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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Alsheghri, A., Zhang, Y., Keren, J., Cheriet, F., & Guibault, F. (2025). Automatic margin line extraction using 3D deep learning on digital surface models of prepared teeth for crown generation. Computers in Biology and Medicine, 196(C), 110960. External link
Alsheghri, A., Zhang, Y., Ghadiri, F., Keren, J., Cheriet, F., & Guibault, F. (2025). Mesh-based segmentation for automated margin line generation on incisors receiving crown treatment. Mathematics and Computers in Simulation, 239, 716-728. External link
Rodriguez, J., Jian, X., Panigrahi, S. S., Zhang, T., Feizi, A., Puri, A., Kalkunte, A., Savard, F., Masry, A., Nayak, S., Awal, R., Massoud, M., Abaskohi, A., Li, Z., Wang, S., Noel, P.-A., Richter, M. L., Vadacchino, S., Agarwal, S., ... Rajeswar, S. (2025, April). BIGDOCS : an open dataset for training multimodal models on document and code tasks [Paper]. 13th International Conference on Learning Representations (ICLR 2025), Singapore, Singapore. External link
Chafi, I., Zhang, Y., Ladini, Y., Cheriet, F., Keren, J., & Guibault, F. (2025, April). Exploring the Use of Generative Adversarial Networks for Automated Dental Preparation Design [Paper]. 22nd International Symposium on Biomedical Imaging (ISBI 2025), Houston, TX, USA. External link
Chafi, I., Hosseinimanesh, G., Alsheghri, A., Ladini, Y., Zhang, Y., Abbasi Moghadam, N., Elfassy, L., Carrière, V.-M., Haidar, S., Keren, J., Cheriet, F., & Guibault, F. (2025, February). Intellident: an AI-based online automated framework for dental crown generation [Paper]. SPIE Medical Imaging, San Diego, CA, USA (8 pages). External link
Alsheghri, A., Zhang, Y., Hosseinimanesh, G., Keren, J., Cheriet, F., & Guibault, F. (2024). Robust Segmentation of Partial and Imperfect Dental Arches. Applied Sciences, 14(23), 10784 (20 pages). Available
Chafi, I., Cheriet, F., Keren, J., Zhang, Y., & Guibault, F. (2024, February). 3D generation of dental crown bottoms using context learning [Presentation]. In SPIE Medical Imaging, 2024, San Diego, California, United States. External link
Wu, N., Liu, B., Zhang, Y., Allam, A. A., Rady, A., Altoom, N. G., Dar, A. A., Qu, R., Wang, Z., & Sun, P. (2024). Environmental fate of benzotriazole 2-(2H-benzotriazol-2-yl)-4,6-di-tert-pentylphenol (UV-328) on the surface of plastic films in soil: Migration and phototransformation. Journal of Environmental Chemical Engineering, 12(2), 112093 (7 pages). External link
Hosseinimanesh, G., Ghadiri, F., Alsheghri, A., Zhang, Y., Keren, J., Cheriet, F., & Guibault, F. (2023, February). Improving the quality of dental crown using a transformer-based method [Paper]. Medical Imaging 2023 : Physics of Medical Imaging,, San Diego, CA, USA (8 pages). External link
Alsheghri, A., Ghadiri, F., Zhang, Y., Lessard, O., Keren, J., Cheriet, F., & Guibault, F. (2022, February). Semi-supervised segmentation of tooth from 3D scanned dental arches [Poster]. SPIE Medical Imaging 2022 : Image processing, San Diego, California, USA (6 pages). External link
Avraam, C., Zhang, Y., Sankaranarayanan, S., Zaitchik, B., Moynihan, E., Juturu, P., Neff, R., & Siddiqui, S. (2021). Optimization-Based Systems Modeling for the Food-Energy-Water Nexus. Current Sustainable/Renewable Energy Reports, 8(1), 4-16. External link
Sankaranarayanan, S., Zhang, Y., Carney, J., Nigussie, Y., Esayas, B., Simane, B., Zaitchik, B., & Siddiqui, S. (2020). What Are the Domestic and Regional Impacts From Ethiopia's Policy on the Export Ban of Teff? Frontiers in Sustainable Food Systems, 4, 4 (14 pages). Available
Trabelsi, C., Bilaniuk, O., Zhang, Y., Serdyuk, D., Subramanian, S., Santos, J. F., Mehri, S., Rostamzadeh, N., Bengio, Y., & Pal, C. J. (2018, April). Deep complex networks [Paper]. 6th International Conference on Learning Representations (ICLR 2018), Vancouver, BC, Canada (19 pages). External link
Cheng, C., Qi, M., Zhang, Y., & Rousseau, L.-M. (2018). A two-stage robust approach for the reliable logistics network design problem. Transportation Research Part B: Methodological, 111, 185-202. External link
Devals, C., Zhang, Y., Dompierre, J., Vu, T. C., Mangani, L., & Guibault, F. (2014). 3D Casing-Distributor Analysis for Hydraulic Design Application. International Journal of Fluid Machinery and Systems, 8(3), 142-154. External link
Vu, T. C., Devals, C., Zhang, Y., Nennemann, B., & Guibault, F. (2011). Steady and unsteady flow computation in an elbow draft tube with experimental validation. International Journal of Fluid Machinery and Systems, 4(1), 85-96. External link
