Assoc. Prof. Dr. Niaz Abdolrahim | Best Researcher Award

Assoc. Prof. Dr. Niaz Abdolrahim | Best Researcher Award

University of Rochester | United States

Dr. Niaz Abdolrahim is an accomplished materials scientist and Assistant Professor in the Department of Mechanical Engineering at the University of Rochester, where she leads pioneering research in multiscale modeling, nanomechanics, and computational materials science. She earned her Ph.D. in Mechanical Engineering and has since developed a strong research portfolio that integrates atomistic simulations, machine learning, and continuum mechanics to study deformation mechanisms, structural phase transformations, and the design of high-performance nanostructured materials. With over 44 published documents, more than 717 citations, and an h-index of 16, her scholarly contributions have been widely recognized in the fields of materials modeling and nanostructure design. Dr. Abdolrahim has secured multiple NSF-funded projects, including the study of stress-assisted phase transformations and data-driven analysis of lattice dynamics. Her work has been published in prestigious journals such as Acta Materialia, npj Computational Materials, Physical Review B, and ACS Applied Nano Materials. Her research interests encompass nanostructured metals, deformation physics, data-driven materials design, and high-performance alloys. Dr. Abdolrahim’s innovative contributions continue to advance the understanding of mechanical behavior in nanoscale systems and establish her as a leading figure in computational materials science and multiscale simulation.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Mostafa, A., Qian, S., Li, F., Rabkin, E., & Abdolrahim, N. (2026). Bending-induced phase transformations and penta-twinning in molybdenum: From nano to microscale. Acta Materialia, 264, 121646. https://doi.org/10.1016/j.actamat.2025.121646

Karami, S., Kum, T. B., Kirmani, A. R., & Abdolrahim, N. (2025). Proton radiation effects in indium oxide using cascade molecular dynamics simulations. APL Energy, 4(9), 0266752. https://doi.org/10.1063/5.0266752

Alvarez, A., Abdolrahim, N., & Singh, S. (2025). Anomalous elastic softening in ferroelectric hafnia under pressure. Physical Review B, 111(6), 064106. https://doi.org/10.1103/PhysRevB.111.064106

Mostafa, A., Vu, L., Guo, Z., Shargh, A. K., Dey, A., Askari, H., & Abdolrahim, N. (2024). Phase-transformation assisted twinning in molybdenum nanowires. Computational Materials Science, 237, 113273. https://doi.org/10.1016/j.commatsci.2024.113273

Salgado, J. E., Lerman, S., Du, Z., Xu, C., & Abdolrahim, N. (2023). Automated classification of big X-ray diffraction data using deep learning models. npj Computational Materials, 9(1), 214. https://doi.org/10.1038/s41524-023-01164-8

Prof. Phan Nguyen | Best Researcher Award

Prof. Phan Nguyen | Best Researcher Award

Hanoi University of Industry | Vietnam

Prof. Nguyen Huu Phan is a distinguished researcher and lecturer in the Faculty of Mechanical Engineering at Hanoi University of Industry, Vietnam, known for his extensive contributions to advanced manufacturing processes, particularly electrical discharge machining (EDM), powder-mixed EDM (PMEDM), micro-EDM, vibration-assisted machining, and multi-criteria optimization. He earned his Doctorate from Thai Nguyen University in 2016 and has since established a strong research record with 25 Scopus-indexed documents, 351 citations, and an h-index of 11, reflecting the impact of his work in machining optimization, dielectric modifications, surface engineering, process modelling, and decision-making methodologies such as Taguchi, TOPSIS, DEAR, and grey relational analysis. His research has been published in leading international journals including Surface Review and Letters, International Journal of Advanced Manufacturing Technology, Materials and Manufacturing Processes, Metals, and International Journal of Modern Physics B. He has collaborated with global researchers on innovations involving coated electrodes, powder-mixed dielectrics, and performance enhancement of EDM for difficult-to-machine materials like Ti-6Al-4V. Dr. Phan also received funding from the National Foundation for Science and Technology Development for his work on optimizing PMEDM process parameters. His ongoing research continues to advance precision machining technologies and sustainable manufacturing solutions.

Profiles : Google ScholarOrcid | Scopus

Featured Publications

Dua, T. V., Phan, N. H., Huy, T. Q., & Toan, N. D. (2025). Investigation of electrode wear and surface quality in powder mixed electrical discharge machining (PMEDM) with low-frequency vibration applied to the workpiece. Surface Review and Letters.

Nguyen, H. P., Shirguppikar, S., Ganachari, V., Ly, N. T., & Toan, N. D. (2025). Optimization of surface roughness in AISI D-3 machining using powder-mixed electrical discharge machining with aluminum powder. Surface Review and Letters.

Pham, V. H., Phan, N. H., Shirguppikar, S., & Toan, N. D. (2025). Enhancing EDM performance with multi-objective decision-making using copper-coated aluminum electrodes and TOPSIS methodology for Ti-6Al-4V machining. International Journal of Modern Physics B.

Phan, N. H., Dong, P. V., Thinh, H. X., Asghari Ilani, M., Ly, N. T., Hai, H. T., & Tam, N. C. (2024). Review: Enhancing additive digital manufacturing with supervised classification machine learning algorithms. The International Journal of Advanced Manufacturing Technology.

Phan, N. H., Shirguppikar, S., & Toan, N. D. (2024). Optimizing micro-EDM with carbon-coated electrodes: A multi-criteria approach. International Journal of Modern Physics B.