Zhishan Guo

Farhangi, A., Bian, J., Huang, A., Xiong, H., Wang, J., & Guo, Z. (2023). AA-forecast: anomaly-aware forecast for extreme events. Data Mining and Knowledge Discovery, 37(3), 1209–1229. https://doi.org/10.1007/s10618-023-00919-7

Al Arafat, A., Vaidhun, S., Liu, L., Yang, K., & Guo, Z. (2023). Compositional Mixed-Criticality Systems with Multiple Executions and Resource-Budgets Model. 2023 IEEE 29TH REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM, RTAS, pp. 67–79. https://doi.org/10.1109/RTAS58335.2023.00013

Hossain, M. S. B., Guo, Z., & Choi, H. (2023). Estimation of Lower Extremity Joint Moments and 3D Ground Reaction Forces Using IMU Sensors in Multiple Walking Conditions: A Deep Learning Approach. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 27(6), 2829–2840. https://doi.org/10.1109/JBHI.2023.3262164

Gray, N., Moraes, M., Bian, J., Wang, A., Tian, A., Wilson, K., … Guo, Z. (2023, July 28). GLARE: A Dataset for Traffic Sign Detection in Sun Glare. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, Vol. 7. https://doi.org/10.1109/TITS.2023.3294411

Vaidhun, S., She, T., Gu, Q., Das, S. K., Yang, K., & Guo, Z. (2023). Precise Mixed-Criticality Scheduling on Varying-Speed Multiprocessors. IEEE Transactions on Computers. https://doi.org/10.1109/TC.2022.3197078

Sun, J., Duan, K., Li, X., Guan, N., Guo, Z., Deng, Q., & Tan, G. (2023). Real-Time Scheduling of Autonomous Driving System with Guaranteed Timing Correctness. 2023 IEEE 29TH REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM, RTAS, pp. 185–197. https://doi.org/10.1109/RTAS58335.2023.00022

Abdelzaher, T., Agrawal, K., Baruah, S., Burns, A., Davis, R. I. I., Guo, Z., & Hu, Y. (2023, March 13). Scheduling IDK classifiers with arbitrary dependences to minimize the expected time to successful classification. REAL-TIME SYSTEMS, Vol. 3. https://doi.org/10.1007/s11241-023-09395-0

Reghenzani, F., Guo, Z., & Fornaciari, W. (2023). Software Fault Tolerance in Real-Time Systems: Identifying the Future Research Questions. ACM Computing Surveys, 55(14S). https://doi.org/10.1145/3589950

Moniruzzaman, M., Yin, Z., Bin Hossain, M. S., Choi, H., & Guo, Z. (2023). Wearable Motion Capture: Reconstructing and Predicting 3D Human Poses From Wearable Sensors. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 27(11), 5345–5356. https://doi.org/10.1109/JBHI.2023.3311448

Reghenzani, F., Guo, Z., Santinelli, L., & Fornaciari, W. (2022). A Mixed-Criticality Approach to Fault Tolerance: Integrating Schedulability and Failure Requirements. Presented at the 2022 IEEE 28th Real-Time and Embedded Technology and Applications Symposium (RTAS). https://doi.org/10.1109/rtas54340.2022.00011

Farhangi, A., Huang, A., & Guo, Z. (2022). A Novel Deep Learning Model For Hotel Demand and Revenue Prediction amid COVID-19. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/hicss.2022.217

Hossain, M. S. B., Dranetz, J., Choi, H., & Guo, Z. (2022). DeepBBWAE-Net: A CNN-RNN Based Deep SuperLearner for Estimating Lower Extremity Sagittal Plane Joint Kinematics Using Shoe-Mounted IMU Sensors in Daily Living. IEEE Journal of Biomedical and Health Informatics, 26(8), 3906–3917. https://doi.org/10.1109/JBHI.2022.3165383

Vaidhun, S., Guo, Z., Bian, J., Xiong, H., & Das, S. (2022). Dynamic Path Planning for Unmanned Aerial Vehicles Under Deadline and Sector Capacity Constraints. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(4), 839–851. https://doi.org/10.1109/TETCI.2021.3122743

Hossain, M. S. B., Choi, H., & Guo, Z. (2022). Estimating lower extremity joint angles during gait using reduced number of sensors count via deep learning (Y. Xie, X. Jiang, W. Tao, & D. Zeng, Eds.). https://doi.org/10.1117/12.2643786

Bin Hossain, M. S., Guo, Z., & Choi, H. (2022). Estimation of Hip, Knee, and Ankle Joint Moment Using a Single IMU Sensor on Foot Via Deep Learning. 2022 IEEE/ACM CONFERENCE ON CONNECTED HEALTH: APPLICATIONS, SYSTEMS AND ENGINEERING TECHNOLOGIES (CHASE 2022), pp. 25–33. https://doi.org/10.1145/3551455.3559605

Bian, J., Arafat, A. A., Xiong, H., Li, J., Li, L., Chen, H., … Guo, Z. (2022). Machine Learning in Real-Time Internet of Things (IoT) Systems: A Survey. IEEE Internet of Things Journal, 9(11), 8364–8386. https://doi.org/10.1109/JIOT.2022.3161050

Guo, Z., Vaidhun, S., Satinelli, L., Arefin, S., Wang, J., & Yang, K. (2022). Mixed-Criticality Scheduling Upon Permitted Failure Probability and Dynamic Priority. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 41(1), 62–75. https://doi.org/10.1109/TCAD.2021.3053232

Farhangi, A., Sui, N., Hua, N., Bai, H., Huang, A., & Guo, Z. (2022). Protoformer: Embedding Prototypes for Transformers. https://doi.org/10.1007/978-3-031-05933-9_35

Bi, R., He, Q., Sun, J., Sun, Z., Guo, Z., Guan, N., & Tan, G. (2022). Response Time Analysis for Prioritized DAG Task with Mutually Exclusive Vertices. 2022 IEEE 43RD REAL-TIME SYSTEMS SYMPOSIUM (RTSS 2022), pp. 460–473. https://doi.org/10.1109/RTSS55097.2022.00046

Arafat, A. A., Vaidhun, S., Wilson, K. M., Sun, J., & Guo, Z. (2022). Response time analysis for dynamic priority scheduling in ROS2. Presented at the DAC '22: 59th ACM/IEEE Design Automation Conference. https://doi.org/10.1145/3489517.3530447

Farhangi, A., Bian, J., Huang, A., Xiong, H., Wang, J., & Guo, Z. (2022). Time Series Prediction with Anomaly-Aware Recurrent Neural Networks. Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD). Presented at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), Grenoble.

Li, R., Guan, N., Jiang, X., Guo, Z., Dong, Z., & Lv, M. (2022). Worst-Case Time Disparity Analysis of Message Synchronization in ROS. 2022 IEEE 43RD REAL-TIME SYSTEMS SYMPOSIUM (RTSS 2022), pp. 40–52. https://doi.org/10.1109/RTSS55097.2022.00014

Reghenzani, F., Bhuiyan, A., Fornaciari, W., & Guo, Z. (2021). A Multi-Level DPM Approach for Real-Time DAG Tasks in Heterogeneous Processors. Presented at the 2021 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss52674.2021.00014

Huang, A. Y., Fisher, T., Ding, H., & Guo, Z. (2021). A network analysis of cross-occupational skill transferability for the hospitality industry. International Journal of Contemporary Hospitality Management, 33(12), 4215–4236. https://doi.org/10.1108/ijchm-01-2021-0073

Sanzid, M., Dranetz, J., Choi, H., & Guo, Z. (2021). An Ensemble Machine Learning Approach for the Estimation of Lower Extremity Kinematics Using Shoe-Mounted IMU Sensors. Presented at the 26th Annual Meeting of the GCMAS. https://doi.org/10.52141/gcmas2021_172

Zhao, B., Xiong, H., Bian, J., Guo, Z., Xu, C.-Z., & Dou, D. (2021). COMO: Efficient Deep Neural Networks Expansion With COnvolutional MaxOut. IEEE Transactions on Multimedia, 23, 1722–1730. https://doi.org/10.1109/TMM.2020.3002614

Bian, J., Yang, S., Xiong, H., Wang, L., Fu, Y., Sun, Z., & Guo, Z. (2021). CRLEDD: Regularized Causalities Learning for Early Detection of Diseases Using Electronic Health Record (EHR) Data. IEEE Transactions on Emerging Topics in Computational Intelligence. https://doi.org/10.1109/TETCI.2020.3010017

Sun, J., Guan, N., Guo, Z., Xue, Y., He, J., & Tan, G. (2021). Calculating Worst-Case Response Time Bounds for OpenMP Programs with Loop Structures. Presented at the 2021 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss52674.2021.00022

Bhuiyan, A., Yang, K., Arefin, S., Saifullah, A., Guan, N., & Guo, Z. (2021). Mixed-criticality real-time scheduling of gang task systems. Real-Time Systems, 57(3), 268–301. https://doi.org/10.1007/s11241-021-09368-1

Liu, X., Han, X., Zhao, L., & Guo, Z. (2021). Narrowing the speedup factor gap of partitioned EDF. Information and Computation, 281, 104743. https://doi.org/10.1016/j.ic.2021.104743

Wang, Y., Jiang, X., Guan, N., Guo, Z., Liu, X., & Yi, W. (2021). Partitioning-Based Scheduling of OpenMP Task Systems With Tied Tasks. IEEE Transactions on Parallel and Distributed Systems, 32(6), 1322–1339. https://doi.org/10.1109/TPDS.2020.3048373

She, T., Vaidhun, S., Gu, Q., Das, S., Guo, Z., & Yang, K. (2021). Precise Scheduling of Mixed-Criticality Tasks on Varying-Speed Multiprocessors. Presented at the RTNS'2021: 29th International Conference on Real-Time Networks and Systems. https://doi.org/10.1145/3453417.3453428

She, T., Guo, Z., Gu, Q., & Yang, K. (2021). Reserving Processors by Precise Scheduling of Mixed-Criticality Tasks. Presented at the 2021 IEEE 27th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). https://doi.org/10.1109/rtcsa52859.2021.00020

Wang, K., Xiong, H., Bian, J., Zhu, Z., Gao, Q., Guo, Z., … Dou, D. (2021). Sampling Sparse Representations with Randomized Measurement Langevin Dynamics. ACM Transactions on Knowledge Discovery from Data, 15(2), 1–21. https://doi.org/10.1145/3427585

Liu, X., Chen, Z., Han, X., Sun, Z., & Guo, Z. (2021). Tighter Bounds of Speedup Factor of Partitioned EDF for Constrained-Deadline Sporadic Tasks. Presented at the 2021 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss52674.2021.00046

Sun, J., Wang, T., Duan, K., Lu, B., Ren, J., Guo, Z., & Tan, G. (2021). Toward Real-Time Guaranteed Scheduling for Autonomous Driving Systems. Proceedings of the 42nd IEEE Real-Time Systems Symposium (RTSS 2021), Industry Challenge. Presented at the 42nd IEEE Real-Time Systems Symposium (RTSS 2021), Industry Challenge, Dortmund, DE.

Arafat, A. A., Guo, Z., & Awad, A. (2021). VR-Spy: A Side-Channel Attack on Virtual Key-Logging in VR Headsets. https://doi.org/10.1109/vr50410.2021.00081

Saifullah, A., Fahmida, S., Modekurthy, V., Fisher, N., & Guo, Z. (2020). CPU Energy-Aware Parallel Real-Time Scheduling. Proceedings of the 32th Euromicro Conference on Real-Time Systems (ECRTS). Presented at the 32th Euromicro Conference on Real-Time Systems (ECRTS), Modena, Italy.

Sun, J., Shi, R., Wang, K., Guan, N., & Guo, Z. (2020). Efficient Feasibility Analysis for Graph-Based Real-Time Task Systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(11), 3385–3397. https://doi.org/10.1109/tcad.2020.3012174

Sun, J., Shi, R., Wang, K., Guan, N., & Guo, Z. (2020). Efficient Feasibility Analysis for Graph-based Real-Time Task Systems. International Conference on Embedded Software (EMSOFT). Presented at the International Conference on Embedded Software (EMSOFT).

Bhuiyan, A., Liu, D., Khan, A., Saifullah, A., Guan, N., & Guo, Z. (2020). Energy-Efficient Parallel Real-Time Scheduling on Clustered Multi-Core. IEEE Transactions on Parallel and Distributed Systems, 31(9), 2097–2111. https://doi.org/10.1109/TPDS.2020.2985701

Yang, K., Bhuiyan, A., & Guo, Z. (2020). F2VD. Presented at the ICCAD '20: IEEE/ACM International Conference on Computer-Aided Design. https://doi.org/10.1145/3400302.3415716

Zsiros, J., Blalock, B., Craig, D., Vaidhun, S., Wang, A., & Guo, Z. (2020). GARDS: Generalized Autonomous Robotic Delivery System. Presented at the 2020 International Conference on Connected and Autonomous Driving (MetroCAD). https://doi.org/10.1109/metrocad48866.2020.00013

Agrawal, K., Baruah, S., Guo, Z., Li, J., & Vaidhun, S. (2020). Hard-Real-Time Routing in Probabilistic Graphs to Minimize Expected Delay. 2020 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss49844.2020.00017

Guo, Z., Yang, K., Yao, F., & Awad, A. (2020). Inter-task cache interference aware partitioned real-time scheduling. Presented at the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing. https://doi.org/10.1145/3341105.3374014

Bian, J., Xiong, H., Fu, Y., Huan, J., & Guo, Z. (2020). MP
            <sup>2
            SDA. ACM Transactions on Knowledge Discovery from Data, 14(3), 1–22. https://doi.org/10.1145/3374919

Liu, S., Guan, N., Guo, Z., & Yi, W. (2020). MiniTEE—A Lightweight TrustZone-Assisted TEE for Real-Time Systems. Electronics, 9(7), 1130. https://doi.org/10.3390/electronics9071130

Singh, J., Santinelli, L., Reghenzani, F., Bletsas, K., & Guo, Z. (2020). Mixed Criticality Scheduling of Probabilistic Real-Time Systems. Proceeding of the 10th European Congress on Embedded Real Time Software and Systems. Presented at the 0th European Congress on Embedded Real Time Software and Systems, Toulouse, France.

Sun, J., Li, F., Guan, N., Zhu, W., Xiang, M., Guo, Z., & Yi, W. (2020). On Computing Exact WCRT for DAG Tasks. Presented at the 2020 57th ACM/IEEE Design Automation Conference (DAC). https://doi.org/10.1109/dac18072.2020.9218744

Sun, J., Chi, Y., Xu, T., Cao, L., Guan, N., Guo, Z., & Yi, W. (2020). On the Volume Calculation for Conditional DAG Tasks: Hardness and Algorithms. Presented at the 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE). https://doi.org/10.23919/date48585.2020.9116559

Bhuiyan, A., Reghenzani, F., Fornaciari, W., & Guo, Z. (2020). Optimizing Energy in Non-Preemptive Mixed-Criticality Scheduling by Exploiting Probabilistic Information. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 39(11), 3906–3917. https://doi.org/10.1109/tcad.2020.3012231

Bhuiyan, A., Reghenzani, F., Fornaciari, W., & Guo, Z. (2020). Optimizing Energy in Non-preemptive Mixed-Criticality Scheduling by Exploiting Probabilistic Information. International Conference on Embedded Software (EMSOFT). Presented at the International Conference on Embedded Software (EMSOFT).

Hossain, M. S. B., Lee, Y., Hong, J., Choi, H., & Guo, Z. (2020). Predicting lower limb 3D kinematics during gait using reduced number of wearable sensors via deep learning. Proceedings of the 44th Meetings of the American Society of Biomechanics (ASB). Presented at the 44th Meetings of the American Society of Biomechanics (ASB).

Vaidhun, S., Guo, Z., Bian, J., Xiong, H., & Das, S. K. (2020). Priority-based Multi-Flight Path Planning with Uncertain Sector Capacities. Presented at the 2020 12th International Conference on Advanced Computational Intelligence (ICACI). https://doi.org/10.1109/icaci49185.2020.9177760

Sun, J., Li, J., Guo, Z., Zou, A., Zhang, X., Agrawal, K., & Baruah, S. (2020). Real-Time Scheduling upon a Host-Centric Acceleration Architecture with Data Offloading. Presented at the 2020 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). https://doi.org/10.1109/rtas48715.2020.00-17

Agrawal, K., Baruah, S., Guo, Z., & Li, J. (2020). The safe and effective application of probabilistic techniques in safety-critical systems. Presented at the ICCAD '20: IEEE/ACM International Conference on Computer-Aided Design. https://doi.org/10.1145/3400302.3415674

Huang, A., Makridis, C., Baker, M., Medeiros, M., & Guo, Z. (2020). Understanding the Impact of COVID-19 Intervention Policies on the Labor Market of the Hospitality and Retail Industries. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3637766

Huang, A., Makridis, C., Baker, M., Medeiros, M., & Guo, Z. (2020). Understanding the impact of COVID-19 intervention policies on the hospitality labor market. International Journal of Hospitality Management, 91, 102660. https://doi.org/10.1016/j.ijhm.2020.102660

Xiong, H., Cheng, W., Bian, J., Hu, W., Sun, Z., & Guo, Z. (2019). <inline-formula> 
                     <tex-math notation="LaTeX">$\mathcal{DBSDA}$ </tex-math>
                  </inline-formula>: Lowering the Bound of Misclassification Rate for Sparse Linear Discriminant Analysis via Model Debiasing. IEEE Transactions on Neural Networks and Learning Systems, 30(3), 707–717. https://doi.org/10.1109/tnnls.2018.2846783

Zhao, M., Liu, D., Jiang, X., Liu, W., Xue, G., Xie, C., … Guo, Z. (2019). CASS: Criticality-Aware Standby-Sparing for real-time systems. Journal of Systems Architecture, 100, 101661. https://doi.org/10.1016/j.sysarc.2019.101661

Yang, Y., Guo, Z., Xiong, H., Ding, D.-W., Yin, Y., & Wunsch, D. C. (2019). Data-Driven Robust Control of Discrete-Time Uncertain Linear Systems via Off-Policy Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems, 30(12), 3735–3747. https://doi.org/10.1109/TNNLS.2019.2897814

Yang, K., & Guo, Z. (2019). EDF-Based Mixed-Criticality Scheduling with Graceful Degradation by Bounded Lateness. Presented at the 2019 IEEE 25th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). https://doi.org/10.1109/rtcsa.2019.8864559

Guo, Z., Bhuiyan, A., Liu, D., Khan, A., Saifullah, A., & Guan, N. (2019). Energy-Efficient Real-Time Scheduling of DAGs on Clustered Multi-Core Platforms. Presented at the 2019 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). https://doi.org/10.1109/rtas.2019.00021

He, Q., Jiang, X., Guan, N., & Guo, Z. (2019). Intra-Task Priority Assignment in Real-Time Scheduling of DAG Tasks on Multi-Cores. IEEE Transactions on Parallel and Distributed Systems, 30(10), 2283–2295. https://doi.org/10.1109/TPDS.2019.2910525

Singh, J., Santinelli, L., Reghenzani, F., Bletsas, K., Doose, D., & Guo, Z. (2019). Mixed Criticality Scheduling of Probabilistic Real-Time Systems. https://doi.org/10.1007/978-3-030-35540-1_6

Bhuiyan, A. ahmed, Yang, K., Arefin, S., Saifullah, A., Guan, N., & Guo, Z. (2019). Mixed-Criticality Multicore Scheduling of Real-Time Gang Task Systems. Presented at the 2019 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss46320.2019.00048

Wang, L., Yang, Y., Ding, D., Yin, Y., Guo, Z., & Wunsch, D. C. (2019). Model-Free Temporal Difference Learning for Non-Zero-Sum Games. Presented at the 2019 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn.2019.8851866

Bian, J., Wang, W., Zhang, X., Wang, W., Huang, A., & Guo, Z. (2019). On Generating Dominators of Customer Preferences. Presented at the 2019 IEEE International Conference on Big Data (Big Data). https://doi.org/10.1109/bigdata47090.2019.9006194

Bhuiyan, A., Sruti, S., Guo, Z., & Yang, K. (2019). Precise scheduling of mixed-criticality tasks by varying processor speed. Presented at the RTNS 2019: 27th International Conference on Real-Time Networks and Systems. https://doi.org/10.1145/3356401.3356410

Li, L., Xiong, H., Guo, Z., Wang, J., & Xu, C.-Z. (2019). SmartPC: Hierarchical Pace Control in Real-Time Federated Learning System. Presented at the 2019 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss46320.2019.00043

Xiong, H., Wang, K., Bian, J., Zhu, Z., Xu, C.-Z., Guo, Z., & Huan, J. (2019). SpHMC: Spectral Hamiltonian Monte Carlo. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 5516–5524. https://doi.org/10.1609/aaai.v33i01.33015516

Farhangi, A., Bian, J., Wang, J., & Guo, Z. (2019). Work-in-Progress: A Deep Learning Strategy for I/O Scheduling in Storage Systems. Presented at the 2019 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss46320.2019.00066

Sun, J., Guan, N., Jiang, X., Chang, S., Guo, Z., Deng, Q., & Yi, W. (2018). A Capacity Augmentation Bound for Real-Time Constrained-Deadline Parallel Tasks Under GEDF. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 37(11), 2200–2211. https://doi.org/10.1109/TCAD.2018.2857362

Sun, J., Guan, N., Jiang, X., Chang, S., Guo, Z., Deng, Q., & Yi, W. (2018). A Capacity Augmentation Bound for Real-Time Constrained-Deadline Parallel Tasks under GEDF. International Conference on Embedded Software (EMSOFT). Presented at the International Conference on Embedded Software (EMSOFT), Torino, Italy.

Santinelli, L., & Guo, Z. (2018). A Sensitivity Analysis for Mixed Criticality: Trading Criticality with Computational Resource. Presented at the 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA). https://doi.org/10.1109/etfa.2018.8502493

Silvestri, S., Goss, K., Guo, Z., & Bhuiyan, A. (2018). Algorithms CS2500 [Open Educational Resource]. Missouri University of Science and Technology Scholars' Mine Course Materials.

Han, X., Zhao, L., Guo, Z., & Liu, X. (2018). An Improved Speedup Factor for Sporadic Tasks with Constrained Deadlines Under Dynamic Priority Scheduling. Presented at the 2018 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2018.00058

Mao, Y., Green, V., Wang, J., Xiong, H., & Guo, Z. (2018). DRESS: Dynamic RESource-Reservation Scheme for Congested Data-Intensive Computing Platforms. Presented at the 2018 IEEE 11th International Conference on Cloud Computing (CLOUD). https://doi.org/10.1109/cloud.2018.00095

Xiong, H., Cheng, W., Fu, Y., Hu, W., Bian, J., & Guo, Z. (2018). De-biasing Covariance-Regularized Discriminant Analysis. Presented at the Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. https://doi.org/10.24963/ijcai.2018/401

Bhuiyan, A., Guo, Z., Saifullah, A., Guan, N., & Xiong, H. (2018). Energy-Efficient Real-Time Scheduling of DAG Tasks. ACM Transactions on Embedded Computing Systems, 17(5), 1–25. https://doi.org/10.1145/3241049

Guo, Z., & Baruah, S. (2018). Mixed-Criticality Real-Time Systems. https://doi.org/10.1007/978-3-642-54477-4_6-2

Guo, Z., Santinelli, L., & Yang, K. (2018). Mixed-Criticality Scheduling with Limited HI-Criticality Behaviors. https://doi.org/10.1007/978-3-319-99933-3_13

Han, X., & Guo, Z. (2018). Resource Augmentation Bounds of EDF and Partitioned-EDF for Sporadic Tasks with Constrained Deadlines. Real-Time Scheduling Open Problems Seminar (RTSOPS). Presented at the Real-Time Scheduling Open Problems Seminar (RTSOPS), Barcelona, Spain.

Guo, Z., Yang, K., Vaidhun, S., Arefin, S., Das, S. K., & Xiong, H. (2018). Uniprocessor Mixed-Criticality Scheduling with Graceful Degradation by Completion Rate. Presented at the 2018 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2018.00052

Singh, J., Santinelli, L., Guo, Z., Brunel, J., Doose, D., & Infantes, G. (2018). Use of probabilities and formal methods to control system criticality levels. Real-Time Scheduling Open Problems Seminar (RTSOPS). Presented at the Real-Time Scheduling Open Problems Seminar (RTSOPS), Barcelona, Spain.

Sruti, S., Bhuiyan, A. A., & Guo, Z. (2018). Work-in-Progress: Precise Scheduling of Mixed-Criticality Tasks by Varying Processor Speed. Presented at the 2018 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2018.00033

Zhang, Y., Wang, L., Jiang, W., & Guo, Z. (2018). Work-in-Progress: RWS - A Roulette Wheel Scheduler for Preventing Execution Pattern Leakage. Presented at the 2018 IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS). https://doi.org/10.1109/rtas.2018.00016

Xiong, H., Cheng, W., Hu, W., Bian, J., & Guo, Z. (2017). AWDA: An Adaptive Wishart Discriminant Analysis. Presented at the 2017 IEEE International Conference on Data Mining (ICDM). https://doi.org/10.1109/icdm.2017.62

Guo, Z., Bhuiyan, A., Saifullah, A., Guan, N., & Xiong, H. (2017). Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks. Proceedings of the 29th Euromicro Conference on Real-Time Systems (ECRTS). Presented at the 29th Euromicro Conference on Real-Time Systems (ECRTS), Dubrovnik, Croatia.

Guo, Z. (2017). Guaranteeing some service upon mode switch in mixed-criticality systems. In Mixed Criticality on Multicore/Manycore Platforms (Dagstuhl Seminar No. 17131). Retrieved from https://www.ece.ucf.edu/~zsguo/pubs/conference_workshop/Dagstuhl17131.pdf

Yang, Y., Wunsch, D., Guo, Z., & Yin, Y. (2017). Hamiltonian-Driven Adaptive Dynamic Programming Based on Extreme Learning Machine. https://doi.org/10.1007/978-3-319-59072-1_24

Zhang, Z., Guo, Z., & Koutsoukos, X. (2017). Handling write backs in multi-level cache analysis for WCET estimation. Presented at the RTNS '17: 25th International Conference on Real-Time Networks and Systems. https://doi.org/10.1145/3139258.3139269

Zhang, Y., Guo, Z., Wang, L., Xiong, H., & Zhang, Z. (2017). Integrating Cache-Related Preemption Delay into GEDF Analysis for Multiprocessor Scheduling with On-chip Cache. Presented at the 2017 IEEE Trustcom/BigDataSE/ICESS. https://doi.org/10.1109/trustcom/bigdatase/icess.2017.317

Bian, J., Xiong, H., Cheng, W., Hu, W., Guo, Z., & Fu, Y. (2017). Multi-party Sparse Discriminant Learning. Presented at the 2017 IEEE International Conference on Data Mining (ICDM). https://doi.org/10.1109/icdm.2017.86

Xiong, H., Zhang, D., Guo, Z., Chen, G., & Barnes, L. E. (2017). Near-Optimal Incentive Allocation for Piggyback Crowdsensing. IEEE Communications Magazine, 55(6), 120–125. https://doi.org/10.1109/mcom.2017.1600748

Yang, Y., Guo, Z., Wunsch, D., & Yin, Y. (2017). Off-policy reinforcement learning for robust control of discrete-time uncertain linear systems. Presented at the 2017 36th Chinese Control Conference (CCC). https://doi.org/10.23919/chicc.2017.8027737

Santinelli, L., & Guo, Z. (2017). On the Criticality of Probabilistic Worst-Case Execution Time Models. https://doi.org/10.1007/978-3-319-69483-2_4

Guo, Z. (2017). Regarding the Optimality of Speedup Bounds of Mixed-Criticality Schedulability Tests. In Mixed Criticality on Multicore/Manycore Platforms (Dagstuhl Seminar No. 17131).

Vaidhun, S., Arefin, S., Guo, Z., Xiong, H., & Das, S. K. (2017). Response time in mixed-critical pervasive systems. Presented at the 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). https://doi.org/10.1109/uic-atc.2017.8397530

Guo, Z., Sruti, S., Ward, B. C., & Baruah, S. (2017). Sustainability in Mixed-Criticality Scheduling. Presented at the 2017 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2017.00010

Guo, Z., Zhang, Y., Wang, L., & Zhang, Z. (2017). Work-in-Progress: Cache-Aware Partitioned EDF Scheduling for Multi-core Real-Time Systems. Presented at the 2017 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2017.00054

Guo, Z., & Baruah, S. K. (2016). A Neurodynamic Approach for Real-Time Scheduling via Maximizing Piecewise Linear Utility. IEEE Transactions on Neural Networks and Learning Systems, 27(2), 238–248. https://doi.org/10.1109/tnnls.2015.2466612

Cheng, W., Guo, Z., Zhang, X., & Wang, W. (2016). CGC. ACM Transactions on Knowledge Discovery from Data, 10(4), 1–27. https://doi.org/10.1145/2903147

Santinelli, L., Guo, Z., & George, L. (2016). Fault-aware sensitivity analysis for probabilistic real-time systems. Presented at the 2016 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT). https://doi.org/10.1109/dft.2016.7684072

Guo, Z. (2016). Mixed-Criticality Scheduling on Varying-Speed Platforms with Bounded Performance Drop Rate. Presented at the 2016 IEEE International Conference on Smart Computing (SMARTCOMP). https://doi.org/10.1109/smartcomp.2016.7501705

Baruah, S., Easwaran, A., & Guo, Z. (2016). Mixed-criticality scheduling to minimize makespan. Proceedings of the 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS). Presented at the 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS) Leibniz International Proceedings in Informatics, Chennai, India.

Guo, Z. (2016). Real-Time Scheduling of Mixed-Critical Workloads upon Platforms with Uncertainties (Ph.D. Thesis). University of North Carolina-Chapel Hill.

Baruah, S., Burns, A., & Guo, Z. (2016). Scheduling Mixed-Criticality Systems to Guarantee Some Service under All Non-erroneous Behaviors. Presented at the 2016 28th Euromicro Conference on Real-Time Systems (ECRTS). https://doi.org/10.1109/ecrts.2016.12

Guo, Z., Liu, R., Xu, X., & Yang, K. (2015). A Survey of Real-Time Automotive Systems [Department of Computer Science Technical Report]. University of North Carolina at Chapel Hill.

Crowley, J. J., Zhabotynsky, V., Sun, W., Huang, S., Pakatci, I. K., Kim, Y., … Pardo-Manuel de Villena, F. (2015). Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nature Genetics, 47(4), 353–360. https://doi.org/10.1038/ng.3222

Guo, Z., Santinelli, L., & Yang, K. (2015). EDF Schedulability Analysis on Mixed-Criticality Systems with Permitted Failure Probability. Presented at the 2015 IEEE 21st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA). https://doi.org/10.1109/rtcsa.2015.8

Guo, Z. (2015). MC Scheduling on Varying-Speed Processors. In Dagstuhl Reports (Dagstuhl Seminar No. 15121; Vol. 5, pp. 128–129).

Baruah, S., Easwaran, A., & Guo, Z. (2015). MC-Fluid: Simplified and Optimally Quantified. Presented at the 2015 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2015.38

Baruah, S., & Guo, Z. (2015). Mixed-criticality job models: a comparison. Proceedings of the 36th IEEE Real-Time Systems Symposium (RTSS), Workshop on Mixed-Criticality Systems. Presented at the 3rd Workshop on Mixed-Criticality Systems (2015, San Antonio, TX), Workshop on Mixed-Criticality Systems (WMC), San Antonio, Texas, USA.

Guo, Z., & Baruah, S. (2015). The concurrent consideration of uncertainty in WCETs and processor speeds in mixed-criticality systems. Presented at the RTNS '15: 23rd International Conference on Real-Time Networks and Systems. https://doi.org/10.1145/2834848.2834852

Guo, Z., & Baruah, S. K. (2015). Uniprocessor EDF scheduling of AVR task systems. Presented at the ICCPS '15: ACM/IEEE 6th International Conference on Cyber-Physical Systems. https://doi.org/10.1145/2735960.2735976

Cheng, W., Zhang, X., Guo, Z., Shi, Y., & Wang, W. (2014). Graph Regularized Dual Lasso for Robust eQTL Mapping. Proceedings of the 22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB). Presented at the 22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), Boston, MA, USA.

Cheng, W., Zhang, X., Guo, Z., Shi, Y., & Wang, W. (2014). Graph-regularized dual Lasso for robust eQTL mapping. Bioinformatics, 30(12), i139–i148. https://doi.org/10.1093/bioinformatics/btu293

Guo, Z., & Baruah, S. (2014). Implementing mixed-criticality systems upon a preemptive varying-speed processor. Leibniz Transactions on Embedded Systems (LITES), 1(2), 3:1–3:19. https://doi.org/10.4230/LITES-v001-i002-a003

Guo, Z., & Baruah, S. (2014). Mixed-Criticality Scheduling upon Varying-Speed Multiprocessors. Presented at the 2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing (DASC). https://doi.org/10.1109/dasc.2014.50

Baruah, S., & Guo, Z. (2014). Scheduling Mixed-Criticality Implicit-Deadline Sporadic Task Systems upon a Varying-Speed Processor. Presented at the 2014 IEEE Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2014.15

Cheng, W., Zhang, X., Guo, Z., Wu, Y., Sullivan, P. F., & Wang, W. (2013). Flexible and robust co-regularized multi-domain graph clustering. Presented at the KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. https://doi.org/10.1145/2487575.2487582

Baruah, S., & Guo, Z. (2013). Mixed-Criticality Scheduling upon Varying-Speed Processors. Presented at the 2013 IEEE 34th Real-Time Systems Symposium (RTSS). https://doi.org/10.1109/rtss.2013.15

Guo, Z., & Baruah, S. (2013). Mixed-criticality scheduling upon non-monitored varying-speed processors. Presented at the 2013 8th IEEE International Symposium on Industrial Embedded Systems (SIES). https://doi.org/10.1109/sies.2013.6601488

French, A., Guo, Z., & Baruah, S. (2013). Scheduling mixed-criticality workloads upon unreliable processors. The 11th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP). Presented at the 11th Workshop on Models and Algorithms for Planning and Scheduling Problems (MAPSP), Pont a Mousson, France.

Liu, Q., Guo, Z., & Wang, J. (2012). A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 99–109. https://doi.org/10.1016/j.neunet.2011.09.001

Guo, Y., Sun, F., & Guo, Z. (2012). Control Allocation of Flying-Wing with Multi-Effectors Based on T-S Fuzzy Model. In International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-London 2011), Volumes 1–3 (pp. 231–235). https://doi.org/10.1115/1.859810.paper38

Liu, E. Y., Guo, Z., Zhang, X., Jojic, V., & Wang, W. (2012). Metric Learning from Relative Comparisons by Minimizing Squared Residual. Presented at the 2012 IEEE 12th International Conference on Data Mining (ICDM). https://doi.org/10.1109/icdm.2012.38

Guo, Z., Liu, Q., & Wang, J. (2011). A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Subject to Linear Equality Constraints. IEEE Transactions on Neural Networks, 22(12), 1892–1900. https://doi.org/10.1109/tnn.2011.2169682

Guo, Z., & Wang, J. (2011). Information retrieval from large data sets via multiple-winners-take-all. Presented at the 2011 IEEE International Symposium on Circuits and Systems (ISCAS). https://doi.org/10.1109/iscas.2011.5938154

Guo, Z., & Wang, J. (2010). A neurodynamic optimization approach to constrained sparsity maximization based on alternative objective functions. Presented at the 2010 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/ijcnn.2010.5596553

Wang, J., & Guo, Z. (2010). Parametric Sensitivity and Scalability of k-Winners-Take-All Networks with a Single State Variable and Infinity-Gain Activation Functions. In L. Zhang, B. L. Lu, & J. Kwok (Eds.), Advances in Neural Networks - ISNN 2010. https://doi.org/10.1007/978-3-642-13278-0_11

Guo, Z., Lu, L., Xi, S., & Sun, F. (2009). An Effective Dimension Reduction Approach to Chinese Document Classification Using Genetic Algorithm. https://doi.org/10.1007/978-3-642-01510-6_55

Guo, Z. (2009). Fault-Tolerant Control Allocation of Unmanned Flying-Wings Flight Vehicles (Honors Undergraduate Thesis). Tsinghua University.

Liang, Y., Liu, X., Wang, Z., Li, J., Cao, B., Cao, Z., … Zhang, Y. (2008). THU and ICRC at TRECVID 2008. National Institute of Standards and Technology.

Yuan, J., Guo, Z., Lv, L., Wan, W., Zhang, T., Wang, D., … Zhang, Y. (2007). THU and ICRC at TRECVID 2007. National Institute of Standards and Technology.

Xu, W., & Guo, Z. (2004). Three-failure match. Mathematics in Practice and Theory, 34(11), 14–19.

Guo, Z. A Neurodynamic Optimization Approach to Constrained Pseudoconvex Optimization (Masters thesis). Chinese University of Hong Kong.