Publications and Outputs

Demos

Initial prototype concept of DT for Smart Factory: Automation and Monitoring
Updated version (May 2020)
Initial prototype concept of DT for Structural Health Monitoring (Bridges)

Publications

Industry 4.0 and Smart Factory

  1.  S. Mihai, W. Davis, R. Trestian, V. H. Dang, P. Towakel, M. Karamanoglu, B. Barn, D. S. Shetve, R. V. Prasad, H. Venkataraman, and H. X. Nguyen, “Digital Twins: A Survey on Enabling Technologies, Challenges and Future Prospects,” IEEE Communications Surveys & Tutorials, 2021, submitted.
  2. Son V. Dinh, Tiep Hoang, Ramona Trestian, Huan X. Nguyen, “Unsupervised Deep Learning-based Reconfigurable Intelligent Surface Aided Broadcasting Communications in Industrial IoTs,” IEEE Internet of Things Journal, 2021, submitted.
  3. William Davis, Mahnoor Yaqoob, Stefan Mihai, Dang Viet Hung, Ramona Trestian, Mehmet Karamanoglu, Balbir Barn and Huan X. Nguyen, “An Innovative Blockchain-based Traceability Framework for Industry 4.0 Cyber-Physical Factory” in Proc. 18th International Conference on Manufacturing Research (ICMR2021).
  4. M. Raza, P. M. Kumar, H. Dang-Viet, W. Davis, H. X. Nguyen, and R. Trestian, “A Digital Twin Framework for Industry 4.0 Enabling Next-Gen Manufacturing,” in Proc. 2020 9th Int. Conf. Industrial Technology and Management (ICITM 2020), Oxford, UK, Feb. 2020 (link)
  5. S. Mihai, W. Davis, H. V. Dang, R. Trestian, M. Karamanoglu, B. Barn, R. V. Prasad, H. Venkataraman, and H. Nguyen, “A Digital Twin Framework for Predictive Maintenance in Industry 4.0,” in Proc. 2020 International Conference on High Performance Computing & Simulation (HPCS 2020) , Dec. 2020.
  6. Dattaprasad S. Shetve, Raja V. Prasad, Ramona Trestian, Huan X Nguyen and Hrishikesh Venkataraman, “CATS: Cluster-Aided Two-Step Approach for Anomaly Detection in Smart Manufacturing,” in Proc. The 2020 Fourth International Conference on Computing and Network Communications (CoCoNet’20)

Structural Health Monitoring

  1. Hung V. Dang, Mallik Tatipamula, and Huan X. Nguyen, “Cloud-based Digital Twinning for Structural Health Monitoring Using Deep Learning,” IEEE Transactions on Industrial Informatics, accepted, 2021.
  2. Hung V. Dang, Stefan Viorel Mihai, William Davisa, Ramona Trestiana and Huan X. Nguyen, “Multi-tasking structural damage detection of spatial truss structure using image-based deep learning approach,” Structures, 2021, submitted.
  3. Hung V. Dang, Khuong N. Le, Thang T. Nguyen, Huan X. Nguyen, “Fast reliability analysis of structures under white noise excitations using Transformer-enhanced surrogate model coupled with importance sampling,” Structural Safety, 2021, submitted
  4. Hung V. Dang, Ramona Trestian, Thanh Bui-Tien, and Huan X. Nguyen, “Probabilistic Method for Time-Varying Reliability Analysis of Structure via Variational Bayesian Neural Network,” Structures, vol. 34, pp. 3703-3715, 2021.
  5. Hung V. Dang, William Davis, Stefan V. Mihai, Ramona Trestian and Huan X. Nguyen, “Forecasting dynamic response of the structure under time-varying excitation using temporal deep learning architecture enhanced by attention mechanism,” Computer & Structure, submitted, 2021
  6. H. V. Dang, M. Raza, H. Tran-Ngoc, T. Bui-Tien, and H. X. Nguyen, “Connection stiffness reduction analysis in steel Bridge via deep convolutional neural network,” Structural Engineering and Mechanics, vol. 77, no. 4, pp. 485-508, Feb. 2021.
  7. H. V. Dang, M. Raza, V. T. Nguyen, T. T., Bui, and H. X. Nguyen, “Deep Learning-Based Detection of Structural Damage Using Time-Series Data,” Structure and Infrastructure Engineering, 2020. DOI: 10.1080/15732479.2020.1815225
  8. H. V. Dang, H. Tran-Ngoc, N. V. Tung, B. T. Thanh, G. De Roeck, H. X. Nguyen, “Data-Driven Structural Health Monitoring using Feature Fusion and Hybrid Deep Learning,” in IEEE Transactions on Automation Science and Engineering, vol. 18, no. 4, pp. 2087-2103, Oct. 2021, DOI: 10.1109/TASE.2020.3034401
  9. L. Nguyen-Ngoc, H. Tran-Ngoc , T. Bui-Tien, M. A. Wahab, H. X. Nguyen, and G. De Roeck, “Damage detection in structures using Particle Swarm Optimization combined with Machine Learning,” Computers, Materials & Continua, accepted, 2020.
  10. H Tran-Ngoc, Samir Khatir, G De Roeck, T Bui-Tien, M Abdel Wahab, “An efficient artificial neural network for damage detection in bridges and beam-like structures by improving training parameters using cuckoo search algorithm”, Engineering Structures; 2019.

5G/6G and other Disruptive Applications

  1. H. X. Nguyen, R. Trestian, D. To and M. Tatipamula, “Digital Twin for 5G and Beyond,” in IEEE Communications Magazine, vol. 59, no. 2, pp. 10-15, February 2021, doi: 10.1109/MCOM.001.2000343.
  2. S. Mihai, P. Shah, G. Mapp, H. X. Nguyen, and R. Trestian, “Towards autonomous driving: A machine learning-based pedestrian detection system using 16-layer LiDAR,” to appear in Proc. the 13th International Conference on Communications (COMM2020), Bucharest, Jun. 2020.
  3. K. Ali, H. X. Nguyen, Q.-T. Vien, P. Shah, M. Raza, V. Paranthaman, B. Errahmadi, M. Awais, S. Islam, J. Rodrigues, “Review and Implementation of Resilient Public Safety Networks: 5G, IoT and Emerging Technologies,” IEEE Networks, Nov. 2020
  4. Geili T. A. Elsanousi, Xin-She Yang, Tuan Le, and Huan X. Nguyen, “The Road Map to Smart Waves With Digital Twin,” IEEE Vehicular Technology Magazine, submitted, 2021
  5. Mahnoor Yaqoob,  Mallik Tatipamula, Ramona Trestian, and Huan X. Nguyen, “Self-Evolving Digital Twin-driven Future Wireless Networks with Smart E2E Network Slicing,” IEEE Software, submitted, 2021
  6. Son V. Dinh, Ramona Trestian, Huan X. Nguyen, “Joint Beamforming Design for Distributed Reconfigurable Intelligent Surfaces-Aided Broadcast Communications with Deep Learning,” ICC’22, submitted.

Fundamental Concepts

  1. T. Clark, B. Barn, V. Kulkarni, and S. Barat, “Language Support for Multi Agent Reinforcement Learning,” in Proc. 13th Innovations in Software Engineering Conference (Formerly known as India Software Engineering Conference), Feb. 2020. (download)
  2. S. Barat, V. Kulkarni, T. Clark, and B. Barn, “An actor based simulation driven digital twin for analyzing complex business systems,” in Proc. 2019 Winter Simulation Conference (WSC) (pp. 157-168), Dec. 2019.