1. F. Yu, S. Maharjan, L. Kerns, X. Min, A. Arslanyilmaz, and M. Zhu, "AQPrius: Offline Approximate Query Processing Enhanced by Error Assessment using Bootstrap Sampling", International Journal of Computer Science and Security (IJCSS) 2024.
2. M. Y. Shakor, M. I. Khaleel, M. Safran, S. Alfarhood and M. Zhu, "Dynamic AES Encryption and Blockchain Key Management: A Novel Solution for Cloud Data Security," in IEEE Access, doi: 10.1109/ACCESS.2024.3351119, 2024.
3. A. Prasad, P. Lal, B. Wolde, M. Zhu, B. K. Samanthula, and N. Panorkou, "Examining the impact of a field trip in nature on students’ environmental perceptions and feelings of empowerment: a case study from the ACMES STEM Summer Camp", Journal of STEM Education: Innovations and Research 2023.
4. K. M. Ibrahim, M. Safran, S. Alfarhood, and M. Zhu, "Workflow Scheduling Scheme for Optimized Reliability and End-to-End Delay Control in Cloud Computing Using AI-Based Modeling", Mathematics, vol. 11, no. 20: 4334, 2023. https://doi.org/10.3390/math11204334.
5. W. Welling, Y. Sheng, and M. Zhu, "CUDA-Aware MPI Implementation of Gibbs Sampling for an IRT Model", Cluster Computing 2023. https://rdcu.be/ddU9v.
6. A. Hou, C. Wu, Q. Duan, D. Quan, L. Zuo, Y. Li, M. Zhu and D. Fang. "SDN-based bandwidth scheduling for prioritized data transfer between data centers", Cluster Computing 2021. https://doi.org/10.1007/s10586-021-03364-7.
7. W. Wang, C. Coutras, and M. Zhu. "Empowering computing students with proficiency in robotics via situated learning", Smart Learn. Environ., vol. 8, 24, 2021. https://doi.org/10.1186/s40561-021-00167-6.
8. A. Al-Sinayyid and M. Zhu. "Job Scheduler for Streaming Applications in Heterogeneous Distributed Processing Systems", The Journal of Supercomputing Springer, DOI: 10.1007/s11227-020-03223-z, 2020. Impact factor 2.157.
9. A. Hou, C. Wu, R. Qiao, L. Zuo, M. Zhu, D. Fang, W. Nie, F. Chen. "QoS Provisioning for Various Types of Deadline-Constrained Bulk Data Transfers between Data Centers", Future Generation Computer Systems Elsevier, vol. 105, pp. 162~174, 2020.
10. E. Wang, D. Li, B. Dong, H. Zhou and M. Zhu. "Flat and Hierarchical System Deployment for Edge Computing System", Future Generation Computer Systems Elsevier, vol. 105, pp. 308~317, 2020.
10. E. Wang, D. Li, B. Dong, H. Zhou, and M. Zhu, "Flat and Hierarchical System Deployment for Edge Computing System", Future Generation Computer Systems, Elsevier, vol. 105, pp. 308~317, 2020.
11. A. Hou, C. Wu, R. Qiao, L. Zuo, M. Zhu, D. Fang, W. Nie, and F. Chen, "QoS Provisioning for Various Types of Deadline-Constrained Bulk Data Transfers between Data Centers", Future Generation Computer Systems, Elsevier, vol. 105, pp. 162~174, 2020.
12. D. Basu, N. Panorkou, M. Zhu, P. Lal, & B. Samanthula, "Exploring the Mathematics of Gravity", Mathematics Teacher: Learning and Teaching PK-12, MTLT, 113(1), pp. 39-46, 2020. https://pubs.nctm.org/view/journals/mtlt/113/1/article-p39.xml.
13. L. Zuo, M. Zhu, C. Wu, and Bin Tang, "Bandwidth Reservation Strategies for Throughput Maximization in Dedicated Networks", IEEE Transactions on Network and Service Management (TNSM), vol. 15, issue 2, pp. 544~554, 2018.
14. D. Yun, C. Wu, and M. Zhu, "Transport-Support Workflow Composition and Optimization for Big Data Movement in High-performance Networks", IEEE Transactions on Parallel and Distributed Systems, vol. 28, no. 12, pp. 3656-3670, December 2017.
15. L. Zuo, M. Zhu, C. Wu, and J. Zurawski, "Fault-tolerant Bandwidth Reservation Strategies for Data Transfers in High-performance Networks", Computer Networks, COMNET Elsevier, vol. 113, pp. 1~16, 2017.
16. M. D. Brazley and M. Zhu, "Cyberlearning: Enhancing 3D Spatial Skills: While Reducing the Gender Gap", Journal of Teaching and Education (JTE), vol. 5, no. 1, pp. 395~410, 2016.
17. L. Zuo and M. Zhu, "Concurrent Bandwidth Reservation Strategies for Big Data Transfer Requests in High-Performance Networks", IEEE Transactions on Network and Service Management (TNSM), vol. 12, no. 2, pp. 232~247, June 2015.
18. L. Zuo, M. Zhu, and C. Wu, "Concurrent bandwidth scheduling for big data transfer over a dedicated channel", International Journal of Communication Networks and Distributed Systems (IJCNDS), vol. 15, no. 2/3, pp. 169~190, 2015.
19. L. Zuo, M. Zhu, and C. Wu, "Fast and Efficient Bandwidth Reservation Algorithms for Dynamic Network Provisioning", Journal of the Network and Systems Management, Springer, vol. 23, no. 3, pp. 420-444, July 2015.
20. F. Cao and M. Zhu, "Decentralized Hybrid Workflow Scheduling Algorithm for Minimum End-to-end Delay in Heterogeneous Computing Environment", International Journal of High Performance Computing and Networking, vol. 8, no. 4, pp. 324~336, 2014.
21. M. Khaleel and M. Zhu, "Energy-efficient Task Scheduling and Consolidation Algorithm for Workflow Jobs in Cloud", International Journal of Computational Science and Engineering, vol. 13, no. 3, pp. 268~284, 2014.
22. Y. Sheng, W. Welling, and M. Zhu, "A GPU-based Gibbs sampler for a unidimensional IRT model", International Scholarly Research Notices in Computational Mathematics, vol. 2014, Article ID 368149, 11 pages. http://dx.doi.org/10.1155/2014/368149.
23. M. Zhu, F. Cao, and C. Wu, "High-through Scientific Workflow Scheduling for Cloud", Journal of Communication Special Issue on Big data and Cloud Computing, vol. 9, no. 4, pp. 312~321. http://www.jocm.us/uploadfile/2014/0429/20140429045159380.pdf, 2014.
24. M. Khaleel, M. Zhu, D. Che, and W. Hou, "A Cooperative Game Theory-based Approach for Energy-Aware Job Scheduling in Cloud", International Journal of Computers and Their Applications, vol. 20, no. 4, pp. 221~235, 2013.
25. D. Ding, F. Cao, D. Che, M. Zhu, and Wen-Chi Hou, "Budget Constrained Dataflow Scheduling for Minimized Completion Time on the Cloud", International Journal of Computers and Their Applications, vol. 20, no. 4, pp. 208~220, 2013.
26. J. Yuan, M. Zhu, K. Meksem, M. Geisler, P. Hart, and D. A. Lightfoot, "Transcript Abundance Responses of Resistance Pathways of Arabidopsis thaliana to Deoxynivalenol", Atlas Journal of Biology, vol. 2, pp. 154~161, 2013.
27. F. Cao and M. Zhu, "Distributed Workflow Mapping Algorithm for Maximized Reliability under End-to-end Delay Constraint", Journal of Supercomputing, Springer, vol. 66, no. 3, pp. 1462~1488, Dec. 2013.
28. F. Mumba and M. Zhu, "Interactive Virtual Classroom System using Google App Engine", Journal of Computers in Mathematics and Science Teaching, vol. 32, no. 2, pp. 195~217, 2013.
29. Q. Wu, M. Zhu, Y. Gu, P. Brown, X. Lu, W. Lin, and Y. Liu, "A Distributed Workflow Management System with Case Study of Real-life Scientific Applications on Grids", Journal of Grid Computing, vol. 10, no. 3, pp. 367~393, 2012.
30. M. Zhu, Guangxing Wang, and Tonny Oyana, "Parallel Spatiotemporal Autocorrelation and Visualization System for Large-scale Remotely Sensed Images", Journal of Supercomputing, Springer, vol. 59, no. 1, pp. 83~103, 2012.
31. J. Wang and M. Zhu, "Parallel Multiple Sequences Alignment with Maximum Likelihood-based Tree Construction Inference", International Journal of Computational Biology and Drug Design, vol. 3, no. 3, pp. 226~236, Jan. 2011.
32. M. Zhu, S. Ding, Q. Wu, R. R. Brooks, N. S.V. Rao, and S. S. Iyengar, "Fusion of Threshold Rules for Target Detection in Wireless Sensor Networks", ACM Transactions on Sensor Networks, vol. 6, no. 2, Article 18, pp. 18~23, February 2010.
33. Q. Wu, M. Zhu, Y. Gu, and N.S.V. Rao, "System Design and Algorithmic Development for Computational Steering in Distributed Environments", IEEE Transactions on Parallel and Distributed Systems, vol. 21, no. 4, pp. 438~451, April 2010.
34. X. Cao and M. Zhu, "A parallel approach toward correlation measurement for gene pairs with time-lagging expression behaviors", International Journal of Computational Biology and Drug Design, vol. 2, no. 3, pp. 274~283, 2009.
35. M. Zhu and R. R. Brooks, "Comparison of Petri Net and Finite State Machine Discrete Event Control of Distributed Surveillance Networks", International Journal of Distributed Sensor Networks, Taylor & Francis, vol. 5, no. 5, pp. 480~501, 2009.
36. Y. Gu, Q. Wu, M. Zhu, and N.S.V. Rao, "Complexity Analysis of Pipeline Mapping Problems in Distributed Heterogeneous Networks", International Journal of Distributed Sensor Networks, vol. 5, no. 1, 2009.
37. Y. Lin, Q. Wu, N. S.V. Rao, and M. Zhu, "Advance Bandwidth Scheduling Algorithms in Dedicated Networks", International Journal of Distributed Sensor Networks, vol. 5, no. 1, 2009.
38. Q. Wu, J. Gao, Z. Chen, and M. Zhu, "Pipelining Parallel Image Compositing and Delivery for Efficient Remote Visualization", Journal of Parallel and Distributed Computing (JPDC), Elsevier, vol. 69, no. 3, pp. 230~238, 2009.
39. Q. Wu, M. Zhu, and N.S.V. Rao, "Integration of Sensing and Computing in an Intelligent Decision Support System for Homeland Security Defense", Pervasive and Mobile Computing Journal, vol. 5, no. 2, pp. 182~200, April 2009.
40. Y. Yang, M. Zhu, L. Wu, and J. Zhou, "Assessment of Data Processing to Improve Reliability of Microarray Experiments Using Genomic DNA Reference", BMC Genomics, 9(Suppl 2):S5. DOI: https://doi.org/10.1186/1471-2164-9-S2-S5, 2008.
41. J. Yuan, M. Zhu, D. A. Lightfoot, M. J. Iqbal, and K. Meksem, "In silico Comparison of Transcript Abundances During Arabidopsis thaliana and Glycine max Resistance to Fusarium virguliforme", BMC Genomics, 9(Suppl 2)
42. M. Xu, M. Zhu, and L. Zhang. "A Stable Iterative Method for Refining Discriminative Gene Clusters." BMC Genomics, 9(Suppl 2):S18. DOI: https://doi.org/10.1186/1471-2164-9-S2-S18, 2008.
43. M. Zhu and Q. Wu. "A Parallel Computing Approach to Decipher Transcription Network for Large-scale Microarray Datasets." BMC Genomics, 9(Suppl 1):S5. DOI: https://doi.org/10.1186/1471-2164-9-S1-S5, 2008.
44. Q. Wu, J. Gao, M. Zhu, N.S.V. Rao, J. Huang, and S.S. Iyengar. "Self-Adaptive Configuration of Visualization Pipeline Over Wide-Area Networks." IEEE Transactions on Computers, vol. 57, no. 1, pp. 55~68, January 2008.
45. M. Zhu, Q. Wu, N.S.V. Rao, and S. S. Iyengar. "Optimal Pipeline Decomposition and Adaptive Network Mapping to Support Distributed Remote Visualization." Journal of Parallel and Distributed Computing (JPDC), Elsevier, vol. 67, no. 8, pp. 947~956, 2007.
46. R. Meyer, J. Yuan, J. Afzal, J. Iqbal, M. Zhu, G. Garvey, and D. A. Lightfoot. "Identification of Gsr1: A locus inferred to regulate gene expression in response to exogenous glutamine." Euphytica, vol. 151, no. 3, pp. 291~302, October 2006.
47. N.S.V. Rao, S. M Carter, Q. Wu, W. R Wing, M. Zhu. A. Mezzacappa, M. Veeraraghavan, and J. M Blondin. "Networking for large-scale science: infrastructure, provisioning, transport and application mapping." Journal of Physics: Conference Series, vol. 16, pp. 541~545, June 2005.
48. X. Zheng, M. Veeraraghavan, N.S.V. Rao, Q. Wu, and M. Zhu. "CHEETAH: Circuit-switched High-speed End-to-End Transport Architecture testbed." IEEE Communications Magazine, vol. 43, no. 8, pp. 11~17, August 2005.
49. R.R. Brooks, M. Zhu, J. Lamb, and S.S. Iyengar. "Aspect-oriented design of sensor networks." Journal of Parallel and Distributed Computing (JPDC), Elsevier, vol. 64, no. 7, pp. 853~865, July 2004.
50. Q. Wu, S.S. Iyengar, and M. Zhu. "Web image retrieval using self-organizing feature map." Journal of the American Society for Information Science and Technology, vol. 52, no. 10, pp. 868~875, August 2001.
51. L. Zuo and M. Zhu, "Big Data and Computational Intelligence in Networking", in Big Data and Computational Intelligence in Networking, Edited by Y. Wu, F. Hu, G. Min, and A. Zomaya, Taylor & Francis LLC, CRC Press, 2016.
52. F. Cao and M. Zhu, "Green Cloud Computing with Efficient Resource Allocation Approach", in Engineer and Optimize Services for the Green Era, Chapter 21, Edited by Dr. Xiaodong Liu and Dr. Yang Li, IGI Global, 2015.
53. R. R. Brooks, M. Pirretti, J. Lamb, M. Zhu, and S. S. Iyengar. Self-Configuration, Distributed Sensor Networks, Second Edition, Sensor Networking and Applications, Edited by S. Sitharama Iyengar and Richard R. Brooks, Chapter 27 pp. 577–620, Published by Chapman and Hall/CRC, 2012.
54. M. Zhu, S. S. Iyengar, J. Lamb, R. R. Brooks, and M. Pirretti, System Control Example DSN Control Hierarchy, Distributed Sensor Networks, Second Edition, Sensor Networking and Applications, Edited by S. Sitharama Iyengar and Richard R. Brooks, Chapter 32 pp. 713-746, Published by Chapman and Hall/CRC, 2012.
55. M. Zhu, R.R. Brooks, S. Ding, Q. Wu, N.S.V. Rao, and S.S. Iyengar. Chebyshev's Inequality-based Multi-Sensor Data Fusion in Self-organizing Sensor Networks, Frontiers in Distributed Sensor Networks Second Edition, Chapter 26, R. R. Brooks and S. S. Iyengar (editors), Chapman and Hall Inc, 2011.
56. Q. Wu, M. Zhu, N. S.V. Rao, R. R. Brooks, S. S. Iyengar, and M. Meng. An integrated intelligent decision support system based on sensor and computer networks. System of Systems – Principles and Applications, Mo Jamshidi (editor), Taylor & Francis Group LLC, pp. 279-315, 2008.
57. R.R. Brooks, M. Zhu, M. Piretti, C. Griffin and S.S. Iyengar, Emergent routing and resource discovery, Disruptive Security Technologies with Mobile Code and Peer-to-Peer Networks, Chapter 11, pp. 283-305, R.R. Brooks (editor), CRC Press 2005.
58. Q. Wu, N.S.V. Rao, R.R. Brooks, S.S. Iyengar, and M. Zhu. On computational and networking problems in distributed sensor networks. Handbook of Sensor Networks: Compact Wireless and Wired Sensing Systems, M. Ilyas and I. Mahgoub (editors), CRC Press LLC, pp. 25.1-25.16, August 2004.
59. M. Zhu, R.R. Brooks, M. Pirretti, and S.S. Iyengar. Physics and Chemistry, Frontiers in Distributed Sensor Networks, Chapter 7, S.S. Iyengar and Richard R. Brooks (editors), CRC Press Inc., September 2003.
60. M. Zhu, J. Lamb, R.R. Brooks, M. Pirretti, and S.S. Iyengar. Example DSN control hierarchy, Frontiers in Distributed Sensor Networks, Chapter 8, S. S. Iyengar and R. R. Brooks (editors), CRC Press Inc., September 2003.
61. W. Wang, Z. Przedworska, J. Parron, M. Lyons, M. Zhu and A. Tuininga, "MCROS: A Multimodal Collaborative RObot System for Human-Centered Tasks", Proceedings of the 21st IEEE International Conference on Networking, Sensing and Control, Hangzhou, China, Oct. 18-20, 2024.
62. A. Alqaddoumi, A. Mulinti, S. Penagamuri, Y. Ghaly, S. Chitnis, W. Wang and M. Zhu, "A Robot-Assisted Missing Child Search Approach", Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent Systems, Madrid, Spain, May 23-24, 2024.
61. W. Wang, Z. Przedworska, J. Parron, M. Lyons, M. Zhu and A. Tuininga, "MCROS: A Multimodal Collaborative RObot System for Human-Centered Tasks", Proceedings of the 21st IEEE International Conference on Networking, Sensing and Control, Hangzhou, China, Oct. 18-20, 2024.
62. A. Alqaddoumi, A. Mulinti, S. Penagamuri, Y. Ghaly, S. Chitnis, W. Wang and M. Zhu, "A Robot-Assisted Missing Child Search Approach", Proceedings of the IEEE International Conference on Evolving and Adaptive Intelligent Systems, Madrid, Spain, May 23-24, 2024.
63. J. Murphy, K. Corcoran, A. Llanos, W. Wang, M. Zhu and Rui Li, “Developing Students' Independent Problem-Solving Skills through the Heuristic Teaching Method in a Game Development Capstone Course”, Proceedings of 2024 IEEE Integrated STEM Education Conference (ISEC), Princeton, NJ March 9th 2024
64. E. Herrera, M. Lyons, J. Parron, R. Li, M. Zhu and W. Wang, “Learning-Finding-Giving: A Natural Vision-Speech-based Approach for Robots to Assist Humans in Human-Robot Collaborative Manufacturing Contexts”, Proceedings of 4th IEEE International Conference on Human-Machine Systems, May 2024, Toronto Canada Conference Theme: Trustworthy Human-Autonomy Teaming
65. B. Li, K. Serrano, M. Mazzaro, M. Wu, W. Wang and M. Zhu, "Identification of Cyanobacteria for Harmful Algal Blooms Research Using the YOLO Framework," Proceedings of 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, NY, USA, 2023, pp. 0407-0415, doi: 10.1109/UEMCON59035.2023.10316078. (The Best Paper award in track of AI and IoT)
66. J. Rodano, O. Obidat, J. Parron, R. Li, M. Zhu, and W. Wang, Teaching Humanoid Robots to Assist Humans for Collaborative Tasks, Proceedings of Eight IEEE Workshop on Smart Service Systems 2023 - Smartcomp 2023 Workshop, Nashville, TN June 2023
67. Y. Sheng, W. S Welling and M. Zhu, Developing Efficient Bayesian Estimation of IRT Models for Integrated STEM Education. Proceedings of 13th IEEE Integrated STEM Education Conference, Johns Hopkins University, Maryland USA March 11, 2023
68. A. Coutras, O. Obidat, M. Zhu and W. Wang, JUST TELL ME: A Robot-assisted E-health Solution for People with Lower-extremity Disability, Proceedings of 2023 9th International Conference on Automation, Robotics and Applications (ICARA23), Abu Dhabi, United Arab Emirates. February 10-12, 2023
69. P. Tilloo, J. Parron, O. Obidat, M. Zhu, and W. Wang, A POMDP-based Robot-Human Trust Model for Human-Robot Collaboration, Proc. The 12th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, 2022.
70. M. Rao, L. Paulino, V. Robila, I. Li, M. Zhu and W. Wang, Training-Free Lane Tracking for 1/10th Scale Autonomous Vehicle Using Inverse Perspective Mapping and Probabilistic Hough Transforms, The proceedings of the 2022 IEEE Integrated STEM Education Conference (ISEC), March, Princeton, NJ, USA, 2022
71. V. Robila, L. Paulino, M. Rao, I. Li, M. Zhu and W. Wang, "Design and Implementation of PID-Based Steering Control for 1/10-Scale Autonomous Vehicle," Proceedings of 2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2021, pp. 0758-0762, doi: 10.1109/UEMCON53757.2021.9666496.
72. L. Paulino, M. Zhu and W. Wang. Learning Autonomous Driving in Tangible Practice: Development and On-Road Applications of a 1/10-Scale Autonomous Vehicle, Proceedings of 2021 IEEE Frontiers in Education Conference (FIE), 2021, pp. 1-4, doi: 10.1109/FIE49875.2021.9637402.
73. W. Wang, C. Coutras and M. Zhu. Situated Learning-Based Robotics Education, Proceedings of 2020 IEEE Frontiers in Education Conference (FIE), Uppsala, 2020 pp. 1-3. doi: 10.1109/FIE44824.2020.9274168
74. M. Zhu, M. Johnson, A. Dutta, N. Panorkou, B. Samanthula, P. Lal, and W. Wang. Educational Simulation Design to Transform Learning in Earth and Environmental Sciences, Proceedings of 2020 IEEE Frontiers in Education Conference (FIE), 2020, pp. 1-6, doi: 10.1109/FIE44824.2020.9274198.
75. L. Zuo and M. Zhu. Minimize Cost of Data Transfers Using Bandwidth Reservation on FPVB Paths of Dynamic HPNs, Proceedings of 2020 International Conference on Computing, Networking and Communications (ICNC), pp. 74-78, Big Island, HI, USA, 2020. doi: 10.1109/ICNC47757.2020.9049789.
76. A. Hou, C. Wu, L. Zuo, D. Quan, Y. Li, M. Zhu, Q. Duan and D. Fang. Co-Scheduling of Advance and Immediate Bandwidth Reservations for Inter-Data Center Transfer, Proceedings of 2019 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS) Workshop in conjunction with The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), pp. 25~35, Denver, CO, Nov. 17 - 22, 2019.
77. L. Zuo, M. Zhu, C. Wu, A. Hou and L. Cao. Bandwidth Reservation for Data Transfers Through Multiple Disjoint Paths of Dynamic HPNs, Proceedings of the 21st IEEE International Conference on High Performance Computing and Communications (HPCC-2019), pp. 2455~2460, Zhangjiajie, China, August 2019
78. M. Zhu, S. Gulati and N. Panorkou. Simulation Design and Development for Learning Seasons and Lunar Phases using HTML5 and JavaScript. Proceedings of IEEE Integrated STEM education Conference (ISEC), pp. 414~418, 2019. March 2019
79. D. Basu, N. Panorkou and M. Zhu. Examining the Social Aspect of Climate Change through Mathematics. Proceedings of IEEE Integrated STEM education Conference (ISEC), pp. 239~244, 2019. March 2019
80. D. Li, B. Dong, M. Zhu. A Study on Flat and Hierarchical System Deployment for Edge Computing. 0163-0169. 10.1109/CCWC.2019.8666572. Proceedings of the IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC) 2019
81. T. Wang, J. Huan, Jun and M. Zhu. Instance-based Deep Transfer Learning. Proceedings of IEEE Winter Conf. on Applications of Computer Vision (WAVC 2019). arXiv:1809.02776v1. pp. 1-9. Waikoloa, Hawaii, U.S.A, Jan. 2019
82. A. Hou, C. Wu, D. Fang, L. Zuo, M. Zhu, X. Zhang, R. Qiao and X. Yin. (2018). Bandwidth Scheduling for Big Data Transfer with Deadline Constraint between Data Centers. pp. 55-63. 10.1109/INDIS.2018.00009. Proceedings of IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS), Dallas, Nov. 2018
83. M. Zhu, N. Panorkou, S. Etikyala, D. Basu, T. Street-Conaway, P. Iranah, D. Mazol, C. Hannum, R. Marshall, P. Lal and B. Samanthula. Steerable Environmental Simulations for Exploratory Learning. Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 83-92). San Diego, CA: Association for the Advancement of Computing in Education (AACE) Las Vegas, Oct. 2018.
84. D. Ding, F. Cao and M. Zhu. Design and Development of an Attendance Tracking and Early Warning System (AT-EAW). Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 11~17). Las Vegas, NV, United States: Association for the Advancement of Computing in Education (AACE) Las Vegas, Oct. 2018.
85. A. Al-Sinayyid and M. Zhu. Maximizing The Processing Rate for Streaming Applications in Apache Storm. Proceedings of The 14th International Conference on Data Science (ICDATA'18), pp. 143~146, Las Vegas, USA, July 30 - August 2, 2018.
86. L. Zuo, M. Zhu, C. Wu and A. Hou. Intelligent Bandwidth Reservation for Big Data Transfer in High-Performance Networks. Proceedings of IEEE International Conference on Communications (ICC) 2018 Communications QoS, Reliability, and Modeling Symposium, IEEE ICC 2018, pp. 1~6. Kansas City, U.S.A., May 20-24, 2018.
87. M. Zhu, N. Panorkou, P. Lal, S. Etikyala, E. Germia, P. Iranah, B. Samanthula and D. Basu. Integrating Interactive Computer Simulations into K-12 Earth and Environmental Science. Proceedings of IEEE Integrated STEM education Conference (ISEC) 2018, pp. 220-223. doi: 10.1109/ISECon.2018.8340488, Princeton, NJ. March 10th, 2018.
88. T. Wang, Z. Qin and M. Zhu, An ELU Network with Total Variation for Image Denoising. Lecture Notes in Computer Science, vol. 10636, pp. 227~237, Springer, Neural Information Processing, ICONIP 2017, Guangzhou, China, November 14-18, 2017.
89. L. Zuo, M. Zhu, C. Wu, M. Han and A. Wang. Flexible Bandwidth Scheduling for Streaming Data Movement Over Dedicated Networks. Proceedings of the International Symposium on Sensor Networks, Sensor Systems, and Security. pp. 185~195. Lakeland, Florida, U.S.A, September 2017.
90. L. Zuo and M. Zhu. Bandwidth Provision Strategies for Reliable Data Movements in Dedicated Networks. Proceedings of the IEEE BDMM'2016 in conjunction with IEEE Big Data 2016, pp. 3069~3078, Washington D.C., U.S.A, December 2016.
91. L. Zuo and M. Zhu. Improved Scheduling Algorithms for Single-Path Multiple Bandwidth Reservation Requests. Proceedings of the 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-16), pp. 1692~1699, Tianjing, China, August 2016.
92. M. Khaleel and M. Zhu. Energy-aware Job Scheduling and Consolidation Approaches for Workflow in Cloud. Poster paper in Proceedings of IEEE Cluster 2015, pp. 506~507, Chicago, U.S.A, Sept. 2015.
93. M. Safran, S. Al-Qahtani, M. Zhu and D. Che. Development of MapReduce and MPI Programs for Motif Search. Poster paper in Proceedings of IEEE Cluster 2015, pp. 500~501, Chicago, U.S.A., Sept. 2015.
94. A. Alahmadi, D. Che, M. Khaleel, M. Zhu and P. Ghodous. An Innovative Energy-Aware Cloud Task Scheduling Framework, Proceedings of IEEE CLOUD 2015, pp. 493~500, New York, U.S.A, June 2015.
95. M. Zhu, S. Rahimi and N. Rahimi. Promoting Teaching Effectiveness and Cultivating Interests in Parallel and Distributed Computing. EduPar Workshop in conjunction with IEEE IPDPS 2015, Proceedings of IEEE IPDPS, pp. 1~2, Hyderabad, India, May 2015.
96. F. Cao, M. Zhu and Q. Wu. Energy-Efficient Resource Management for Scientific Workflows in Clouds, Proceedings of the IEEE 2014 8th International Symposium on Scientific Workflows and Big Data Science (SWF 2014), pp. 402~409, in conjunction with IEEE BigData, Alaska, June 27 to July 2, 2014.
97. F. Cao, D. Ding, D. Che, M. Zhu and W. Hou. Scheduling Data Processing Flows under Budget Constraint on the Cloud. Proceedings of the ACM Research in Applied Computation Symposium (RACS) Montreal CA, pp. 69~74, ISBN: 978-1-4503-2348-2, 2013.
98. F. Cao and M. Zhu. Energy-aware Workflow Job Scheduling for Green Clouds. Proceedings of the IEEE International Conference on Green Computing and Communications (GreenCom2013), pp. 232~239, Beijing, China, August 2013.
99. L. Zuo, M. Khaleel, M. Zhu and C. Wu. On Fixed-Path Variable-Bandwidth Scheduling in High-performance Networks. Proceedings of the IEEE International Conference on Green Computing and Communications (GreenCom2013), pp. 23 ~ 30, Beijing, China, August 2013.
100. F. Yu, W. Hou, C. Luo, D. Che and M. Zhu. CS2: A New Database Synopsis for Query Estimation. Proceedings of ACM SIGMOD'13: International Conference on Management of Data, pp. 469~480, ISBN: 978-1-4503-2037-5, New York, USA, June 2013.
101. F. Cao, M. Zhu and D. Ding. Distributed Scientific Workflow Scheduling with Throughput or Budget Constraints in Grid Environments. Proceedings of the 17th workshop on job scheduling strategies for parallel processing (JSSPP) in conjunction with the 27th IEEE International Parallel & Distributed Processing Symposium (IPDPS), pp. 62~80, Boston, USA, May 2013.
102. F. Cao and M. Zhu. Energy Efficient Workflow Job Scheduling for Green Cloud. In Proceedings of PhD Forum of the 27th IEEE International Parallel & Distributed Processing Symposium (IPDPS), pp. 2218 ~2221, Boston, USA, May 2013.
103. L. Zuo and M. Zhu. Toward Flexible and Fast Routing Strategies for Dynamic Network Provisioning. Proceedings of the 27th IEEE International Parallel & Distributed Processing Symposium (IPDPS), PhD Forum, pp. 2222~2225, Boston, USA, May 2013.
104. P. Brown, M. Zhu, Q. Wu, D. Yun and J. Zurawski. A Workflow-based Network Advisor for Data Movement with End-to-end Performance Optimization. The 7th Workshop on Workflows in Support of Large-Scale Science. Proceeding of the ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC12), pp. 73~81, Salt Lake City, UT, Nov. 2012.
105. P. Brown, M. Zhu, Q. Wu, D. Yun and J. Zurawski. Exploring the Optimal Strategy for Large-scale Data Movement in High-performance Networks. Poster paper, WORKS Workshop, Proceeding of the 31st IEEE International Performance Computing and Communications Conference (IPCCC). pp. 181~182, Austin, TX, Dec. 2012.
106. M. Zhu, Q. Wu and Y. Zhao. A Cost-Effective Scheduling Algorithm for Scientific Workflows in Clouds. Proceeding of the 31st IEEE International Performance Computing and Communications Conference (IPCCC), pp. 256~265, Austin, TX, Dec. 2012 (Best Paper Award).
107. M. Zhu and F. Mumba. An Interactive Learning and Assessment System for Simulation-based Science Education Using Cloud Computing Technology. Demo paper in Proceeding of the 18th International Conference on Distributed Multimedia Systems (DMS), Miami Beach, FL, August 9-11, 2012.
108. P. Dharam, Q. Wu and M. Zhu. On Bandwidth Reservation for Optimal Resource Utilization in High-performance Networks. Proceedings of the 37th Annual IEEE Conference on Local Computer Networks(LCN), pp. 144 ~ 147, Clearwater, Florida, USA, Oct. 2012.
109. D. Yun, Q. Wu, M. Zhu and P. Brown. Modeling and Optimizing Transport-Support Workflows in High-performance Networks. Proceedings of the 37th Annual IEEE Conference on Local Computer Networks (LCN), pp. 384~391, Clearwater, Florida, USA, Oct. 2012.
110. P. Brown, M. Zhu and D. Che. Leveraged Data Diffusion Technique for Optimized Data Management in Sky Computing Environments. Proceedings of the 2nd Intl. Conf. on Advanced Computing and Communications (ACC-2012), pp. 79~84, Los Angeles, CA, 2012.
111. D. Che, M. Zhu, J. Fairfield and M. Khaleel. Putting “Credit Union” Cloud Computing Model into Practice. Proceedings of the ACM Research in Applied Computation Symposium (RACS), pp. 80~85, San Antonia, TX, Oct. 2012.
112. F. Mumba, M. Zhu, J. Ma and S. Ahmed. New Design and Implementation of a Virtual Classroom System Using Google App Engine. Proceedings of SITE 2012--Society for Information Technology & Teacher Education International Conference, pp. 698~705, Austin, Texas, USA, March 5-9, 2012.
113. P. Brown, M. Zhu, Q. Wu and X. Lu. Network-Aware Data Movement Advisor, Workshop of Network aware data management. Proceeding of the ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), pp. 31~40, Seattle, WA, Nov. 14-17, 2011
114. Q. Wu, M. Zhu, Y. Gu, X. Lu, P. Brown, M. Reuter, and S. Miller. A Distributed Workflow Management System with Case Study of Real-life Scientific Applications. Proceedings of the 30th IEEE International Performance Computing and Communications Conference (IPCCC 2011), pp. 1~8, November 17-19, Orlando, FL, 2011.
115. M. Zhu, F. Cao, and J. Mi. A Hybrid Mapping and Scheduling Algorithm for Distributed Workflow Applications in a Heterogeneous Computing Environment. Intelligent Distributed Computing V, Springer, SCI 382, vol. 1, pp. 117~127. Proceedings of the 5th International symposium on Intelligent Distributed Computing (IDC 2011), Delft, The Netherlands, October 2011.
116. F. Cao and M. Zhu. A Fault-tolerant Workflow Mapping Algorithm under End-to-end Delay Constraint. Proceeding of the Symposium on Advances of High Performance Computing and Networking (AHPCN-2011) in conjunction with the 13th IEEE international conference on High Performance Computing and Communications (HPCC-2011), pp. 575~580, Banff, Canada, September 2-4, 2011.
117. J. Ingram and M. Zhu. GPU Accelerated Microarray Data Analysis Using Random Matrix Theory. Proceeding of The IEEE 8th International Conference on Ubiquitous Intelligence and Computing (UIC-2011) Workshop on Embedded Multi-Core computing and Applications, pp. 839~844, Banff, Canada, September 2-4, 2011.
118. M. Tucker, F. Mumba, E. Miles and M Zhu. Elementary School Teachers’ Knowledge of Science Process Skills. Poster of the Mathematics and Science Partnership Program Regional Conference, San Francisco, CA, March 21-23, 2011.
119. F. Mumba, M. Zhu, and C.C. Cheng. An Interactive Simulation based Virtual Classroom System using Cloud Computing Technology. Proceedings of the SITE 2011--Society for Information Technology & Teacher Education International Conference, pp. 1~6, Nashville, Tennessee, USA; March 7-11, 2011.
120. V. M. Chabalengula, F. Mumba, M. Zhu, A. Banda, S. Mbewe and S. Miles. Science Teachers Familiarity of and Interest in Computer Simulations, Animations, Visualization, Modeling and Virtual reality. Proceedings of the SITE--Society for Information Technology & Teacher Education International Conference, pp. 2075~2077, Nashville, Tennessee, USA; March 7-11, 2011.
121. F. Mumba, V. M. Chabalengula and M. Zhu. Partnership in Advanced Science Achievement using Computational Science. Poster of Science, Technology, Engineering and Mathematics (STEM) in Education, Queensland University of Technology, Brisbane Australia, November 26-27, 2010.
122. Q. Wu, M. Zhu, X. Lu, P. Brown, Y. Lin, Y. Gu, F. Cao and M.A. Reuter. Automation and Management of Scientific Workflows in Distributed Network Environments. Proceedings of the 6th International Workshop on System Management Techniques, Processes, and Services, pp. 1~8, Atlanta, GA, April 19, 2010.
123. J. Yuan, M. Zhu, K. Meksem, P. Hart, and D. A. Lightfoot. Parallel comparative analyses of resistance pathways of Arabidopsis Thaliana and soybean (Glycine max) to fusarium Virguliforme and to deoxynivalenol of gibberella zeae. The World Soybean Research Conference VIII, Beijing, China, 2009.
124. J. He, M. Zhu, and M. Wainer. Parallel sequence alignment using Graphics Processing Unit. Proceedings of International Conference on Bioinformatics & Computational Biology BIOCOMP'09, vol. 1, pp. 96~103, Las Vegas, July 2009.
125. P. Brown, E. Fitzek, C. Li, M. Zhu, and M. Geisler. A new way to look at plant cis-regulatory elements. Joint Annual Meetings of the American Society of Plant Biologists and the Phycological Society of America, Hawaii Convention Center, Honolulu, Hawaii, July 2009.
126. P. Brown, E. Fitzek, C. Li, M. Zhu, and M. Geisler. Global discovery and functional annotation of Arabidopsis cis-regulatory elements. The 19th International Conference on Arabidopsis Research, Bioinformatics, Modeling, and Systems Biology, Montreal, Canada, July 2008.
127. J. Geisler-Lee, M. Zhu, and M. Geisler. Novel Gene Discovery in the Biosynthesis of Suberin, a Biopolymer. The 19th International Conference on Arabidopsis Research, Montreal, Canada, July 2008.
128. M. Zhu and N. K. Yadav. A Distributed System for Parallel Simulations. Proceedings of IEEE Global Communications Conference (IEEE GLOBECOM), pp. 1~5, New Orleans, LA, December 1-3, 2008.
129. Y. Gu, Q. Wu, M. Zhu, and N.S.V. Rao. Complexity analysis of pipeline mapping in heterogeneous distributed networks. Proceedings of International Symposium on Computer and Sensor Network Systems, Zhengzhou, P.R. China, April 7-10, 2008 (ISCSNS08). Also published in International Journal of Distributed Sensor Networks, 2008.
130. Y. Lin, Q. Wu, N.S.V. Rao, and M. Zhu. Advance bandwidth scheduling algorithms in dedicated networks. Proceedings of International Symposium on Computer and Sensor Network Systems, Zhengzhou, P.R. China, April 7-10, 2008 (ISCSNS08).
131. Q. Wu, Y. Gu, M. Zhu, and N.S.V. Rao. Optimizing network performance of computing pipelines in distributed environments. Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, the 9th IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing, pp. 1~8, Miami, Florida, April 2008.
132. M. Zhu, Q. Wu, and N.S.V. Rao. Computational monitoring and steering using network-optimized visualization and Ajax web server. Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, pp. 1~12, Miami, Florida, April 2008.
133. Y. Lin, Q. Wu, N.S.V. Rao, and M. Zhu. On design of scheduling algorithms for advance bandwidth reservation in dedicated networks. Proceedings of INFOCOM High-Speed Networks Workshop, pp. 1~6, Phoenix, Arizona, April 13, 2008.
134. M. Zhu and Q. Wu. A Parallel computing approach to decipher transcription network for large-scale microarray datasets. Proceedings of the 2007 International Conference on Bioinformatics and Computational Biology, vol. II, pp. 700~706, Las Vegas, Nevada, June 25-28, 2007.
135. Y. Yang, M. Zhu, L. Wu, and J. Zhou. Biostatistical Considerations of the Use of Genomic DNA Reference in Microarrays. Proceedings of 7th IEEE Bioinformatics and Bioengineering (BIBE07), Boston, MA, vol. I, pp 593~600, October 2007 (First Runner-up of Best Application Paper Award).
136. J. Yuan, M. Zhu, M. Iqbal, and D. A. Lightfoot. A Computational Approach to Understand Arabidopsis thaliana and Soybean Resistance to Fusarium solani (Fsg). Proceedings of the 7th IEEE Bioinformatics and Bioengineering, Boston, MA,vol. I, pp 585~592, October 2007.
137. Q. Wu, J. Gao, and M. Zhu. A scalable framework for distributed virtual reality using heterogeneous processors. Proceedings of the 16th International Conference on Artificial Reality and Telexistence, Lecture Notes in Computer Science, vol 1, pp. 314~323, Hangzhou, P.R. China, November 2006.
138. M. Zhu, Q. Wu, Y. Yang, and J. Zhou. A New approach to identify functional modules using random matrix theory. Proceedings of IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, vol. 1, pp. 117~123, Toronto, Canada, September 2006.
139. M. Zhu, S. Ding, R.R. Brooks, Q. Wu, N.S.V. Rao, and S. S. Iyengar. Fusion of threshold rules for target detection in self-organizing sensor networks. The 9th ONR/GTRI Workshop on Target Tracking and Sensor Fusion, Gatlinburg, TN, June 2006.
140. Q. Wu, M. Zhu, and N.S.V. Rao. System design for on-line distributed computational visualization and steering. Proceedings of the International Conference on E-learning and Games, Lecture Notes in Computer Science, vol. 3942, pp. 1121~1130, Hangzhou, China, April 2006.
141. M. Zhu, S.S. Iyengar, Q. Wu, and N.S.V. Rao. Optimal visualization pipeline decomposition and adaptive network mapping to support remote visualization. Proceeding of the 13th Annual Mardi Gras Conference: Frontiers of Grid Applications and Technologies, Baton Rouge, LA, February 2005.
142. M. Zhu, Q. Wu, N.S.V. Rao, and S.S. Iyengar. On optimal mapping of visualization pipeline onto linear arrangement of network nodes. Proceedings of SPIE 2004 (International Society for Optical Engineering), Conference on Visualization and Data Analysis, vol. 5669, pp. 1~11, San Jose, CA January 2005.
143. M. Zhu, Q. Wu, N.S.V. Rao, and S.S. Iyengar. Adaptive Visualization Pipeline Decomposition and Mapping onto Computer Networks. Proceedings of the 3rd International Conference on Image and Graphics, vol. 1, pp. 402~405, Hong Kong, China, December 2004.
144. R. R. Brooks, M. Piretti, M. Zhu, and S.S. Iyengar. Distributed Adaptation Methods for Wireless Sensor Networks. Proceedings of IEEE Globecom 2003, vol. 5, pp. 2967~2971, December 2003.
145. R. R. Brooks, M. Piretti, M. Zhu, and S.S. Iyengar. Adaptive routing using emergent protocols in wireless Ad Hoc Sensor Networks. Proceedings of SPIE 48th annual meeting symposium, Advanced Signal Processing Algorithms, Architecture, and Implementation, pp.155~163, San Diego, CA, August 2003.