Google Scholar Profile: https://scholar.google.com/citations?hl=en&user=W91A6_sAAAAJ
Orcid: https://orcid.org/0000-0002-0674-2131
DBLP: https://dblp.org/pid/24/5908.html
Full List of Publications: PDF Link
Full List of Publications:
Peer Reviewed Articles (Reverse Chronological Order)
[1] M. Yahya, A. Wahid, L. Yang, J. G. Breslin, E. Kharlamov, and M. I. Ali. Link prediction in industrial knowledge graphs: A case study on football manufacturing. IEEE Access, 2024.
[2] M. Yahya, A. Ali, Q. Mehmood, L. Yang, J. G. Breslin, and M. I. Ali. A benchmark dataset with knowledge graph generation for industry 4.0 production lines. Semantic Web, 15(2):461–479, 2024.
[3] A. Wahid, J. G. Breslin, and M. A. Intizar. Tcrscanet: Harnessing temporal convolutions and recurrent skip component for enhanced rul estimation in mechanical systems. Human-Centric Intelligent Systems, pages 1–24, 2024.
[4] A. O. Victor and M. I. Ali. Enhancing time series data predictions: A survey of augmentation techniques and model performances. In Proceedings of the 2024 Australasian Computer Science Week, pages 1–13. 2024.
[5] M. Tahir and M. I. Ali. Multi-criterion client selection for efficient federated learning. In Proceedings of the AAAI Symposium Series, volume 3, pages 318–322, 2024.
[6] J. Kafunah, M. I. Ali, and J. G. Breslin. Uncertainty-aware ensemble combination method for quality monitoring fault diagnosis in safety-related products. IEEE Transactions on Industrial Informatics, 20(2):1975–1986, Feb. 2024.
[7] J. Zhou, C. Briciu-Burghina, F. Regan, and M. I. Ali. A data-driven approach for building the profile of water storage capacity of soils. Sensors, 23(12):5599, June 2023.
[8] M. Yahya, B. Zhou, J. G. Breslin, M. I. Ali, and E. Kharlamov. Semantic modeling, development and evaluation for the resistance spot welding industry. IEEE Access, 11:37360–37377, 2023.
[9] A. Victor Okhuese and A. M. Intizar. Healthcare internet of things (iot): A survey of stateof-the-art methods and approaches. 2023.
[10] J. Kafunah, P. Verma, M. I. Ali, and J. G. Breslin. Out-of-distribution data generation for fault detection and diagnosis in industrial systems. IEEE Access, 11:135061–135073, 2023.
[11] A. Wahid, J. G. Breslin, and M. A. Intizar. Prediction of machine failure in industry 4.0: A hybrid cnn-lstm framework. Applied Sciences, 12(9), 2022.
[12] M. Tahir and M. I. Ali. On the performance of federated learning algorithms for iot. IoT, 3(2):273–284, 2022.
[13] B. Sudharsan, D. Sundaram, P. Patel, J. G. Breslin, M. I. Ali, S. Dustdar, A. Zomaya, and R. Ranjan. Multi-component optimization and efficient deployment of neural-networks on resource-constrained iot hardware, 2022.
[14] B. Sudharsan, J. G. Breslin, M. Tahir, M. Intizar Ali, O. Rana, S. Dustdar, and R. Ranjan. Ota-tinyml: Over the air deployment of tinyml models and execution on iot devices. IEEE Internet Computing, 26(3):69–78, May 2022.
[15] C. Briciu-Burghina, J. Zhou, M. I. Ali, and F. Regan. Demonstrating the potential of a low-cost soil moisture sensor network. Sensors, 22(3):987, Jan. 2022.
[16] M. Yahya, J. G. Breslin, and M. I. Ali. Semantic web and knowledge graphs for industry 4.0. Applied Sciences, 11(11):5110, 2021.
[17] M. Yahya, J. G. Breslin, and M. I. Ali. Semantic web and knowledge graphs for industry 4.0. Applied Sciences, 11(11):5110, may 2021.
[18] B. Sudharsan, P. Yadav, J. G. Breslin, and M. I. Ali. Train++: An incremental ML model training algorithm to create self-learning iot devices. In 2021 IEEE Smart-
World, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI), Atlanta, GA, USA, October 18-21, 2021, pages 97–106. IEEE, 2021.
[19] B. Sudharsan, P. Yadav, J. G. Breslin, and M. I. Ali. An SRAM optimized approach for constant memory consumption and ultra-fast execution of ML classifiers on tinyml hardware. In B. Carminati, C. K. Chang, E. Daminai, S. Deng, W. Tan, Z. Wang, R. Ward, and J. Zhang, editors, IEEE International Conference on Services Computing, SCC 2021, Chicago, IL, USA, September 5-10, 2021, pages 319–328. IEEE, 2021.
[20] B. Sudharsan, D. Sundaram, P. Patel, J. G. Breslin, and M. I. Ali. Edge2guard: Botnet attacks detecting offline models for resource-constrained iot devices. In 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, Kassel, Germany, March 22-26, 2021, pages 680–685. IEEE, 2021.
[21] B. Sudharsan, D. Sheth, S. Arya, F. Rollo, P. Yadav, P. Patel, J. G. Breslin, and M. I. Ali. Elasticl: Elastic quantization for communication efficient collaborative learning in iot. In Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems, SenSys ’21, page 382–383, New York, NY, USA, 2021. Association for Computing Machinery.
[22] B. Sudharsan, S. Salerno, D. Nguyen, M. Yahya, A. Wahid, P. Yadav, J. G. Breslin, and M. I. Ali. Tinyml benchmark: Executing fully connected neural networks on commodity microcontrollers. In 7th IEEE World Forum on Internet of Things, WF-IoT 2021, New Orleans, LA, USA, June 14 - July 31, 2021, pages 883–884. IEEE, 2021.
[23] B. Sudharsan, P. Patel, A. Wahid, M. Yahya, J. G. Breslin, and M. I. Ali. Porting and execution of anomalies detection models on embedded systems in iot: Demo abstract. In IoTDI ’21: International Conference on Internet-of-Things Design and Implementation, Virtual Event / Charlottesville, VA, USA, May 18-21, 2021, pages 265–266. ACM, 2021.
[24] B. Sudharsan, P. Patel, J. G. Breslin, M. I. Ali, K. Mitra, S. Dustdar, O. Rana, P. P. Jayaraman, and R. Ranjan. Toward distributed, global, deep learning using iot devices. IEEE Internet Comput., 25(3):6–12, 2021.
[25] B. Sudharsan, P. Patel, J. G. Breslin, and M. I. Ali. Ultra-fast machine learning classifier execution on iot devices without SRAM consumption. In 19th IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2021, Kassel, Germany, March 22-26, 2021, pages 316–319. IEEE, 2021.
[26] B. Sudharsan, P. Patel, J. G. Breslin, and M. I. Ali. SRAM optimized porting and execution of machine learning classifiers on mcu-based iot devices: demo abstract. In M. Maggio, J. Weimer, M. A. Farque, and M. Oishi, editors, ICCPS ’21: ACM/IEEE 12th International Conference on Cyber-Physical Systems, Nashville, Tennessee, USA, May 19-21, 2021, pages 223–224. ACM, 2021.
[27] B. Sudharsan, P. Patel, J. G. Breslin, and M. I. Ali. Enabling machine learning on the edge using sram conserving efficient neural networks execution approach. In Y. Dong, N. Kourtellis, B. Hammer, and J. A. Lozano, editors, Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, pages 20–35, Cham, 2021. Springer International Publishing.
[28] B. Sudharsan, P. Patel, J. G. Breslin, and M. I. Ali. Enabling machine learning on the edge using SRAM conserving efficient neural networks execution approach. In Y. Dong, N. Kourtellis, B. Hammer, and J. A. Lozano, editors, Machine Learning and Knowledge
Discovery in Databases. Applied Data Science Track - European Conference, ECML PKDD 2021, Bilbao, Spain, September 13-17, 2021, Proceedings, Part V, volume 12979 of Lecture Notes in Computer Science, pages 20–35. Springer, 2021.
[29] B. Sudharsan, S. Malik, P. Corcoran, P. Patel, J. G. Breslin, and M. I. Ali. Owsnet: Towards real-time offensive words spotting network for consumer iot devices. In 7th IEEE World Forum on Internet of Things, WF-IoT 2021, New Orleans, LA, USA, June 14 - July 31, 2021, pages 83–88. IEEE, 2021.
[30] B. Sudharsan, J. G. Breslin, and M. I. Ali. Ml-mcu: A framework to train ml classifiers on mcu-based iot edge devices. IEEE Internet of Things Journal, pages 1–1, 2021.
[31] B. Sudharsan, J. G. Breslin, and M. I. Ali. Imbal-ol: Online machine learning from imbalanced data streams in real-world iot. In 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, December 15-18, 2021, pages 4974–4978. IEEE, 2021.
[32] B. Sudharsan, J. G. Breslin, and M. I. Ali. Globe2train: A framework for distributed ML model training using iot devices across the globe. In 2021 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI), Atlanta, GA, USA, October 18-21, 2021, pages 107–114. IEEE, 2021.
[33] R. Sahal, S. H. Alsamhi, J. G. Breslin, K. N. Brown, and M. I. Ali. Digital twins collaboration for automatic erratic operational data detection in industry 4.0. Applied Sciences, 11(7):3186, 2021.
[34] R. Sahal, S. H. Alsamhi, J. G. Breslin, K. N. Brown, and M. I. Ali. Digital twins collaboration for automatic erratic operational data detection in industry 4.0. Applied Sciences, 11(7):3186, apr 2021.
[35] R. Sahal, S. H. Alsamhi, J. G. Breslin, and M. I. Ali. Industry 4.0 towards forestry 4.0: Fire detection use case. Sensors, 21(3):694, 2021.
[36] V. Patel, S. Kanani, T. Pathak, P. Patel, M. I. Ali, and J. Breslin. An intelligent doorbell design using federated deep learning. In 8th ACM IKDD CODS and 26th COMAD, CODS COMAD 2021, page 380–384, New York, NY, USA, 2021. Association for Computing Machinery.
[37] P. Mehta, R. Dwivedi, C. Feeney, P. Patel, M. I. Ali, and J. Breslin. Towards designing an explainable-ai based solution for livestock mart industry. In 8th ACM IKDD CODS and 26th COMAD, CODS COMAD 2021, page 421, New York, NY, USA, 2021. Association for Computing Machinery.
[38] J. Kafunah, M. I. Ali, and J. G. Breslin. Handling imbalanced datasets for robust deep neural network-based fault detection in manufacturing systems. Applied Sciences, 11(21), 2021.
[39] M. I. Ali, P. Patel, J. G. Breslin, R. F. Harik, and A. P. Sheth. Cognitive digital twins for smart manufacturing. IEEE Intell. Syst., 36(2):96–100, 2021.
[40] D. Thakker, P. Patel, M. I. Ali, and T. Shah. Semantic web of things for industry 4.0. Semantic Web, 11(6):885–886, 2020.
[41] B. Sudharshan, D. Sundaram, J. G. Breslin, and M. I. Ali. Avoid touching your face: A hand-to-face 3d motiondataset (covid-away) and trained models forsmartwatches. In Proc. of IoT-HSA at the 10th International Conference on Internet of Things, 2020.
[42] B. Sudharshan, J. G. Breslin, and M. I. Ali. RCE-NN: A five-stages pipeline to execute cnns on resource-constrained edge devices. In Proc. of the 10th International Conference on Internet of Things, 2020.
[43] B. Sudharshan, J. G. Breslin, and M. I. Ali. Edge2Train: A framework to train machine learning models(svms) on resource-constrained iot edge devices. In Proc. of the 10th International Conference on Internet of Things, 2020.
[44] B. Sudharshan, J. G. Breslin, and M. I. Ali. Adaptive strategy to improve the quality ofcommunication for iot edge devices. In IEEE Virtual World Forum on Internet of Things, WF-IoT, 2020.
[45] R. Sahal, J. G. Breslin, and M. I. Ali. Big data and stream processing platforms for industry 4.0 requirements mapping for a predictive maintenance use case. Journal of Manufacturing Systems, 54:138 – 151, 2020.
[46] T. Pathak, V. Patel, S. Kanani, S. Aryaand, P. Patel, and M. I. Ali. A distributed framework to orchestrate video analytics acrossedge and cloud: A use case of smart doorbell. In Proc. of the 10th International Conference on Internet of Things, 2020.
[47] V. Patel, S. Kanani, T. Pathak, P. Patel, M. I. Ali, and J. G. Breslin. A demonstration of smart doorbell design using federated deep learning. CoRR, abs/2010.09687, 2020, 2010.09687.
[48] P. Patel and M. I. Ali. Developing real-time smart industrial analytics for industry 4.0 applications. In Smart Service Management, pages 193–215. Springer, 2020.
[49] V. Kamath, J. Breslin, and M. I. Ali. Industrial iot and digital twins for a smart factory : An open source toolkit for application design and benchmarking. In Proc. of the Global IoT Summit (GIoT) 2020, Dublin, Ireland, 2020.
[50] B. Joshi, T. Pathak, V. Patel, S. Kanani, P. Patel, M. I. Ali, and J. G. Breslin. Demonstration of a cloud-based software framework for video analytics application using low-cost iot devices. CoRR, abs/2010.07680, 2020, 2010.07680.
[51] B. Joshi, T. Pathak, V. Patel, S. Kanani, P. Patel, and M. Ali. A cloud-based smart doorbell using low-cost cots devices. ACM International Conference Proceeding Series, 2020.
[52] B. Joshi, P. Patel, and M. I. Ali. A distributed framework to orchestrate video analytics across edge and cloud: A use case of smart doorbell. In Proc. of the 10th International Conference on Internet of Things, 2020.
[53] A. Wahid and M. I. Ali. Deconvolutional pixel layer model for road segmentation without human assistance. In 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, 2019.
[54] B. Sudharsan, P. Corcoran, and M. I. Ali. Smart speaker design and implementation with biometric authentication and advanced voice interaction capability. In 27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, 2019.
[55] Z. U. Shamszaman and M. I. Ali. Enabling cognitive contributory societies using SIoT: QoS aware real-time virtual object management. Journal of Parallel and Distributed Computing, 2019.
[56] R. Sahal, J. G. Breslin, and M. I. Ali. On evaluating the impact of changes in IoT data streams rate over query window configurations. In Proceedings of the 13th ACM International Conference on Distributed and Event-based Systems, DEBS 2019, Darmstadt, Germany, June 24-28, 2019., pages 262–263, 2019.
[57] T. L. Pham, M. I. Ali, and A. Mileo. Enhancing the scalability of expressive stream reasoning via input-driven parallelization. Semantic Web Journal, 2019.
[58] T.-L. Pham, M. I. Ali, and A. Mileo. C-ASP: Continuous ASP-based reasoning over RDF streams. In Logic Programming and Nonmonotonic Reasoning, pages 45–50. Springer International Publishing, 2019.
[59] T.-L. Pham, M. I. Ali, and A. Mileo. C-ASP: Continous asp-based reasoning over rdf streams. In Proc. of Logic Programming and Non-Monotonic Reasoning LPNMR 2019, Philadelphia, USA, 2019.
[60] D.-D. Nguyen and M. I. Ali. Enabling on-demand decentralized iot collectability marketplaceusing blockchain and crowdsensing. In Proc. of the Global IoT Summit (GIoT) 2019, Aarhus, Denmark, 2019.
[61] M. I. Ali, P. Patel, and J. G. Breslin. A middleware for real-time event detection and predictive analytics in smart manufacturing. In Proc. of International Conference on Distributed Computing in Sensor Systems (DCOSS 2019), Santorini, Greece, 2019.
[62] M. I. Ali, Q. Mehmood, and M. Saleem. Assessing, monitoring and analyzing linkeddata quality in public sparql endpoints. In Proceedings of the 18th International Semantic Web Conference, ISWC 2019, Auckland, New Zealand, October 26-30, 2019.
[63] M. I. Ali, Q. Mehmood, and M. Saleem. Assessing, monitoring and analyzing linkeddata quality in public sparql endpoints. In Proceedings of the 18th International Semantic Web Conference, ISWC 2019, Auckland, New Zealand, October 26-30, 2019.
[64] M. Ali, Q. Mehmood, and M. Saleem. Assessing, monitoring and analyzing linked data quality in public sparql endpoints. CEUR Workshop Proceedings, 2496:37–50, 2019.
[65] R. Tommasini, Y. A. Sedira, D. Dell’Aglio, M. Balduini, M. I. Ali, D. Le Phuoc, E. Della Valle, and J.-P. Calbimonte. Vocals: Vocabulary and catalog of linked streams. In International Semantic Web Conference, pages 256–272. Springer, 2018.
[66] R. Tommasini, Y. A. Sedira, D. Dell’Aglio, M. Balduini, M. Intizar Ali, D. Le Phuoc, E. Della Valle, and J.-P. Calbimonte. Vocals: Describing streams on the web. 2018.
[67] Z. U. Shamszaman and M. I. Ali. Towards a smart society through semantic virtual-object enabled real-time management framework in the social internet of things. IEEE Internet of Things Journal, 2018.
[68] Z. U. Shamszaman and M. I. Ali. Toward a smart society through semantic virtual-object enabled real-time management framework in the social internet of things. IEEE Internet of Things Journal, 5(4):2572–2579, aug 2018.
[69] P. Patel, M. I. Ali, and A. P. Sheth. From raw data to smart manufacturing: AI and semantic web of things for industry 4.0. IEEE Intelligent Systems, 33(4):79–86, 2018.
[70] D. Nguyen, C. L. Van, and M. I. Ali. Vessel trajectory prediction using sequence-to-sequence models over spatial grid. In Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems, DEBS 2018, Hamilton, New Zealand, June 25-29, 2018, pages 258–261, 2018.
[71] D. Nguyen, C. L. Van, and M. I. Ali. Vessel destination and arrival time prediction with sequence-to-sequence models over spatial grid. In Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems, DEBS 2018, Hamilton, New Zealand, June 25-29, 2018, pages 217–220, 2018.
[72] S. Kolozali, M. Bermudez-Edo, N. F. Davar, P. Barnaghi, F. Gao, M. I. Ali, A. Mileo, M. Fischer, T. Iggena, D. Kuemper, and R. Tonjes. Observing the pulse of a city: A smart city framework for real-time discovery, federation, and aggregation of data streams. IEEE Internet of Things Journal, 2018.
[73] M. Ali, P. Patel, A. Sheth, and D. Thakker. Preface of sweti 2018: Semantic web of things for industry 4.0. CEUR Workshop Proceedings, 2112, 2018.
[74] C. L. Van, F. Gao, and M. I. Ali. Optimizing the performance of concurrent RDF stream processing queries. In The Semantic Web - 14th International Conference, ESWC 2017, Portorož, Slovenia, May 28 - June 1, 2017, Proceedings, Part I, pages 238–253, 2017.
[75] Z. Ush-Shamszaman and M. I. Ali. On the need for applications aware adaptive middleware in real-time RDF data analysis (short paper). In On the Move to Meaningful Internet Systems. OTM 2017 Conferences - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Proceedings, Part II, pages 189– 197, 2017.
[76] T. Pham, A. Mileo, and M. I. Ali. Towards scalable non-monotonic stream reasoning via input dependency analysis. In 33rd IEEE International Conference on Data Engineering, ICDE 2017, San Diego, CA, USA, April 19-22, 2017, pages 1553–1558, 2017.
[77] T. Pham, S. Germano, A. Mileo, D. Kümper, and M. I. Ali. Automatic configuration of smart city applications for user-centric decision support. In 20th Conference on Innovations in Clouds, Internet and Networks, ICIN 2017, Paris, France, March 7-9, 2017, pages 360– 365, 2017.
[78] P. Patel, A. Gyrard, S. K. Datta, and M. I. Ali. Swotsuite: A toolkit for prototyping end-toend semantic web of things applications. In Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, April 3-7, 2017, pages 263–267, 2017.
[79] P. Patel, M. I. Ali, and A. P. Sheth. On using the intelligent edge for iot analytics. IEEE Intelligent Systems, 32(5):64–69, 2017.
[80] A. Kamilaris, A. Pitsillides, F. X. Prenafeta-Boldu, and M. I. Ali. A web of things based eco-system for urban computing - towards smarter cities. In 24th International Conference on Telecommunications, ICT 2017, Limassol, Cyprus, May 3-5, 2017, pages 1–7, 2017.
[81] A. Gyrard, M. Serrano, J. B. Jares, S. K. Datta, and M. I. Ali. Sensor-based linked open rules (S-LOR): an automated rule discovery approach for iot applications and its use in smart cities. In Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, April 3-7, 2017, pages 1153–1159, 2017.
[82] A. Gyrard, P. Patel, S. K. Datta, and M. I. Ali. Semantic web meets internet of things and web of things: [2nd edition]. In Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, April 3-7, 2017, pages 917–920, 2017.
[83] F. Gao, M. I. Ali, E. Curry, and A. Mileo. Automated discovery and integration of semantic urban data streams: The ACEIS middleware. Future Generation Comp. Syst., 76:561–581, 2017.
[84] D. Dell’Aglio, D. L. Phuoc, A. L. Tuán, M. I. Ali, and J. Calbimonte. On a web of data streams. In Proceedings of the Workshop on Decentralizing the Semantic Web 2017 co-located with 16th International Semantic Web Conference (ISWC 2017), 2017.
[85] D. Dell’Aglio, D. Le Phuoc, A. Le-Tuan, M. Ali, and J.-P. Calbimonte. On a web of data streams. CEUR Workshop Proceedings, 1934, 2017.
[86] M. I. Ali, P. Patel, S. K. Datta, and A. Gyrard. Multi-layer cross domain reasoning over distributed autonomous iot applications. OJIOT, 3(1):75–90, 2017.
[87] M. I. Ali, N. Ono, M. Kaysar, Z. Ush-Shamszaman, T. Pham, F. Gao, K. Griffin, and A. Mileo. Real-time data analytics and event detection for iot-enabled communication systems. J. Web Sem., 42:19–37, 2017.
[88] M. I. Ali, N. Ono, M. Kaysar, Z. U. Shamszaman, T.-L. Pham, F. Gao, K. Griffin, and A. Mileo. Real-time data analytics and event detection for iot-enabled communication systems. Web Semantics: Science, Services and Agents on the World Wide Web, 42:19–37,
2017.
[89] D. Puiu, P. Barnaghi, R. Tönjes, D. Kümper, M. I. Ali, A. Mileo, J. X. Parreira, M. Fischer, S. Kolozali, N. Farajidavar, et al. Citypulse: Large scale data analytics framework for smart cities. IEEE Access, 4:1086–1108, 2016.
[90] D. Puiu, P. Barnaghi, R. Tonjes, D. Kumper, M. Ali, A. Mileo, J. Xavier Parreira, M. Fischer, S. Kolozali, N. Farajidavar, F. Gao, T. Iggena, T.-L. Pham, C.-S. Nechifor, D. Puschmann, and J. Fernandes. Citypulse: Large scale data analytics framework for smart cities. IEEE Access, 4:1086–1108, 2016.
[91] A. Kamilaris, S. Yumusak, and M. I. Ali. WOTS2E: A search engine for a semantic web of things. In 3rd IEEE World Forum on Internet of Things, WF-IoT 2016, Reston, VA, USA, December 12-14, 2016, pages 436–441, 2016.
[92] A. Kamilaris, F. Gao, F. X. Prenafeta-Boldu, and M. I. Ali. Agri-iot: A semantic framework for internet of things-enabled smart farming applications. In 3rd IEEE World Forum on Internet of Things, WF-IoT 2016, Reston, VA, USA, December 12-14, 2016, pages 442–447, 2016.
[93] A. Kamilaris and M. I. Ali. Do "web of things platforms" truly follow the web of things? In 3rd IEEE World Forum on Internet of Things, WF-IoT 2016, Reston, VA, USA, December 12-14, 2016, pages 496–501, 2016.
[94] F. Gao, M. I. Ali, E. Curry, and A. Mileo. Qos-aware stream federation and optimization based on service composition. Int. J. Semantic Web Inf. Syst., 12(4):43–67, 2016.
[95] F. Gao, M. I. Ali, E. Curry, and A. Mileo. Qos-aware adaptation for complex event service. In Proceedings of the 31st Annual ACM Symposium on Applied Computing, Pisa, Italy, April 4-8, 2016, pages 1597–1604, 2016.
[96] Z. U. Shamszaman, M. I. Ali, and A. Mileo. On the need for adaptivity in rdf stream processing. In RDF Stream Processing Workshop (ESWC2015), 2015.
[97] M. Saleem, M. I. Ali, R. Verborgh, and A.-C. N. Ngomo. Federated query processing over linked data. Tutorial at ISWC, 2015.
[98] M. Saleem, M. I. Ali, A. Hogan, Q. Mehmood, and A. N. Ngomo. LSQ: the linked SPARQL queries dataset. In The Semantic Web - ISWC 2015 - 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11-15, 2015, Proceedings, Part II, pages 261– 269, 2015.
[99] M. Saleem, M. I. Ali, A. Hogan, Q. Mehmood, and A. N. Ngomo. The LSQ dataset: Querying for queries. In Proceedings of the ISWC 2015 Posters & Demonstrations Track co-located with the 14th International Semantic Web Conference (ISWC-2015), Bethlehem, PA, USA, October 11, 2015., 2015.
[100] M. Saleem, M. I. Ali, A. Hogan, Q. Mehmood, and A.-C. N. Ngomo. The lsq dataset: Querying for queries. In International Semantic Web Conference (Posters & Demos), 2015.
[101] F. Gao, M. I. Ali, and A. Mileo. Rdf stream processing for smart city applications. In RDF Stream Processing Workshop (ESWC2015), pages 1–3, 2015.
[102] M. I. Ali, N. Ono, M. Kaysar, K. Griffin, and A. Mileo. A semantic processing framework for iot-enabled communication systems. In International Semantic Web Conference, pages 241–258. Springer, 2015.
[103] M. I. Ali, F. Gao, and A. Mileo. Citybench: A configurable benchmark to evaluate rsp engines using smart city datasets. In International Semantic Web Conference, pages 374– 389. Springer, 2015.
[104] M. Ali, N. Ono, M. Kaysar, K. Griffin, and A. Mileo. A semantic processing framework for iot-enabled communication systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9367:241–258, 2015.
[105] R. Tönjes, P. Barnaghi, M. Ali, A. Mileo, M. Hauswirth, F. Ganz, S. Ganea, B. Kjærgaard, D. Kuemper, S. Nechifor, et al. Real time iot stream processing and large-scale data analytics for smart city applications. In poster session, European Conference on Networks and Communications, 2014.
[106] F. Gao, E. Curry, M. I. Ali, S. Bhiri, and A. Mileo. Qos-aware complex event service composition and optimization using genetic algorithms. In Service-Oriented Computing - 12th International Conference, ICSOC 2014, Paris, France, November 3-6, 2014. Proceedings, pages 386–393, 2014.
[107] F. Gao, M. I. Ali, and A. Mileo. Semantic discovery and integration of urban data streams. In Proceedings of the Fifth Workshop on Semantics for Smarter Cities a Workshop at the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Italy, October 19, 2014., pages 15–30, 2014.
[108] F. Gao, M. Ali, and A. Mileo. Semantic discovery and integration of urban data streams. CEUR Workshop Proceedings, 1280:15–30, 2014.
[109] M. I. Ali and A. Mileo. How good is your SPARQL endpoint? - A qos-aware SPARQL endpoint monitoring and data source selection mechanism for federated SPARQL queries. In On the Move to Meaningful Internet Systems: OTM 2014 Conferences - Confederated International Conferences: CoopIS, and ODBASE 2014, Amantea, Italy, October 27-31, 2014, Proceedings, pages 491–508, 2014.
[110] Q. Mehmood, M. I. Ali, O. Fagan, O. Friel, and A. Mileo. Semantically interlinked notification system for ubiquitous presence management. In On the Move to Meaningful Internet Systems: OTM 2013 Conferences - Confederated International Conferences: CoopIS, DOA-Trusted Cloud, and ODBASE 2013, Graz, Austria, September 9-13, 2013. Proceedings, pages 588– 605, 2013.
[111] S. Z. H. Gillani, M. I. Ali, and A. Mileo. Xsparql-viz: A mashup-based visual query editor for XSPARQL. In The Semantic Web: ESWC 2013 Satellite Events - ESWC 2013 Satellite Events, Montpellier, France, May 26-30, 2013, Revised Selected Papers, pages 219–224, 2013.
[112] M. I. Ali, N. Lopes, O. Friel, and A. Mileo. Update semantics for interoperability among xml, rdf and rdb. In Asia-Pacific Web Conference, pages 43–50. Springer, 2013.
[113] M. Ali, N. Lopes, O. Friel, and A. Mileo. Update semantics for interoperability among xml, rdf and rdb: A case study of semantic presence in cisco’s unified presence systems. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7808 LNCS:43–50, 2013.
[114] M. I. Ali. Optimizing data integration queries over web data sources (OPTIQ). In ICEIS 2012 - Proceedings of the 14th International Conference on Enterprise Information Systems, Volume 1, Wroclaw, Poland, 28 June - 1 July, 2012, pages 163–168, 2012.
[115] M. Ali. Optimizing data integration queries over web data sources (optiq). ICEIS 2012 - Proceedings of the 14th International Conference on Enterprise Information Systems, 1 DISI(AIDSS/-):163–168, 2012.
[116] M. I. Ali, R. Pichler, H.-L. Truong, and S. Dustdar. On integrating data services using data mashups. In British National Conference on Databases, pages 132–135. Springer, 2011.
[117] M. I. Ali, R. Pichler, H. L. Truong, and S. Dustdar. Incorporating data concerns into query languages for data services. In Enterprise Information Systems - 13th International Conference, ICEIS 2011, Beijing, China, June 8-11, 2011, Revised Selected Papers, pages 132–145, 2011.
[118] M. I. Ali, R. Pichler, H. L. Truong, and S. Dustdar. Data concern aware querying for the integration of data services. In ICEIS (1), pages 111–119, 2011.
[119] M. Ali, R. Pichler, H.-L. Truong, and S. Dustdar. Data concern aware querying for the integration of data services. ICEIS 2011 - Proceedings of the 13th International Conference on Enterprise Information Systems, 1 DISI:111–119, 2011.
[120] M. I. Ali, R. Pichler, H. L. Truong, and S. Dustdar. On using distributed extended xquery for web data sources as services. In Web Engineering, 9th International Conference, ICWE 2009, San Sebastián, Spain, June 24-26, 2009, Proceedings, pages 497–500, 2009.
[121] M. I. Ali, R. Pichler, H.-L. Truong, and S. Dustdar. Dexin: An extensible framework for distributed xquery over heterogeneous data sources. In International Conference on Enterprise Information Systems, pages 172–183. Springer, 2009.
[122] M. Ali, R. Pichler, H.-L. Truong, and S. Dustdar. Dexin: An extensible framework for distributed xquery over heterogeneous data sources. Lecture Notes in Business Information Processing, 24 LNBIP:172–183, 2009.