By Dr Liming Zhu

Conference Papers

Bednarz T; Mathews A; Filonik D; Hughes RT; Chen D; Zhu L, 2021, 'Visual analytics for large networks: Theory, art and practice', in ACM SIGGRAPH 2021 Courses SIGGRAPH 2021, http://dx.doi.org/10.1145/3450508.3464558

Lu Q; Xu X; Bandara HMND; Chen S; Zhu L, 2021, 'Patterns for Blockchain-Based Payment Applications', in ACM International Conference Proceeding Series, http://dx.doi.org/10.1145/3489449.3490006

Zhang D; Xu X; Zhu L; Paik HY, 2021, 'A process adaptation framework for blockchain-based supply chain management', in IEEE International Conference on Blockchain and Cryptocurrency Icbc 2021

Chia SY; Xu X; Paik HY; Zhu L, 2021, 'Analysing and extending privacy patterns with architectural context', in Proceedings of the ACM Symposium on Applied Computing, pp. 1390 - 1398, http://dx.doi.org/10.1145/3412841.3442014

Shanmugarasa Y; Paik HY; Kanhere SS; Zhu L, 2021, 'Towards Automated Data Sharing in Personal Data Stores', in 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and Other Affiliated Events Percom Workshops 2021, pp. 328 - 331, http://dx.doi.org/10.1109/PerComWorkshops51409.2021.9431001

Xu X; Dilum Bandara HMN; Lu Q; Weber I; Bass L; Zhu L, 2021, 'A Decision Model for Choosing Patterns in Blockchain-Based Applications', in Proceedings IEEE 18th International Conference on Software Architecture Icsa 2021, pp. 47 - 57, http://dx.doi.org/10.1109/ICSA51549.2021.00013

Qi M; Wang Z; Wu F; Hanson R; Chen S; Xiang Y; Zhu L, 2021, 'A Blockchain-Enabled Federated Learning Model for Privacy Preservation: System Design', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 473 - 489, http://dx.doi.org/10.1007/978-3-030-90567-5_24

Ao S; Zhou T; Long G; Lu Q; Zhu L; Jiang J, 2021, 'CO-PILOT: COllaborative Planning and reInforcement Learning On sub-Task curriculum', in Advances in Neural Information Processing Systems, pp. 10444 - 10456

Lo SK; Lu Q; Paik HY; Zhu L, 2021, 'FLRA: A Reference Architecture for Federated Learning Systems', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 83 - 98, http://dx.doi.org/10.1007/978-3-030-86044-8_6

Dong M; Yao L; Wang X; Xu X; Zhu L, 2021, 'MetaGB: A Gradient Boosting Framework for Efficient Task Adaptive Meta Learning', in Proceedings IEEE International Conference on Data Mining Icdm, pp. 101 - 110, http://dx.doi.org/10.1109/ICDM51629.2021.00020

Su Y; Xing Z; Peng X; Xia X; Wang C; Xu X; Zhu L, 2021, 'Reducing Bug Triaging Confusion by Learning from Mistakes with a Bug Tossing Knowledge Graph', in Proceedings 2021 36th IEEE ACM International Conference on Automated Software Engineering Ase 2021, pp. 191 - 202, http://dx.doi.org/10.1109/ASE51524.2021.9678574

Sun J; Xing Z; Peng X; Xu X; Zhu L, 2021, 'Task-Oriented API Usage Examples Prompting Powered by Programming Task Knowledge Graph', in Proceedings 2021 IEEE International Conference on Software Maintenance and Evolution Icsme 2021, pp. 448 - 459, http://dx.doi.org/10.1109/ICSME52107.2021.00046

Hughes R; Edmond C; Wells L; Glencross M; Zhu L; Bednarz T, 2020, 'EXplainable AI (XAI): An introduction to the XAI landscape with practical examples', in SIGGRAPH Asia 2020 Courses SA 2020, Association for Computing Machinery (ACM), pp. 1 - 62, presented at SIGGRAPH Asia 2020 Courses, http://dx.doi.org/10.1145/3415263.3419166

Chen J; Xie M; Xing Z; Chen C; Xu X; Zhu L; Li G, 2020, 'Object detection for graphical user interface: Old fashioned or deep learning or a combination?', in Esec Fse 2020 Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pp. 1202 - 1214, http://dx.doi.org/10.1145/3368089.3409691

Ren X; Ye X; Xing Z; Xia X; Xu X; Zhu L; Sun J, 2020, 'API-Misuse Detection Driven by Fine-Grained API-Constraint Knowledge Graph', in Proceedings 2020 35th IEEE ACM International Conference on Automated Software Engineering Ase 2020, pp. 461 - 472, http://dx.doi.org/10.1145/3324884.3416551

Dong M; Yuan F; Yao L; Xu X; Zhu L, 2020, 'MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation', in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 688 - 697, http://dx.doi.org/10.1145/3394486.3403113

Zhao D; Xing Z; Chen C; Xu X; Zhu L; Li G; Wang J, 2020, 'Seenomaly: Vision-based linting of gui animation effects against design-don't guidelines', in Proceedings International Conference on Software Engineering, pp. 1286 - 1297, http://dx.doi.org/10.1145/3377811.3380411

Chen J; Chen C; Xing Z; Xu X; Zhu L; Li G; Wang J, 2020, 'Unblind your apps: Predicting natural-language labels for mobile gui components by deep learning', in Proceedings International Conference on Software Engineering, pp. 322 - 334, http://dx.doi.org/10.1145/3377811.3380327

Hu R; Pan S; Long G; Lu Q; Zhu L; Jiang J, 2020, 'Going deep: Graph convolutional ladder-shape networks', in Aaai 2020 34th Aaai Conference on Artificial Intelligence, pp. 2838 - 2845

Xu X; Bandara HMND; Lu Q; Zhang D; Zhu L, 2020, 'Understanding and Handling Blockchain Uncertainties', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 108 - 124, http://dx.doi.org/10.1007/978-3-030-59638-5_8

Verma S; Wang C; Zhu L; Liu W, 2019, 'DeepCU: Integrating both common and unique latent information for multimodal sentiment analysis', in IJCAI International Joint Conference on Artificial Intelligence, Macao, China, pp. 3627 - 3634, presented at 28th International Joint Conference on Artificial Intelligence IJCAI-19, Macao, China, 10 August 2019

Ko R; Chen L; Zhu L, 2019, 'Message from IEEE TrustCom 2019 General Chairs', in Proceedings 2019 18th IEEE International Conference on Trust Security and Privacy in Computing and Communications 13th IEEE International Conference on Big Data Science and Engineering Trustcom Bigdatase 2019, pp. xix, http://dx.doi.org/10.1109/TrustCom/BigDataSE.2019.00005

Verma S; Wang C; Zhu L; Liu W, 2019, 'A compliance checking framework for DNN models', in Ijcai International Joint Conference on Artificial Intelligence, pp. 6470 - 6471, http://dx.doi.org/10.24963/ijcai.2019/924

Zhang Y; Xu X; Satyal S; Chen S; Zhu L, 2019, 'A RESTful architecture for data exploration as a service', in Proceedings of the ACM Symposium on Applied Computing, pp. 1692 - 1700, http://dx.doi.org/10.1145/3297280.3297444

Wu H; Wang C; Tyshetskiy Y; Docherty A; Lu K; Zhu L, 2019, 'Adversarial examples for graph data: Deep insights into attack and defense', in Ijcai International Joint Conference on Artificial Intelligence, pp. 4816 - 4823, http://dx.doi.org/10.24963/ijcai.2019/669

Lee SU; Zhu L; Jeffery R, 2019, 'Data governance decisions for platform ecosystems', in Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 6377 - 6386

Verma S; Wang C; Zhu L; Liu W, 2019, 'Towards Effective Data Augmentations via Unbiased GAN Utilization', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 555 - 567, http://dx.doi.org/10.1007/978-3-030-29894-4_45

Ozkaya I; Zhu L, 2018, 'New and Emerging Ideas Track 2018', in Proceedings 2018 IEEE 15th International Conference on Software Architecture Companion Icsa C 2018, pp. 47, http://dx.doi.org/10.1109/ICSA-C.2018.00020

Wu D; Sakr S; Zhu L; Lee S; Wu H, 2018, 'HDM-MC in-Action: A framework for big data analytics across multiple clusters', in Proceedings International Conference on Distributed Computing Systems, pp. 1547 - 1550, http://dx.doi.org/10.1109/ICDCS.2018.00165

Wu H; Wang C; Lu K; Fu Y; Zhu L, 2018, 'One size does not fit all: The case for chunking configuration in backup deduplication', in Proceedings 18th IEEE ACM International Symposium on Cluster Cloud and Grid Computing Ccgrid 2018, pp. 213 - 222, http://dx.doi.org/10.1109/CCGRID.2018.00036

Xu X; Pautasso C; Zhu L; Lu Q; Weber I, 2018, 'A pattern collection for blockchain-based applications', in ACM International Conference Proceeding Series, http://dx.doi.org/10.1145/3282308.3282312

Wang B; Chen S; Yao L; Liu B; Xu X; Zhu L, 2018, 'A simulation approach for studying behavior and quality of blockchain networks', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Seattle, WA, USA, pp. 18 - 31, presented at International Conference on Blockchain, ICBC 2018, Seattle, WA, USA, 25 June 2018 - 30 June 2018, http://dx.doi.org/10.1007/978-3-319-94478-4_2

Wu H; Wang C; Yin J; Lu K; Zhu L, 2018, 'Sharing deep neural network models with interpretation', in Web Conference 2018 Proceedings of the World Wide Web Conference Www 2018, pp. 177 - 186, http://dx.doi.org/10.1145/3178876.3185995

Lee SU; Zhu L; Jeffery R, 2018, 'A contingency-based approach to data governance design for platform ecosystems', in Proceedings of the 22nd Pacific Asia Conference on Information Systems Opportunities and Challenges for the Digitized Society are We Ready Pacis 2018

Lee SU; Zhu L; Jeffery R, 2018, 'A data governance framework for platform ecosystem process management', in Lecture Notes in Business Information Processing, pp. 211 - 227, http://dx.doi.org/10.1007/978-3-319-98651-7_13

Liu Y; Lu Q; Xu X; Zhu L; Yao H, 2018, 'Applying design patterns in smart contracts: A case study on a blockchain-based traceability application', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 92 - 106, http://dx.doi.org/10.1007/978-3-319-94478-4_7

Zhang Y; Zhu L; Xu X; Chen S; Tran AB, 2018, 'Data service API design for data analytics', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 87 - 102, http://dx.doi.org/10.1007/978-3-319-94376-3_6

Lee SU; Zhu L; Jeffery R, 2018, 'Designing data governance in platform ecosystems', in Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 5014 - 5023

Verma S; Liu W; Wang C; Zhu L, 2018, 'Hybrid networks: Improving deep learning networks via integrating two views of images', in Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, pp. 46 - 58, http://dx.doi.org/10.1007/978-3-030-04167-0_5

Zhang S; Yao L; Xu X; Wang S; Zhu L, 2017, 'Hybrid collaborative recommendation via Semi-AutoEncoder', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Guangzhou, China, pp. 185 - 193, presented at 24th International Conference, ICONIP 2017, Guangzhou, China, 14 November 2017 - 18 November 2017, http://dx.doi.org/10.1007/978-3-319-70087-8_20

Fu M; Chen S; Yang J; Nepal S; Zhu L, 2017, 'ARA-Assessor: Application-aware runtime risk assessment for cloud-based business continuity', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Malaga, Spain, pp. 511 - 527, presented at 15th International Conference, ICSOC 2017, Malaga, Spain, 13 November 2017 - 16 November 2017, http://dx.doi.org/10.1007/978-3-319-69035-3_38

Shahin M; Babar MA; Zahedi M; Zhu L, 2017, 'Beyond Continuous Delivery: An Empirical Investigation of Continuous Deployment Challenges', in International Symposium on Empirical Software Engineering and Measurement, Toronto, ON, Canada, pp. 111 - 120, presented at 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), Toronto, ON, Canada, 09 November 2017 - 10 November 2017, http://dx.doi.org/10.1109/ESEM.2017.18

Rabhi F; Geumpana T; Zhu L, 2017, 'Accommodating Information Priority Model in Cloudlet Environment', in Lecture Notes in Business Information Processing, Springer Nature, Sydney, NSW, pp. 21 - 34, presented at Australian Symposium on Service Research and Innovation, Sydney, NSW, 19 October 2017 - 20 October 2017, http://dx.doi.org/10.1007/978-3-319-76587-7_2

Ekparinya P; Gramoli V; Jourjon G; Zhu L, 2017, 'Stratosphere: Dynamic IP Overlay above the Clouds', in Proceedings - Conference on Local Computer Networks, LCN, Singapore, Singapore, pp. 583 - 586, presented at 2017 IEEE 42nd Conference on Local Computer Networks (LCN), Singapore, Singapore, 09 October 2017 - 12 October 2017, http://dx.doi.org/10.1109/LCN.2017.75

Liu B; Yu XL; Chen S; Xu X; Zhu L, 2017, 'Blockchain Based Data Integrity Service Framework for IoT Data', in Proceedings - 2017 IEEE 24th International Conference on Web Services, ICWS 2017, Honolulu, HI, USA, pp. 468 - 475, presented at 2017 IEEE International Conference on Web Services (ICWS), Honolulu, HI, USA, 25 June 2017 - 30 June 2017, http://dx.doi.org/10.1109/ICWS.2017.54

Shahin M; Zahedi M; Ali Babar M; Zhu L, 2017, 'Adopting continuous delivery and deployment: Impacts on team structures, collaboration and responsibilities', in ACM International Conference Proceeding Series, Karlskrona, Sweden, pp. 384 - 393, presented at EASE'17 Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering, Karlskrona, Sweden, 15 June 2017 - 16 June 2017, http://dx.doi.org/10.1145/3084226.3084263

Xu X; Weber I; Staples M; Zhu L; Bosch J; Bass L; Pautasso C; Rimba P, 2017, 'A Taxonomy of Blockchain-Based Systems for Architecture Design', in Proceedings 2017 IEEE International Conference on Software Architecture Icsa 2017, pp. 243 - 252, http://dx.doi.org/10.1109/ICSA.2017.33

Wu D; Sakr ; zhu LIMING; Wu HUIJUN, 2017, 'Towards Big Data Analytics across Multiple Clusters', Madrid, Spain, presented at 17TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID, Madrid, Spain, 14 May 2017 - 17 May 2017

Wu D; sakr ; Zhu LIMING, 2017, 'HDM: Optimized Big Data Processing with Data Provenance', in Proceedings of the 20th International Conference on Extending Database Technology, Venice, Italy, presented at The 20th International Conference on Extending Database Technology, Venice, Italy, 21 March 2017 - 24 March 2017

Verma S; Liu W; Wang C; Zhu L, 2017, 'Extracting highly effective features for supervised learning via simultaneous tensor factorization', in PROCEEDINGS OF THE THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-NINTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE, The AAAI Press, Palo Alto, California., San Francisco, California USA, pp. 4995 - 4996, presented at THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, San Francisco, California USA, 04 February 2017 - 09 February 2017, https://www.aaai.org/Library/AAAI/aaai17contents.php

Back to profile page