Dr. Amir Abbas Kazemzadeh
Ph.D. Computing, emphasis in Data Science, Boise State University, 2019-2023
Ph.D. Chemical Engineering, Nanyang Technological University, 2013-2017
M.S. Bioprocess Engineering, University Technology Malaysia, 2011-2012
M.S. Chemical Engineering, Sharif University of Technology, 2004-2006
B.S. Chemical Engineering, Persian Gulf University, 2000-2004
Advisor: Dr. Mahmood Mamivand
Post-graduation employment: Advanced Modeling Engineer/Data Scientist at Micron Technology
During my first master’s degree in Chemical Engineering (Process Engineering) from Sharif University of Technology, I worked on optimization of crude oil distillation unit in the refineries to increase the unit operation efficiency and reduction of energy consumption. Both analytical solutions and numerical simulations have been performed to analyze heat and mass transfer within the crude oil distillation equipment such as distillation towers, condensers, boilers, and fluid catalytic cracker. After finishing my first master’s degree, I got financial support from University Technology, to pursue my education and research in another master’s in Bioprocess Engineering. I extracted protein from plants to substitute with Fetal Bovine Serum that is provided from the animal’s blood. Then, I got full financial support from Nanyang Technological University (NTU) to pursue my first Ph.D. in Chemical Engineering. During my Ph.D. degree, I applied machine learning and data science to process engineering and biomedical engineering. I developed a neural network to predict the change of particle size distribution in a gas-solid fluidized bed. Moreover, I applied neural networks to make a model that can help us to design the optimum carrier for dry powder inhalation. After that, I got a grant from Iran’s National Elites Foundation to peruse my research as a postdoctoral to work on bone cement to solve the current issues about curing time. We synthesized Polymethylmethacrylate (PMMA) and calcium phosphate cement (CPCs) with shorter curing time. At the same time, I was working as an adjunct professor at the university. Then, I came to Rowan University in the United State to work on biocompatible polymers for biomedical electronic devices. I could synthesize a flexible conductive biocompatible material with a combination of poly(glycerol sebacate) acrylate (PGSA) and some metals including zinc, iron, and magnesium.
Due to my background in machine learning, I decided to go through the detail of this state-of-the-art field. Therefore, I got full financial support from Boise State University to get another Ph.D. in the interdisciplinary filed called Computing. During my application for Boise State University, I wrote a proposal with my current advisor, Dr. Mamivand, about the design of a new permanent magnet for high-temperature NASA and aviation applications. We got Idaho NASA EPSCoR Research Initiation Grant. This project has two main parts: 1- Simulation of Alnico as a permanent magnet by phase-field modeling to find its microstructure for different process conditions and compositions; 2- Finding the best microstructure by deep learning which can provide the optimum magnetic properties. In general, I will try to apply data analysis as a powerful tool in the design of materials in my current Ph.D. project in Computational Materials Design Lab (https://mamivand.weebly.com/people.html).