Publications
The update-to-date publication list can be found at my Google Scholar.
Conference Papers
S. Awine and J. Liu, "Topology-Aware Multi-Agent Reinforcement Learning for Efficient Resource Allocation in Cloud-Native Stream Processing," In Proc. of 19th IEEE International Conference on Cloud Computing (IEEE CLOUD), July 13-18, Sydney, Australia, 2026. [Accepted] [Acceptance Rate: 23%]
K. Kiros and J. Liu, "Regime-Aware Resource Demand Forecasting for Cloud Scheduling: When History Beats ML and When ML Matters," short paper, In Proc. of 19th IEEE International Conference on Cloud Computing (IEEE CLOUD), July 13-18, Sydney, Australia, 2026. [Accepted]
Y. Parra Bautista, M. Erdell, C. Theran, N. Mateeva, R. Alo, and J. Liu, "AI-Driven Sustainability in Data Centers: A Multitudinal Evaluation of Environmental Efficiency, Renewable Energy Integration, and Inclusive Growth Scores," In Proc. of the 24th LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI), July 15-17, 2026. [Accepted]
S. Awine and J. Liu, "Online Uncertainty-Aware Hierarchical Scheduling for Heterogeneous Cloud Workloads Using Deep Reinforcement Learning," In Proc. of IEEE International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), 2026. [Accepted]
J. Liu, S. Awine, and R. Gong, "Online Adaptive Resource Allocation for Dynamic Stream Processing in Cloud Environments using Deep Reinforcement Learning," In Proc. of IEEE International Conference on Communications (ICC), May 24-28, Glasgow, Scotland, UK, 2026. [Accepted]
S. Awine, J. Liu, R. Alo, Y. Parra Bautista, and C. Theran-Suares, "Adaptive Scheduling of Digital Twin Workloads Using Topology-Aware Reinforcement Learning in High-Performance Computing," In DT4HS 2026, January 20-21, Houston, 2026. [Poster Paper]
R. Gong and J. Liu, "Applying ML for Mediation Analysis between Residential Segregation and Mortality Rates," In Proc. of IEEE Symposium on Computer Applications & Industrial Electronics (IEEE ISCAIE), April 25-26, Parkroyal Penang, Penang Island, 2026. [Accepted]
J. Liu, K. Kiros, R. Gong, and C. Yedjou, "An Explainable ML-based Approach to Predicting Virtual Machine Resource Demand for High Resource Utilization in Clouds," In Proc. of 12th Annual Conference on Computational Science and Computational Intelligence (CSCI), December 3-5, 2025. [Paper]
J. Liu, R. Gong, R. A. Alo, W. Dai, R. A. Long, and P. Ngnepieba, "Falcon: An Efficient Dependency-Aware Scheduling for High Throughput and Resource Utilization in Clouds," In Proc. of 2025 IEEE World Forum on Public Safety Technology (WF-PST), September 23-25, Orlando, 2025.
J. Liu, "DeepInspect: A Novel ML-based Approach to Identify COVID-19 Vaccine Disparities and Determinants for Improving Pandemic Health Care," In Proc. of the International Medicine and Biosciences Conference 2025 (TIMBC 2025), November 6-8, Dubai, 2025. [Abstract Paper Accepted]
R. Gong and J. Liu, "MLM: Using ML to Handle Missing Values in Residential Segregation and Mortality Rates for Association Analysis," In Proc. of the 11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), December 16-19, Sharjah, 2024.
R. Gong, J. Liu, and M. Zhao, "Comparison of Segregation Indexes and Residential Segregation for Mortality Analysis," In Proc. of ICECER, December 4-6, Gaborone, 2024.
J. Liu, "CMIDiscover: An ML-based Approach to Detect COVID-19 Misinformation on Social Media for Reducing Public Health Risk," In Proc. of ISCAI, 2024. [Abstract Paper Accepted]
J. Liu, R. Gong, W. Dai, C. Kolog, S. Awine, and J. Carter, "DeepInspect: Identifying COVID-19 Vaccine Disparities and Determinants for Improving Health Equity," In Proc. of Healthcare Insights, 2025. [Abstract Paper Accepted]
J. Liu and R. Gong, "AIM: Using AI to Improve Residential Racial and Economic Segregation for Mortality Analysis," In Proc. of 2024 IEEE World Forum on Public Safety Technology (WF-PST), Washington, D.C., 2024. [Paper]
W. Dai, R. Zhang, and J. Liu, "P-TimeSync: A Precise Time Synchronization Simulation with Network Propagation Delays," In Proc. of 2024 IEEE World Forum on Public Safety Technology (WF-PST), Washington, D.C., 2024.
J. Liu, R. Gong, C. Kolog, C. Yedjou, J. Nam-Speers, L. Cheng, and W. Dai, "EqualDig: Mitigating Digital Inequality for Improving AI Education at Minority-Serving Institutions," In AAAI 2024 Spring Symposium, Stanford University, Stanford, California, 2024.
J. Liu, C. Yedjou, and J. Deng, "VISUAL-Learning: Developing a Cloud-Based VISUAL Simulator for Enhancing STEM Students’ AI Learning Experience," In AAAI 2024 Spring Symposium, Stanford University, Stanford, California, 2024.
J. Liu, Y. Lao, Y. Mao, and R. Buyya, "Sailfish: A Dependency-Aware and Resource Efficient Scheduling for Low Latency in Clouds", In Proc. of IEEE Big Data, Sorrento, 2023. [Paper]
A. D'Onofrio Jr., A. Hossain, L. Santana, N. Machlovi, S. Stein, J. Liu, A. Li, and Y. Mao, "Distributed Quantum Learning with co-Management in a Multi-tenant Quantum System", In Proc. of IEEE Big Data, Sorrento, 2023. J. Liu, R. Gong, W. Dai, W. Zheng, Y. Mao, W. Zhou, and F. Deng, "HCoop: A Cooperative and Hybrid Resource Scheduling for Heterogeneous Jobs in Clouds", In Proc. of IEEE CloudCom. [Paper] J. Liu, R. Alo, R. Gong, and Y. Mao, "Hobby: An Efficient Dependency-Aware Scheduling for High Throughput in Clouds", In Proc. of IEEE LATINCOM, 2023. J. Liu, R. Gong, L. Cheng, and R. Alo, "DeepHealth: Geospatial and ML-based Approach to Identify Health Disparities and Determinants for Improving Pandemic Health Care", In Proc. of IEEE ICCCN, Honolulu, 2023. [Paper] J. Liu, R. Gong, and W. Zhou, "SmartEye: Detecting COVID-19 Misinformation on Twitter for Mitigating Public Health Risk", In Proc. of IEEE BigComp, 2023. J. Deng, Y. Ding, L. Achenie, J. Liu, S. Pan, S. Purushotham, H. Wu, and Q. Wang, "International Workshop on Digital Twins for Smart Health", WWW'23 Companion: Companion Proceedings of the ACM Web Conference 2023, 2023. J. Liu, X. Zhang, R. Alo, X. Huang, L. Cheng, and F. Deng, "CrossCas: A Novel Cross-Platform Approach for Predicting Cascades in Online Social Networks with Hidden Markov Model", In Proc. of the 2022 IEEE Global Communications Conference (GLOBECOM), December 4-8, 2022. [Paper] J. Liu, "Fregata: A Low-Latency and Resource-Efficient Scheduling for Heterogeneous Jobs in Clouds", In Proc. of IEEE BigComp, Daegu, Korea, 2022. [Acceptance Rate: 25%] J. Liu, R. Alo, Y. J. Parra Bautista, C. Yedjou, and C. Theran, "A Geospatial and ML-based Approach to Health Disparity Identification and Determinant Tracing for Improving Pandemic Health Care", In Proc. of SNAMS, Gandia, 2021. [Best Paper Award] J. Liu, L. Cheng, A. Sarker, L. Yan, and R. Alo, "DeepTrack: An ML-based Approach to Health Disparity Identification and Determinant Tracking for Improving Pandemic Health Care", In Proc. of IEEE Big Data, Orlando, 2021. J. Liu, L. Cheng, H. Chi, C. Liu, and R. Alo, "CDetector: Extracting Textual Features of Financial Social Media to Detect Cyber Attacks", In Proc. of IEEE International Conference on Computer Communications and Networks (ICCCN), pp. 1-6, 2021. J. Liu and L. Cheng, "SwiftS: A Dependency-Aware and Resource Efficient Scheduling for High Throughput in Clouds", In Proc. of IEEE International Conference on Computer Communications (INFOCOM), 2021. DOI: 10.1109/INFOCOMWKSHPS51825.2021.9484459 J. Liu, R. Alo, and C. Liu, "Examining Textual Features of Financial Social Media to Detect Cyber Attacks", In Proc. of ICCAIS, March 18-20, 2021. J. Liu, R. Alo, and Y. J. Parra Bautista, "DeepTrace: Improving Pandemic Health Care by Identifying Disparities and Determinants", In Proc. of IEEE BigComp, Jeju Island, Korea, 2021. Y. J. Parra Bautista, J. Liu, and R. Alo, "Behavior Analysis of Pandemic Source Media Communications", In Proc. of IEEE BigComp, Jeju Island, Korea, 2021. J. Liu, L. Cheng, and H. Chi, "DeepDive: Examining Determinants of Health Disparities in COVID-19 for Improving Pandemic Health Care", In Proc. of ACM ICVISP, Bangkok Thailand, 2020. J. Carter, H. S. Narman, O. Cosgun, and J. Liu, "Trade-off Model of Fog-Cloud Computing for Space Information Networks", In Proc. of IEEE Cloud Summit, 2020. J. Liu, R. Alo, and Y. J. Parra Bautista, "DeepTrace: Improving US Pandemic Health Care through Health Disparity Identification and Determinant Tracing", In Proc. of International Conference on Intelligent Data Science Technologies and Applications (IDSTA), Valencia, Spain, 2020. W. Chung, E. Mustaine, J. Liu, and M. Vora, "A Theory-Driven Framework for Modeling Temporal Online Social Networks of GitHub", In Proc. of the Americas Conference on Information Systems (AMCIS), August 15-17, 2019. W. Chung, M. Vora, J. Liu, Y. Huang, E. Mustaine, and V. S. Lai, "Simulating Temporal Dynamics in Cryptocurrency Software Social Networks", In Proc. of the Americas Conference on Information Systems (AMCIS), August 15-17, 2019. J. Liu, W. Chung, Y. Huang and C. Toraman, "CrossSimON: A Novel Probabilistic Approach to Cross-Platform Online Social Network Simulation", In Proc. of the 17th IEEE International Conference on Intelligence and Security Informatics (ISI), July 1-3, 2019. [Paper] W. Chung, C. Toraman, Y. Huang, M. Vora, and J. Liu, "A Deep Learning Approach to Modeling Temporal Social Networks on Reddit", In Proc. of the 17th IEEE International Conference on Intelligence and Security Informatics (ISI), July 1-3, 2019. H. S. Narman, A. D. Uulu, and J. Liu, "Profile Analysis for Cryptocurrency in Social Media", In Proc. of IEEE ISSPIT, Louisville, 2018. W. Chung, J. Liu, X. Tang, and V. Lai, "Extracting Textual Features of Financial Social Media to Detect Cognitive Hacking", In Proc. of IEEE ISI, Miami, 2018. J. Liu, H. Shen, A. Sarker, and W. Chung, "Leveraging Dependency in Scheduling and Preemption for High Throughput in Data-Parallel Clusters", In Proc. of the 2018 IEEE International Conference on Cluster Computing (Cluster’18), September 10-13, Belfast, United Kingdom, 2018. [Paper] J. Liu, W. Chung, X. Tang, and V. Lai, "Identifying Cyber Threats from Financial Social Media: A Hybrid Feature Selection Approach", 2018 Research Symposium, Tampa, 2018. J. Liu, H. Shen, and H. Hu, "Load-aware and Congestion-free State Management in Network Function Virtualization", In Proc. of ICNC, Silicon Valley, 2017. J. Liu and H. Shen, "A Popularity-aware Cost-effective Replication Scheme for High Data Durability in Cloud Storage", In Proc. of IEEE Big Data, Washington D.C., 2016. [Paper] J. Liu, H. Shen, and H. S. Narman, "CCRP: Customized Cooperative Resource Provisioning for High Resource Utilization in Clouds", In Proc. of IEEE Big Data, Washington D.C., 2016. [Paper] J. Liu and H. Shen, "Dependency-aware and Resource-efficient Scheduling for Heterogeneous Jobs in Clouds", In Proc. of IEEE CloudCom, Luxembourg, 2016. [Paper] J. Liu and H. Shen, "A Low-Cost Multi-Failure Resilient Replication Scheme for High Data Availability in Cloud Storage", In Proc. of 23rd Annual International Conference on High Performance Computing, Data, and Analytics (HiPC), Hyderabad, 2016. [Acceptance Rate: 25%] [Paper] J. Liu, H. Shen, and L. Chen, "CORP: Cooperative Opportunistic Resource Provisioning for Short-Lived Jobs in Cloud Systems", In Proc. of IEEE CLUSTER, Taipei, 2016. [Paper] J. Liu, H. Shen and X. Zhang, "A Survey of Mobile Crowdsensing Techniques: A Critical Component for The Internet of Things", In Proc. of IEEE International Conference on Computer Communication and Networks (ICCCN), pp. 1-6, 2016. [Paper] J. Liu, L. Yu, H. Shen, Y. He, and J. Hallstrom, "Characterizing Data Deliverability of Greedy Routing in Wireless Sensor Networks", In Proc. of IEEE SECON, Seattle, 2015. [Paper]Journal Papers
C. G. Yedjou, K. Makoudjou, M. Ochapa, J. Liu, S. Messeha, and P. B. Tchounwou, "AI-Enhanced Assessment of Lipid Profiling in Commercial Baby Foods in the United States", Journal of Nutrition & Food Sciences, 2026.
C. G. Yedjou, R. Long, V. Eno, J. Liu, S. B. Smith, P. Ngnepieba, K. Densu, M. MsCallister, L. Latinwo, and P. B. Tchounwou, "COVID-19 Prevalence in Nations with Normal Body Mass Index (BMI): Implications of Artificial Intelligence (AI) in Healthcare", Journal of Nutrition & Food Sciences, 15(1), 1-7, 2025.
E. Katsoulakis, Q. Wang, H. Wu, L. Shahriyari, R. Fletcher, J. Liu, L. Achenie, H. Liu, P. Jackson, Y. Xiao, T. Syeda-Mahmood, R. Tuli, and J. Deng, "Digital Twins for Health: A Scoping Review", NPJ Digital Medicine, 7(1):77, 2024. DOI: 10.1038/s41746-024-01073-0. Impact Factor: 15.2 [Top-tier Journal] [Paper]
A. Zhang, Q. Liu, J. Liu, and L. Cheng, "CASA: Cost-effective EV Charging Scheduling based on Deep Reinforcement Learning", Neural Computing and Applications, 36, 8355–8370, 2024.
J. Li, Z. Jiang, Z. Chen, J. Liu, and C. Long, "CuEMS: Deep Reinforcement Learning for Community Control of Energy Management Systems in Microgrids", Energy and Buildings, 304 (2024): 113865.
C. Yedjou, S. Webster, D. Osborne, J. Liu, Y. Balagurunathan, C. Odewuni, L. Latinwo, P. Ngnepiepa, R. Alo, P. Tchounwou, "Health Promotion and Racial Disparity in COVID-19 Mortality Among African American Populations", Reports on global health research, 6(3):168, 2023. DOI: 10.29011/2690-9480.100168.
R. Gong and J. Liu, "Application of Machine Learning to Mortality Modelings during the Pandemic in the U.S.A.", Journal of Statistics and Computer Science, 2(1):12-27, 2023.
R. Gong and J. Liu, "Announcement Effects of Capital Increases during the 2008 Global Financial Crisis", Journal of Econometrics and Statistics, 3(1), 17-36, 2023.
R. Gong, J. Chan, and J. Liu, "A Short Note on Comparing Bayesian Density Estimation with Univariate Kernel Density Estimation", Asian J. Math. Appl., 2023:1, 2023.
J. Li, X. Tong, J. Liu, and L. Cheng, "An efficient Federated Learning System for Network Intrusion Detection", IEEE Systems Journal, 17(2), 2455-2464, 2023.
H. Chi, J. Liu, W. Xu, M. Peng, and J. deGoicoechea, "Design Hands-on Lab Exercises for Cyber-physical Systems Security Education", Journal of The Colloquium for Information Systems Security Education, 9(1), 1-8, 2022.
J. Liu, H. Shen, H. Chi, H. Narman, Y. Yang, L. Cheng, and W. Chung, "A Low-Cost Multi-Failure Resilient Replication Scheme for High-Data Availability in Cloud Storage", IEEE/ACM Transactions on Networking (TON), 29(4), 1436-1451, 2021. [Top Journal in the Field of Communication Networks] [Paper]
C. Yedjou, R. Alo, J. Liu, J. Enow, P. Ngnepiepa, R. Long, L. Latinwo, and P. B. Tchounwou, "Chemo-Preventive Effect of Vegetables and Fruits Consumption on the COVID-19 Pandemic", Journal of Nutrition & Food Sciences, 4(2), 1-22, 2021.
H. Chi, M. Ghaffari, A. Srinivasan, and J. Liu, "Development of Cybersecurity Lab Exercises for Mobile Health", Journal of The Colloquium for Information Systems Security Education, 7(1), 1-6, 2020.
X. Chen, L. Cheng, C. Liu, Q. Liu, J. Liu, Y. Mao, and J. Murphy, "A WOA-Based Optimization Approach for Task Scheduling in Cloud Computing Systems", IEEE Systems Journal, 14(3), 3117-3128, 2020.
J. Liu, H. Shen, and H. S. Narman, "Popularity-Aware Multi-Failure Resilient and Cost-Effective Replication for High Data Durability in Cloud Storage", IEEE Transactions on Parallel and Distributed Systems (TPDS), 30(10), 2355-2369, 2019. [Paper]
J. Liu, H. Shen, H. S. Narman, W. Chung, and Z. Lin, "A Survey of Mobile Crowdsensing Techniques: A Critical Component for The Internet of Things", ACM Transactions on Cyber-Physical Systems (TCPS), 2(3), 18:1-26, 2018. [Paper]
J. Liu, H. Shen, L. Yu, H. S. Narman, J. Zhai, J. Hallstrom, and Y. He, "Characterizing Data Deliverability of Greedy Routing in Wireless Sensor Networks", IEEE Transactions on Mobile Computing (TMC), 17(3), 543-559, 2018. [Paper]
J. Liu, H. Shen, and L. Yu, "Question Quality Analysis and Prediction in Community Question Answering Services with Coupled Mutual Reinforcement", IEEE Transactions on Services Computing (TSC), 10(2), 286-301, 2017. [Paper]
Y. Xu, P. Tang, and J. Liu, "Resource Scheduling Algorithm Based on Multi-target Balance in Enterprise Gloud Storage System", Journal of Theoretical and Applied Information Technology, 48(3):1578-1583, 2013. H. Shen, Z. Li, J. Liu, and J. Grant, "Knowledge Sharing in the Online Social Network of Yahoo! Answers and Its Implications", IEEE Transactions on Computers (TC), 64(6):1715-1728, 2015. H. Shen, J. Liu, K. Chen, J. Liu, and S. Moyer, "SCPS: A Social-Aware Distributed Cyber-Physical Human-Centric Search Engine", IEEE Transactions on Computers (TC), 64(2):518-532, 2015. 