2024
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Nguyen, K., Nguyen, H., Nguyen, K., Truong, B., Phan, T., & Cao, H., (2024). Efficient and Concise Explanations for Object Detection with Gaussian-Class Activation Mapping Explainer. In The 37th Canadian Conference on Artificial Intelligence (Canadian AI 2024). Guelph, ON, Canada.
[DOI] -
Nuh Mih, A., Rahimi, A., Kawnine, A., Palma, F., Dubay, R., Wachowicz, M. & Cao, H. (2024). Achieving Pareto Optimality using Efficient Parameter Reduction for DNNs in Resource-Constrained Edge Environment. In The 37th Canadian Conference on Artificial Intelligence (Canadian AI 2024). Guelph, ON, Canada.
[DOI] -
Nguyen, T.T. H., Nguyen, V.T. K., Cao, Q.H., Truong, V.B., Nguyen, Q.K., & Cao, H., (2024). Enhancing the Fairness and Performance of Edge Cameras with Explainable AI. In The 42nd IEEE International Conference on Consumer Electronics (ICCE 2024). Las Vegas, NV, USA.
[DOI] -
Clement, T., Nguyen, T.T. H., Abdelaal, M., & Cao, H., (2024). XAI-Enhanced Semantic Segmentation Models for Visual Quality Inspection. In The 42nd IEEE International Conference on Consumer Electronics (ICCE 2024). Las Vegas, NV, USA.
[DOI] -
Nuh Mih, A., Cao, H., Kawnine, A., & Wachowicz, M. (2024). ECAvg: A Collaborative Edge-Cloud Approach using Averaged Weights. In The 42nd IEEE International Conference on Consumer Electronics (ICCE 2024). Las Vegas, NV, USA.
[DOI] -
Kawnine, A., Cao, H., Mih Nuh, A., & Wachowicz, M. (2024). Evaluating Multi-Global Server Architecture for Federated Learning. In The 42nd IEEE International Conference on Consumer Electronics (ICCE 2024). Las Vegas, NV, USA.
[DOI] -
Nguyen, H., Richard, R., Wachowicz, M., & Cao, H. (2024). Deciphering the Heartbeat: Towards an Explainable AI Approach using ECG Signals for Exploring Aging-in-Place Intelligence. In UNB Computer Science Research Expo. Fredericton, NB, Canada.
[DOI] -
Nguyen, H., Cao, H. (2024). Prototyping a Multimodal XAI Toolbox to Enhance Transparency of Black-box Systems. In UNB Computer Science Research Expo. Fredericton, NB, Canada.
[DOI] -
Rahimi, A., Khan, D., Sundaram, V., Laskey, M., & Cao, H. (2024). Online Fall Prediction with TinyML. In UNB Computer Science Research Expo. Fredericton, NB, Canada.
[DOI] -
Kawnine, A., Palma, F., & Cao, H. (2024). Leveraging Hierarchical Federated Learning Architecture for Temporal Analysis. In The 30th UNB Annual Graduate Research Conference. Fredericton, NB, Canada.
[DOI] -
Arid, H., Cao, H. & Palma, F. (2024). Do Developer Sentiment and Emotions Affect Software Quality? An Exploratory Study. In The 30th UNB Annual Graduate Research Conference. Fredericton, NB, Canada.
[DOI] -
Dey, K., Cao, H. & Palma, F. (2024). Syntactic and Semantic Analysis of REST, and GraphQL APIs to Assess and Compare their Linguistic. In The 30th UNB Annual Graduate Research Conference. Fredericton, NB, Canada.
[DOI]
2023
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Cao, H., Wachowicz, M., Richard, R. & Hsu, C-H. (2023). Fostering new Vertical and Horizontal IoT Applications with Intelligence Everywhere. In Collective Intelligence, 2(3).
[DOI] -
Hsu, C-H., Xu, M., Cao, H.,, Baghban, H., & Ali, A. B. M. S.(2023). Big Data Intelligence and Computing. (Edited Book). In Springer Nature. ISBN: 978-981-99-2233-8
[DOI] -
Mih Nuh, A., Cao, H., Wachowicz, M., Pickard, J. & Dubay, R. (2023). TransferD2: Automated Defect Detection Approach in Smart Manufacturing using Transfer Learning Techniques. In 2023 IEEE International Conference on Omni-Layer Intelligent Systems (IEEE COINS) IEEE. Berlin, Germany.
[DOI] -
Nuh Mih, A., Cao, H., (2023, April). EdgeAI for Defect Detection using Transfer Learning Techniques in the Context of Smart Manufacturing. In UNB Computer Science Research Expo . Fredericton, NB, Canada.
[DOI] -
Kawnine, A., Cao, H., (2023, April). Towards A Performance Evaluation for Federated Averaging on Edge Devices. In UNB Computer Science Research Expo . Fredericton, NB, Canada.
[DOI] -
Dadhich, S., Cao, H., (2023, April). Developing an IoT prototype for Climate Data Acquisition using Arduino. In UNB Computer Science Research Expo . Fredericton, NB, Canada.
[DOI]
2022
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Richard, R., Cao, H., & Wachowicz, M. (2022). EVStationSIM: An end-to-end platform to identify and interpret similar clustering patterns of EV charging stations across multiple time slices. In Applied Energy, 322, 119491.
[DOI] -
McCully, L., Cao, H., Wachowicz, M., Champion, S. & Williams, P.A.H. (2022). Discovering self-quantified patterns using multi-time window models. In Applied Computing and Informatics.
[DOI] -
Richard, R., Cao, H., & Wachowicz, M. (2022). A Spatial-temporal Comparison of EV Charging Station Clusters Leveraging Multiple Validity Indices. In Communications in Computer and Information Science book series.
[DOI]
2021
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Cao, H., Wachowicz, M. & Craig, J. (2021). Edge-Cloud Intelligence in Self-Diagnostic of Land Mobile Radio Systems. In Internet of Things (WF-IoT), 2021 IEEE 7rd World Forum on. IEEE. New Orleans, Louisiana, USA.
[DOI] -
Parise A., Callejo, M. A. M., Cao, H., & Wachowicz, M. (2021). Prophet model for forecasting occupancy presence in indoor spaces using non-intrusive sensors. In AGILE: GIScience Series 2, 1-13.
[DOI] -
Richard, R., Cao, H., & Wachowicz, M. (2021). An Automated Clustering Process for Helping Practitioners to Identify Similar EV Charging Patterns Across Multiple Temporal Granularities. In Proceedings of the 10th International Conference on Smart Cities and Green ICT Systems - SMARTGREENS (pp. 67-77). ISBN 978-989-758-512-8. Virtual Conference. (Acceptance Rate: 19%)
[DOI] ( Best Student Paper Award)
2020
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Richard, R., Cao, H., & Wachowicz, M. (2020). Discovering EV Recharging Patterns through an Automated Analytical Workflow. In 2020 IEEE International Smart Cities Conference (ISC2) (pp. 1-8). IEEE. Virtual Conference.
[DOI] -
Cao, H., & Wachowicz, M. (2020). A Holistic Overview of Anticipatory Learning for the Internet of Moving Things: Research Challenges and Opportunities. Special Issue State-of-the-Art in Spatial Information Science. In International Journal of Geo-Information 9(4), 272.
[DOI]
2019
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Cao, H., & Wachowicz, M. (2019). An Edge-Fog-Cloud Architecture of Streaming Analytics for Internet of Things Applications. Special Issue Edge/Fog/Cloud Computing in the Internet of Things. In Sensors 19(16), 3594.
[DOI] -
Cao, H., Wachowicz, M., Renso, C., & Carlini, E. (2019). Analytics Everywhere: generating insights from the Internet of Things. In IEEE Access, 7, 71749-71769.
[DOI] -
Cao, H., & Wachowicz, M. (2019). The design of an IoT-GIS platform for performing automated analytical tasks. In Computers, Environment and Urban Systems, 74, 23-40.
[DOI] -
Cao, H., & Wachowicz, M. (2019). Analytics Everywhere for streaming IoT data. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 18-25). IEEE. Granada, Spain.
[DOI] -
Cao, H., Brown M., Chen L., Smith R., & Wachowicz, M. (2019). Lessons learned from integrating batch and stream processing using IoT data. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 32-34). IEEE. Granada, Spain.
[DOI] -
Parise A., Callejo, M. A. M., Cao, H., Mendonca M., Kohli H., & Wachowicz, M. (2019). Indoor Occupancy Prediction using an IoT Platform. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 26-31). IEEE. Granada, Spain.
[DOI]
2018
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Cao, H., Wachowicz, M., Renso, C., & Carlini, E. (2018). An edge-fog-cloud platform for anticipatory learning process designed for internet of mobile things In arXiv: 1711.09745
[arXiv]
2017
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Cao, H., Wachowicz, M., & Cha, S. (2017, December). Developing an edge computing platform for real-time descriptive analytics. In Big Data (Big Data), 2017 IEEE International Conference on (pp. 4546-4554). IEEE. Boston, MA, USA.
[DOI] -
Maduako, I., Cao, H., Hernandez, L., & Wachowicz, M. (2017, October). Combining edge and cloud computing for mobility analytics. In Proceedings of the Second ACM/IEEE Symposium on Edge Computing (p. 22). ACM. San Jose, CA, USA.
[DOI] -
Hernandez, L., Cao, H., & Wachowicz, M. (2017, October). Implementing an Edge-Fog-Cloud architecture for stream data management. In Fog World Congress (FWC), 2017 IEEE (pp. 1-6). IEEE. Santa Clara, CA, USA.
[DOI] -
Cao, H., & Wachowicz, M. (2017, August). The design of a streaming analytical workflow for processing massive transit feeds. In 2nd International Symposium on Spatiotemporal Computing. Harvard University, Cambridge, MA, USA.
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Cao, H. (2017). What is the next innovation after the internet of things?. arXiv preprint arXiv:1708.07160. (Technical Report)
2016
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Cha, S., Ruiz, M. P., Wachowicz, M., Tran, L. H., Cao, H., & Maduako, I. (2016, December). The role of an IoT platform in the design of real-time recommender systems. In Internet of Things (WF-IoT), 2016 IEEE 3rd World Forum on (pp. 448-453). IEEE. Reston, Virginia, USA
[DOI] -
Cao, H., Maduako, I., Cavalheri, E., Brideau, E., & Wachowicz, M. (2016, September). The Role of Graph Databases in Geomatics. In Geomatics Atlantics 2016, Fredericton, NB, Canada.
[DOI] -
Cao, H., Maduako, I., Cavalheri, E., Brideau, E., & Wachowicz, M. (2016, September). How can graph databases improve transit systems? In UNB Research Showcase, University of New Brunswick, Fredericton, NB, Canada.
[DOI]
2015
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Cao, V. H., Chu, K. X., Le-Khac, N. A., Kechadi, M. T., Laefer, D., & Truong-Hong, L. (2015, July). Toward a new approach for massive LiDAR data processing. In Spatial Data Mining and Geographical Knowledge Services (ICSDM), 2015 2nd IEEE International Conference on (pp. 135-140). IEEE.
[DOI]
2012
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Lung, V. D., Van Hung, C., Loc, N. P., & Quoc, N. V. (2012, December). Analysis of Vietnamese tones to optimize database in speech synthesis using unit selection method. In Signal Processing and Information Technology (ISSPIT), 2012 IEEE International Symposium on (pp. 000043-000048). IEEE.
[DOI]