About

Amin Sabzehzar is a double majors student in MBA and M.Sc. in Mechanical Engineering at the University of Nevada, Reno (UNR). His biggest obsession is to help manufacturing plant and industries with innovative design and use of data to find the solution for unsolved problems.

In 2007, graduating from high school with a high GPA eased his way through getting admitted in the third ranked school in Iran, Isfahan University of Technology (IUT) to major in Mechanical Engineering. For the first couple of years, passing engineering courses developed his critical thinking, mathematical and statistical knowledge. In the last year of my bachelor degree, he worked on servo hydraulic system for his bachelor project, in which he succeeded in connecting the system with the LabVIEW software to get data online (position, force, and speeding data) from the main controller.

In 2011, he got admitted at University of Tehran in master of Manufacturing Engineering. In the first year, during his coursework and projects, he learnt about lean production, Just in Time (JIT) manufacturing, production flow optimization, risk analysis, inventory management, six-sigma techniques, planning and control, differential equations, complex analysis, and numerical optimization. In the following years, he got familiar with artificial intelligence methods, which later motivated his master project on using artificial intelligent methods for data classification and to control the robot stability.

In 2013, he introduced eXtended Classifier System for the Real-time-input Real-time-output (XCSRR), which is the improved version of XCS. In XCSRR, he used a clustering method to optimize the number of rules and decrease the number of iteration that is necessary to train the system. To validate the efficiency of his method, he applied XCSRR on mathematical model of humanoid robot, using MATLAB Software. The result showed 15% of improvement in the robot’s stability, compared to Neural Network (NN) methods. The result of this study was published in a paper entitled “An Improved eXtended Classifier System for the Real-time-input Real-time-output (XCSRR) Stability Control of a Biped Robot”.

He also improved eXtended Classifier System for Function approximation (XCSF) with continuous actions. Results from numerous experiments showed that the proposed algorithm outperforms the original classifier system in terms of both accuracy and computational cost. The result of this study was published in a paper entitled “An Improved Continuous-Action Extended Classifier Systems for Function Approximation”. 

Since 2014, he has been involved in a great project with collaboration of his peers at Shan Research Group. In this project, they introduced a soft gripper consists of three fingers which are modeled in computer in order to optimize designing’s parameters. Finite element analysis and experimental results show the efficiency of the gripper to pick up heavy objects and twisting. The result of this study was submitted to the soft robotic journal as a paper entitled “A soft gripper with rigidity tunable elastomer as tendon”. 

Since 2015, and after he got admitted at UNR majoring in MBA, he got involved in different projects related to Structured Query language (SQL) and Relational Database Management Systems (RDBMS). having the knowledge of SQL and working with Tableau as well as the knowledge engineering. Amin Sabzehzar is able to come up with solution to optimize industrial systems and processes.