Underprovisioned GPUs: On Sufficient Capacity for Real-Time Mission-Critical Perception”, in Proc. IEEE ICCCN, Honolulu, USA, July 2023.

2022

• Shengzhong Liu, Tianshi Wang, Jinyang Li, Dachun Sun, Mani Srivastava, Tarek Abdelzaher, “AdaMask: Enabling Machine-Centric Video Streaming with Adaptive Frame Masking for DNN Inference Offloading”, in Proc. ACM MM, Lisbon, Portugal, October 2022.
• Shengzhong Liu, Shuochao Yao, Xinzhe Fu, Huajie Shao, Rohan Tabish, Simon Yu, Ayoosh Bansal, Heechul Yun, Lui Sha, Tarek Abdelzaher, “Real-Time Task Scheduling for Machine Perception in Intelligent Cyber-Physical Systems”, IEEE Transactions on Computerss, Volume 71, Issue 8, August 2022.
• Shengzhong Liu, Tianshi Wang, Hongpeng Guo, Xinzhe Fu, Philip David, Maggie Wigness, Archan Misra, Tarek Abdelzaher, “Multi-View Scheduling of Onboard Live Video Analytics to Minimize Frame Processing Latency”, in Proc. IEEE ICDCS, Bologna, Italy, July 2022.
• Shengzhong Liu, Xinzhe Fu, Maggie Wigness, Philip David, Shuochao Yao, Lui Sha, Tarek Abdelzaher, “Self-Cueing Real-Time Attention Scheduling in Criticality-Driven Visual Machine Perception”, in Proc. IEEE RTAS, Milano, Italy, May 2022.
• Huajie Shao, Zhisheng Xiao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Tianshi Wang, Jinyang Li, Tarek Abdelzaher, “ControlVAE: Tuning, Analytical Properties, and Performance Analysis”, in IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 44, Issue 12, December 2022.
• Yigong Hu, Shengzhong Liu, Tarek Abdelzaher, Maggie Wigness, Philip David, “Real-Time Task Scheduling with Image Resizing for Criticality-based Machine Perception”, in Journal of Real-Time Systems, Volume 58, August 2022.
• Ragini Gupta, Bo Chen, Shengzhong Liu, Tianshi Wang, Klara Nahrstedt, Tarek Abdelzaher, Sandeep Sandha, Mani Srivastava, Abel Souza, Prashant Shenoy, Jeffrey Smith, Maggie Wigness, Niranjan Suri, “DARTS: Distributed IoT Architecture for Real-Time, Resilient and AI-Compressed Workflows”, in Proc. ACM ApPLIED 2022 (affiliated with PODC-2022), Online, 2022.
• Dongxin Liu, Tarek Abdelzaher, Tianshi Wang, Yigong Hu, Jinyang Li, Shengzhong Liu, Matthew Caesar, Deepti Kalasapura, Joydeep Bhattacharyya, Nassy Srour, Maggie Wigness, Jae Kim, Guijun Wang, Greg Kimberly, Denis Osipychev, Shouchao Yao, “IoBT-OS: Optimizing the Sensing-to-Decision Pipeline for the Internet of Battlefield Things”, in Proc. IEEE ICCCN, Online, July 2022.
• Jinning Li, Huajie Shao, Dachun Sun, Ruijie Wang, Yuchen Yan, Jinyang Li, Shengzhong Liu, Hanghang Tong, Tarek Abdelzaher, “Unsupervised Belief Representation Learning with Information-Theoretic Variational Graph Auto-Encoders”, in Proc. ACM SIGIR, Madrid, Spain, 2022.
• Ruijie Wang, Zheng li, Dachun Sun, Shengzhong Liu, Jinning Li, Bing Yin, Tarek Abdelzaher, “Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graph”, in Proc. NeurIPS, New Orleans, USA, November 2022.
• Tianshi Wang, Denizhan Kara, Jinyang Li, Shengzhong Liu, Tarek Abdelzaher, Brian Jalaian, “The Methodological Pitfall of Dataset-Driven Research on Deep Learning: An IoT Example”, in Proc. MILCOM, IoT-AE Workshop, Rockville, USA, December 2022.

2021

• Shengzhong Liu*, Franck Le*, Supriyo Chakraborty*, Tarek Abdelzaher, “On Exploring Attention-based Explanation for Transformer Models in Text Classification”, in Proc. IEEE BigData, Online, December 2021.
• Shuochao Yao, Jinyang Li, Dongxin Liu, Tianshi Wang, Shengzhong Liu, Huajie Shao, Tarek Abdelzaher, “Deep Compressive Offloading: Speeding Up Edge Offloading for AI Services”, in ACM GetMobile, Volume 25, Issue 1, March 2021.
• Ruijie Wang, Zijie Huang, Shengzhong Liu, Huajie Shao, Dongxin Liu, Jinyang Li, Tianshi Wang, Dachun Sun, Shuochao Yao, Tarek Abdelzaher, “DyDiff: A Dynamic Variational Framework for Information Diffusion Prediction”, in Proc. ACM SIGIR, Online, July 2021.
• Dongxin Liu, Tianshi Wang, Shengzhong Liu, Ruijie Wang, Shuochao Yao, Tarek Abdelzaher, “Contrastive Self-Supervised Representation Learning for Sensing Signals from the Time-Frequency Perspective”, in Proc. IEEE ICCCN, Athens, Greece, July 2021.
• Yigong Hu, Shengzhong Liu, Tarek Abdelzaher, Maggie Wigness, Philip David, “On Exploring Image Resizing for Optimizing Criticality-based Machine Perception”, in Proc. IEEE RTCSA, Online, August 2021.
• Huajie Shao, Dachun Sun, Shuochao Yao, Lu Su, Zhibo Wang, Dongxin Liu, Shengzhong Liu, Lance Kaplan, Tarek Abdelzaher, “Truth Discovery with Multi-modal Data in Social Sensing”, IEEE Transactions on Computers, Volume 70, Issue 9, September 2021.
• Tianshi Wang, Shuochao Yao, Shengzhong Liu, Jinyang Li, Dongxin Liu, Huajie Shao, Ruijie Wang, Tarek Abdelzaher, “Audio Keyword Reconstruction from On-Device Motion Sensor Signals via Neural Frequency Unfolding”, in Proc. IMWUT/UbiComp, Online, September 2021.
• Dachun Sun, Chaoqi Yang, Jinyang Li, Ruijie Wang, Shuochao Yao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Tianshi Wang, Tarek Abdelzaher, “Computational Modeling of Hierarchically Polarized Groups by Structured Matrix Factorization”, in Frontiers in Big Data, December 2021.

2020

• Shengzhong Liu, Shuochao Yao, Xinzhe Fu, Rohan Tabish, Simon Yu, Ayoosh Bansal, Heechul Yun, Lui Sha, Tarek Abdelzaher, “On Removing Algorithmic Priority Inversion from Mission-critical Machine Inference Pipelines”, in Proc. IEEE RTSS, Houston, USA (Online), December 2020.
• Shengzhong Liu, Shuochao Yao, Yifei Huang, Dongxin Liu, Huajie Shao, Yiran Zhao, Jinyang Li, Tianshi Wang, Ruijie Wang, Chaoqi Yang, Tarek Abdelzaher, “Handling Missing Sensors in Topology-aware IoT Applications with Gated Graph Neural Networks”, in Proc. ACM IMWUT/UbiComp, Cancun, Mexico, September 2020
• Shengzhong Liu*, Shuochao Yao*, Jinyang Li, Dongxin Liu, Tianshi Wang, Huajie Shao, Tarek Abdelzaher, “GlobalFusion: A Global Attentional Deep Learning Framework for Multisensor Information Fusion”, in Proc. ACM IMWUT/UbiComp, Cancun, Mexico, September 2020.
• Shuochao Yao, Jinyang Li, Dongxin Liu, Tianshi Wang, Shengzhong Liu, Huajie Shao, Tarek Abdelzaher, “Deep Compressive Offloading: Speeding Up Neural Network Inference by Trading Edge Computation for Network Latency”, in Proc. ACM SenSys, Yokohama, Japan (Online), November, 2020.
• Chaoqi Yang, Jinyang Li, Ruijie Wang, Shuochao Yao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Tianshi Wang, Tarek Abdelzaher, “Hierarchical Overlapping Belief Estimation by Structured Matrix Factorization”, in Proc. IEEE/ACM ASONAM, The Hague, Netherlands (Virtual), December 2020.
• Shuochao Yao, Yifan Hao, Yiran Zhao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Tianshi Wang, Jinyang Li, Tarek Abdelzaher, “Scheduling Real-time Deep Learning Services as Imprecise Computations”, In Proc. IEEE RTCSA, Gangnueng, South Korea, August 2020.
• Huajie Shao, Shuochao Yao, Andong Jing, Shengzhong Liu, Dongxin Liu, Tianshi Wang, Jinyang Li, Chaoqi Yang, Ruijie Wang, Tarek Abdelzaher, “Misinformation Detection and Adversarial Attack Cost Analysis in Directional Social Networks”, in IEEE ICCCN, Honolulu, Hawaii, August 2020.
• Huajie Shao, Shuochao Yao, Dachun Sun, Aston Zhang, Shengzhong Liu, Dongxin Liu, Jun Wang, Tarek Abdelzaher, “ControlVAE: Controllable Variational Autoencoder”, in Proc. ICML, July 2020.
• Huajie Shao, Dachun Sun, Jiahao Wu, Zecheng Zhang, Aston Zhang, Shuochao Yao, Shengzhong Liu, Tianshi Wang, Chao Zhang, Tarek Abdelzaher “paper2repo: GitHub Repository Recommendation for Academic Papers”, in Proc. WWW, Taipei, Taiwan, April 2020.
• Tarek Abdelzaher, Jiawei Han, Yifan Hao, Andong Jing, Dongxin Liu, Shengzhong Liu, Hoang Hai Nguyen, David M. Nicol, Huajie Shao, Tianshi Wang, Shuochao Yao, Yu Zhang, Omar Malik, Stephen Dipple, James Flamino, Fred Buchanan, Sam Cohen, Gyorgy Korniss, Boleslaw K. Szymanski, “Multiscale Online Media Simulation with SocialCube”, in Journal of Computational and Mathematical Organization Theory, January 2020.

2019

• Shengzhong Liu, Shuochao Yao, Dongxin Liu, Huajie Shao, Yiran Zhao, Xinzhe Fu, Tarek Abdelzaher, “A Latent Hawkes Process Model for Event Clustering and Temporal Dynamics Learning with Applications in GitHub”, in Proc. IEEE ICDCS, Dallas, USA, July 2019.
• Tarek Abdelzaher, Shuochao Yao, Yifan Hao, Yiran Zhao, Ailing Piao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Shaohan Hu, Dulanga Weerakoon, Kasthuri Jayarajah, Archan Misra, “Eugene: Towards Deep Intelligence as a Service”, in Proc. IEEE ICDCS, Dallas, USA, July 2019.
• Yiran Zhao, Shuochao Yao, Dongxin Liu, Huajie Shao, Shengzhong Liu, Tarek Abdelzaher, “Evaluation of Fuel-saving Transportation Systems in the City of Chicago”, in Proc. IEEE ICCCN, Valencia, Spain, July 2019.
• Huajie Shao, Shuochao Yao, Yiran Zhao, Lu Su, Zhibo Wang, Dongxin Liu, Shengzhong Liu, Lance Kaplan, Tarek Abdelzaher, “Unsupervised Fact-finding with Multi-modal Data in Social Sensing”, in Proc. Fusion, Ottawa, Canada, July 2019.
• Yiran Zhao, Shuochao Yao, Dongxin Liu, Huajie Shao, Shengzhong Liu, Tarek Abdelzaher “GreenRoute: A Generalizable Fuel-Saving Vehicular Navigation Service”, in Proc. IEEE ICAC, Umea, Sweden, June 2019.
• Shuochao Yao, Ailing Piao, Wenjun Jiang, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Jinyang Li, Tianshi Wang, Shaohan Hu, Lu Su, Jiawei Han, Tarek Abdelzaher, “STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks”, in Proc. WWW, San Francisco, USA, May 2019.
• Shuochao Yao, Yiran Zhao, Huajie Shao, Dongxin Liu, Shengzhong Liu, Yifan Hao, Ailing Piao, Shaohan Hu, Lu Su, Tarek Abdelzaher, “SADeepSense: Self-Attention Deep Learning Framework for Heterogeneous On-Device Sensors in Internet of Things Applications”, in Proc. IEEE INFOCOM, Paris, France, 2019.

2018

• Shuochao Yao, Yifan Hao, James Flamino, Dongxin Liu, Shengzhong Liu, Huajie Shao, Mouna Bamba, Jiahao Wu, Tarek Abdelzaher, Boleslaw Szymanski “A Predictive Self-Configuring Simulator for Online Media”, Winter Simulation Conference, Gothenburg, Sweden, December 2018.
• Shuochao Yao, Yiran Zhao, Huajie Shao, Shengzhong Liu, Dongxin Liu, Lu Su, Tarek Abdelzaher, “FastDeepIoT: Towards Understanding and Optimizing Neural Network Execution Time on Mobile and Embedded Devices”, in Proc. ACM SenSys, Shenzhen, China, November 2018.
• Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Shaohan Hu, Dongxin Liu, Shengzhong Liu, Lu Su, Tarek Abdelzaher, “SenseGAN: Enabling Deep Learning for Internet of Things with a Semi-Supervised Framework”, in Proc. ACM IMWUT/UbiComp, September 2018.
• Shuochao Yao, Yiran Zhao, Huajie Shao, Chao Zhang, Aston Zhang, Dongxin Liu, Shengzhong Liu, Lu Su, Tarek Abdelzaher, “ApDeepSense: Deep Learning Uncertainty Estimation Without the Pain for IoT Applications”, in Proc. IEEE ICDCS, Vienna, Austria, July 2018.

2017

• Shengzhong Liu*, Zhenzhe Zheng*, Fan Wu, Shaojie Tang, Guihai Chen, “Context-aware Data Quality Estimation in Mobile Crowdsensing”, in Proc. IEEE INFOCOM, Atlanta, USA, May 2017.
• Fan Wu, Shengzhong Liu, Ye Hu, Xinzhe Fu, “Principles of Wireless Sensor Networks (Translated Version in Chinese)”, China Machine Press.