| Machine learning on big data: Opportunities and challenges L Zhou, S Pan, J Wang, AV Vasilakos Neurocomputing 237, 350-361, 2017 | 1087 | 2017 |
| Smart manufacturing J Davis, T Edgar, R Graybill, P Korambath, B Schott, D Swink, J Wang, ... Annual review of chemical and biomolecular engineering 6 (1), 141-160, 2015 | 245 | 2015 |
| Kepler+ Hadoop: a general architecture facilitating data-intensive applications in scientific workflow systems J Wang, D Crawl, I Altintas Proceedings of the 4th Workshop on Workflows in Support of Large-Scale …, 2009 | 198 | 2009 |
| Pattern based property specification and verification for service composition J Yu, TP Manh, J Han, Y Jin, Y Han, J Wang Web Information Systems–WISE 2006: 7th International Conference on Web …, 2006 | 139 | 2006 |
| Big data provenance: Challenges, state of the art and opportunities J Wang, D Crawl, S Purawat, M Nguyen, I Altintas 2015 IEEE international conference on big data (Big Data), 2509-2516, 2015 | 121 | 2015 |
| A review of earth artificial intelligence Z Sun, L Sandoval, R Crystal-Ornelas, SM Mousavi, J Wang, C Lin, ... Computers & Geosciences 159, 105034, 2022 | 115 | 2022 |
| Workflow as a service in the cloud: architecture and scheduling algorithms J Wang, P Korambath, I Altintas, J Davis, D Crawl Procedia computer science 29, 546-556, 2014 | 79 | 2014 |
| An approach to detecting diabetic retinopathy based on integrated shallow convolutional neural networks W Chen, B Yang, J Li, J Wang IEEE Access 8, 178552-178562, 2020 | 62 | 2020 |
| Cloud computing in e-Science: research challenges and opportunities X Yang, D Wallom, S Waddington, J Wang, A Shaon, B Matthews, ... The Journal of Supercomputing 70, 408-464, 2014 | 61 | 2014 |
| Provenance for mapreduce-based data-intensive workflows D Crawl, J Wang, I Altintas Proceedings of the 6th Workshop on Workflows in Support of Large-scale …, 2011 | 60 | 2011 |
| CAFISE: An approach to enabling adaptive configuration of service grid applications YB Han, ZF Zhao, G Li, DS Xing, QZ Lv, JW Wang, JH Xiong, H Liu Journal of Computer Science and Technology 18, 484-494, 2003 | 54 | 2003 |
| Deploying kepler workflows as services on a cloud infrastructure for smart manufacturing P Korambath, J Wang, A Kumar, L Hochstein, B Schott, R Graybill, ... Procedia Computer Science 29, 2254-2259, 2014 | 53 | 2014 |
| A deterministic self-organizing map approach and its application on satellite data based cloud type classification W Zhang, J Wang, D Jin, L Oreopoulos, Z Zhang 2018 IEEE International Conference on Big Data (Big Data), 2027-2034, 2018 | 47 | 2018 |
| Wearable sensor based human posture recognition J Wang, Z Huang, W Zhang, A Patil, K Patil, T Zhu, EJ Shiroma, ... 2016 IEEE International conference on big data (big data), 3432-3438, 2016 | 47 | 2016 |
| A scalable data science workflow approach for big data bayesian network learning J Wang, Y Tang, M Nguyen, I Altintas 2014 IEEE/ACM International Symposium on Big Data Computing, 16-25, 2014 | 45 | 2014 |
| Machine learning based algorithms for global dust aerosol detection from satellite images: inter-comparisons and evaluation J Lee, YR Shi, C Cai, P Ciren, J Wang, A Gangopadhyay, Z Zhang Remote Sensing 13 (3), 456, 2021 | 43 | 2021 |
| Challenges and approaches for distributed workflow-driven analysis of large-scale biological data I Altintas, J Wang, D Crawl, W Li Proceedings of the 2012 Joint EDBT/ICDT Workshops, 73-78, 2012 | 43 | 2012 |
| Big data applications using workflows for data parallel computing J Wang, D Crawl, I Altintas, W Li Computing in Science & Engineering 16 (4), 11-21, 2014 | 42 | 2014 |
| Early cloud experiences with the kepler scientific workflow system J Wang, I Altintas Procedia Computer Science 9, 1630-1634, 2012 | 39 | 2012 |
| A smart manufacturing use case: Furnace temperature balancing in steam methane reforming process via kepler workflows P Korambath, J Wang, A Kumar, J Davis, R Graybill, B Schott, M Baldea Procedia Computer Science 80, 680-689, 2016 | 38 | 2016 |
Ilkay AltintasSDSC/UCSD在 sdsc.edu 的电子邮件经过验证
