Biography:

Dr. Kordijazi is an interdisciplinary engineer with teaching and research interests in the field of applied AI for the design, metrology, and manufacturing of advanced materials. He received his Ph.D. in Industrial & Manufacturing Engineering from the University of Wisconsin, Milwaukee, in 2021. His doctoral research focused on applying AI/ML and statistical techniques for the property predictions of cast alloys and nanocomposites. He subsequently joined The State University of New York (SUNY) Polytechnic Institute as a postdoctoral associate. His current research focuses on the application of computer vision algorithms for the metrology of new generations of nanoscale semiconductor materials. He has published over 30 peer-reviewed publications. He is a recipient of the Graduate Student Excellence Fellowship and Chancellor’s Graduate Student Awards from the University of Wisconsin, Milwaukee, and two Best Paper Awards from the American Foundry Society.

 SELECTED PUBLICATIONS

Journal articles:

Alrfou, K., Kordijazi, A., Rohatgi, P. & Zhao, T. (2022). Synergy of unsupervised and supervised machine learning methods for the segmentation of the graphite particles in the microstructure of ductile iron, Materials Today Communications, 30, 103174.

Rohatgi, M., & Kordijazi, A., Application of machine learning to mechanical properties of copper-graphene composites, MRS Communications, 13, 111–116

Kordijazi, A., Behera, S., Patel, D., Rohatgi, P., & Nosonovsky, M. (2021). Predictive Analysis of Wettability of Al–Si Based Multiphase Alloys and Aluminum Matrix Composites by Machine Learning and Physical Modeling. Langmuir, 37(12), 3766-3777.

Kordijazi, A., Zhao, T., Zhang, J., Alrfou, K., & Rohatgi, P. (2021). A Review of Application of Machine Learning in Design, Synthesis, and Characterization of Metal Matrix Composites: Current Status and Emerging Applications. JOM, 1-15.

Hasan, M. S., Kordijazi, A., Rohatgi, P. K., & Nosonovsky, M. (2021). Triboinformatic modeling of dry friction and wear of aluminum base alloys using machine learning algorithms. Tribology International, 161, 107065.

Hasan, M. S., Kordijazi, A., Rohatgi, P. K., & Nosonovsky, M. (2021). Triboinformatics approach for friction and wear prediction of Al-Graphite composites using machine learning methods. Journal of Tribology, 144(1), 011701.

Kordijazi, A., Weiss, D., Das, S., Behera, S., Roshan, H. M., & Rohatgi, P. (2021). Effect of solidification time on microstructure, wettability, and corrosion properties of A205-T7 aluminum alloys. International Journal of Metalcasting, 15(1), 2-12.

Sadabadi, H., Allahkaram, S. R., Kordijazi, A., Akbarzadeh, O., & Rohatgi, P. K. (2021). Structural characterization of LaCoO3 perovskite nanoparticles synthesized by sol–gel autocombustion method. Engineering Reports, 3(6), e12335.

Kordijazi, A., Roshan, H. M., Dhingra, A., Povolo, M., Rohatgi, P. K., & Nosonovsky, M. (2020). Machine-learning methods to predict the wetting properties of iron-based composites. Surface Innovations, 9(2–3), 111-119.

Kordijazi, A., Behera, S. K., Suri, S., Wang, Z., Povolo, M., Salowitz, N., & Rohatgi, P. (2020). Data-driven modeling of wetting angle and corrosion resistance of hypereutectic cast Aluminum-Silicon alloys based on physical and chemical properties of surface. Surfaces and Interfaces, 20, 100549.

Das, S., Kordijazi, A., Akbarzadeh, O., & Rohatgi, P. K. (2020). An innovative process for dispersion of graphene nanoparticles and nickel spheres in A356 alloy using pressure infiltration technique. Engineering Reports, 2(1), e12110.

Kordijazi, A. (2019). Optimization of Ni–P–Zn electroless bath and investigation of corrosion resistance of as-plated coatings. Materials Research Express, 6(9), 096565.

Book chapter:

Pivehzhani, O. A., Kordijazi, A., Sagadevan, S., Moosavi, S., Babadi, A. A., Wahab, Y. A., ... & Chowdhury, Z. Z. (2020). Syngas to Green Fuel Conversion: Nanocatalysis Approach. In Advanced Heterogeneous Catalysts Volume 1: Applications at the Nano-Scale (pp. 545-579). American Chemical Society.

Conference articles:

Kordijazi, A., Weiss, D., Das, S., & Rohatgi, P. (2021). Manufacturing A206 Aluminum Alloy by Step Sand Casting: Effect of Solidification Time on Mechanical and Surface Properties of the Cast Samples Using Experimental and Simulation Results. In Light Metals 2021: 50th Anniversary Edition (pp. 147-157). Springer International Publishing.

Kordijazi, A., Behera, S., Jamet, A., Fernández, A., Rohatgi, P. (2021). Predictive analysis of water wettability and corrosion resistance of secondary AlSi10MnMg(Fe) alloy manufactured by vacuum assisted high pressure die casting. American Foundry Society Transaction, 129, 1-12.  

Ullberg, H., Rane, K., Kordijazi, A., Rohatgi, P. (2021). Cast magnesium foam for energy absorption and bone regrowth. American Foundry Society Transaction, 129, 1-11.