Education:
Assist. Prof. Dr. Ammar Alsheghri holds a Ph.D. in Materials Engineering from McGill University, Canada, which he completed in May 2020 with a perfect GPA of 4.0/4.0. During his Ph.D., he was awarded the prestigious Graduate Excellence Fellowship. He earned his Master of Science in Mechanical Engineering from the Masdar Institute of Science and Technology, Khalifa University, UAE, in collaboration with the Massachusetts Institute of Technology (MIT), USA, in May 2015, also achieving a GPA of 4.0/4.0. Dr. Alsheghri obtained his Bachelor of Science in Mechanical Engineering from Khalifa University, UAE, in June 2013, graduating with the highest honors and an impressive GPA of 3.98/4.0.
Professional Experience:
Assist. Prof. Dr. Ammar Alsheghri has an extensive professional background in both academia and industry. Currently, he is an Assistant Professor in the Department of Mechanical Engineering at King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia, a position he has held since August 2023. Prior to this, he served as a Postdoctoral Fellow at Polytechnique Montreal from 2020 to 2022, where he worked on geometric deep learning for dental applications, collaborating with industrial partners to develop customized dental crowns. Dr. Alsheghri also contributed as a Research Assistant at McGill University from 2015 to 2020, where his thesis focused on bioinspired design and optimization of materials for dentures and cellular structures. He has previous experience as a Research Assistant at Masdar Institute of Khalifa University, working on self-healing materials using finite element analysis. In addition to his academic roles, Dr. Alsheghri has substantial industrial experience. He was a Technology Developer at Dragonfly, part of the Comet Group, from 2022 to 2023, focusing on AI-driven scientific imaging and software development. He also worked as a Research & Development Consultant and Intern at Dragonfly, leading projects involving artificial intelligence for material image processing and mechanical properties analysis. His industry roles also include an internship at Diehl Aircabin GmbH in Germany, where he performed stress analysis for the Airbus A380 ceiling and assisted with composite material testing.
Research Interests:
Assist. Prof. Dr. Ammar Alsheghri’s research interests are deeply rooted in the intersection of materials engineering, mechanical engineering, and cutting-edge technologies such as artificial intelligence. His work focuses on bioinspired design and optimization of materials, particularly for dental applications, including the development of dentures and customized prosthetic structures. Dr. Alsheghri is also highly engaged in the field of geometric deep learning, specifically 3D deep learning for applications in dental segmentation and the generation of dental crowns from scanned dental arches. His expertise extends to self-healing materials, mechanics modeling, and finite element analysis (FEA), which he has applied to enhance the structural properties of materials. Additionally, he is interested in AI-driven image processing and computational mechanics, applying these techniques to scientific imaging and material analysis, with the aim of optimizing mechanical properties and structures for various engineering applications.
Skills:
Assist. Prof. Dr. Ammar Alsheghri possesses a diverse and advanced skill set that spans both academia and industry. He is highly proficient in materials engineering, with expertise in bioinspired design and optimization of materials, specifically for dental and prosthetic applications. Dr. Alsheghri excels in finite element analysis (FEA) and computational mechanics, which he has applied to projects involving self-healing materials and lightweight structures. He is also skilled in computer-aided design (CAD) and 3D modeling, having worked on the design and development of dental prostheses and optimized cellular structures. In addition, Dr. Alsheghri has strong capabilities in artificial intelligence, particularly in geometric deep learning and 3D deep learning, which he has applied to the segmentation of dental structures and the design of customized dental crowns. He is experienced in data analysis, image processing, and the use of AI for scientific imaging. His skills in laboratory testing and materials characterization complement his technical expertise, allowing him to contribute to multidisciplinary research and development efforts.
Conclusion:
With an outstanding academic record, a strong research portfolio, multiple patents, and a track record of successful collaborations in both academia and industry, Dr. Ammar Alsheghri stands out as a highly qualified candidate for the Best Researcher Award. His interdisciplinary expertise, particularly in materials engineering, AI, and bioinspired design, positions him as a leader in advancing research and technology in both mechanical and biomedical engineering fields.
Publication Top Noted:
- Removable partial denture alloys processed by laser‐sintering technique
- Authors: O Alageel, MN Abdallah, A Alsheghri, J Song, E Caron, F Tamimi
- Journal: Journal of Biomedical Materials Research Part B: Applied Biomaterials
- Volume/Issue: 106(3)
- Pages: 1174-1185
- Year: 2018
- DOI: 10.1002/jbm.b.33910
- Design and cost analysis of a solar photovoltaic powered reverse osmosis plant for Masdar Institute
- Authors: A Alsheghri, SA Sharief, S Rabbani, NZ Aitzhan
- Journal: Energy Procedia
- Volume: 75
- Pages: 319-324
- Year: 2015
- DOI: 10.1016/j.egypro.2015.07.439
- Finite element implementation and application of a cohesive zone damage-healing model for self-healing materials
- Authors: AA Alsheghri, RKA Al-Rub
- Journal: Engineering Fracture Mechanics
- Volume: 163
- Pages: 1-22
- Year: 2016
- DOI: 10.1016/j.engfracmech.2016.05.020
- High strength brushite bioceramics obtained by selective regulation of crystal growth with chiral biomolecules
- Authors: H Moussa, W Jiang, A Alsheghri, A Mansour, A El Hadad, H Pan, R Tang, …
- Journal: Acta Biomaterialia
- Volume: 106
- Pages: 351-359
- Year: 2020
- DOI: 10.1016/j.actbio.2020.01.004
- Composition and characteristics of trabecular bone in osteoporosis and osteoarthritis
- Authors: I Tamimi, ARG Cortes, JM Sánchez-Siles, JL Ackerman, …
- Journal: Bone
- Volume: 140
- Pages: 115558
- Year: 2020
- DOI: 10.1016/j.bone.2020.115558
- Thermodynamic-based cohesive zone healing model for self-healing materials
- Authors: AA Alsheghri, RKA Al-Rub
- Journal: Mechanics Research Communications
- Volume: 70
- Pages: 102-113
- Year: 2015
- DOI: 10.1016/j.mechrescom.2015.09.007
- Determining the retention of removable partial dentures
- Authors: O Alageel, AA Alsheghri, S Algezani, E Caron, F Tamimi
- Journal: Journal of Prosthetic Dentistry