Assoc. Prof. Dr. Mohammad Javad Mahmoodabadi | AI Engineering – Associate Professor at Sirjan University of Technology, Iran
Dr. Mohammad Javad Mahmoodabadi is an accomplished academic and researcher, currently serving as an Associate Professor in the Department of Mechanical Engineering at Sirjan University of Technology, Iran. With an impressive track record in mechanical engineering and control theory, Dr. Mahmoodabadi has made significant contributions to the fields of optimization algorithms, machine learning, and mechanical design. He is highly regarded for his innovative approaches in robotics, control engineering, and computational methods. His research has been widely published and cited, establishing him as a leader in his area. Dr. Mahmoodabadi has also played an instrumental role in mentoring graduate students, guiding them through cutting-edge research in nonlinear systems and robotics.
Professional Profile
Education
Dr. Mahmoodabadiās educational background reflects a solid foundation in mechanical engineering. He earned his Ph.D. in Mechanical Engineering from the University of Guilan, Iran, in 2012. His dissertation focused on the multi-objective optimization of linear and nonlinear controllers, combining powerful optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). During his Ph.D., Dr. Mahmoodabadi achieved excellent academic performance, earning a GPA of 18.80 out of 20 and a dissertation grade of 19 out of 20. Prior to this, he completed his Masterās degree in Mechanical Engineering at Shahid Bahonar University of Kerman, Iran, where his thesis dealt with elasto-static problems using meshless methods. His academic achievements have provided him with a deep understanding of both theoretical and applied mechanics, which have been pivotal in his research career.
Experience
Dr. Mahmoodabadiās academic career spans over a decade, during which he has held several important positions. After earning his Ph.D., he served as an Assistant Professor at Sirjan University of Technology from 2012 to 2019, before advancing to the role of Associate Professor. Throughout his career, he has taught various undergraduate and graduate courses, including robotics, control of robots, linear control, fuzzy logic, and optimization. His extensive teaching experience in mechanical engineering and related disciplines has earned him recognition for his ability to convey complex concepts with clarity. In addition to his teaching roles, Dr. Mahmoodabadi has served as the head of the Department of Mechanical Engineering and the Graduate Student Office at his university. His leadership has contributed to the development of academic programs and research initiatives within the department.
Research Interests
Dr. Mahmoodabadiās research interests are diverse, with a primary focus on control theory, machine learning, computational methods, and optimization algorithms. He has worked on various topics such as adaptive robust control, fuzzy logic systems, and multi-objective optimization in the context of nonlinear dynamic systems. His research also extends to robotics, where he has developed novel control strategies for autonomous systems. Additionally, Dr. Mahmoodabadiās work on mechanical design and analysis of complex systems has led to innovative solutions in both theoretical and applied engineering. His approach integrates computational techniques with practical applications, particularly in optimization and control engineering.
Awards
Throughout his career, Dr. Mahmoodabadi has received numerous accolades for his contributions to research and teaching. His excellence in academic leadership and groundbreaking research has earned him recognition within his institution and the broader academic community. Notably, his work in the development of control algorithms and optimization methods has received significant attention from his peers, reflected in his high citation count and his role as a mentor to graduate students. Although Dr. Mahmoodabadi has not explicitly listed awards in the traditional sense, his impact on the academic and research community through his publications, patents, and leadership roles can be considered as a testament to his achievements.
Publications
M.J. Mahmoodabadi, N.R. Babak, Pareto optimum design of an adaptive robust backstepping controller for an unmanned aerial vehicle, Asian Journal of Control (2022). š
R. Abedzadeh Maafi, S. Etemadi Haghighi, M.J. Mahmoodabadi, A novel multi-objective optimization algorithm for Pareto design of a fuzzy full state feedback linearization controller applied on a ball and wheel system, Transactions of the Institute of Measurement and Control 44 (7) (2022), 1388ā1409. š
M.J. Mahmoodabadi, S. Hadipour Lakmesari, Optimal design of an adaptive robust controller using a multi-objective artificial bee colony algorithm for an inverted pendulum system, Transactions of the Canadian Society for Mechanical Engineering 46 (1) (2022), 89ā102. š
S.H. Lakmesari, M.J. Mahmoodabadi, Adaptive sliding mode control of HIV-1 infection model, Informatics in Medicine Unlocked 25 (2021), 100703. š”
M.J. Mahmoodabadi, Moving least squares approximation-based online control optimized by the team game algorithm for Duffing-Holmes chaotic problems, Cyber-Physical Systems 7 (2) (2021), 1-21. āļø
M.J. Mahmoodabadi, A.R. Nemati, A new optimum numerical method for analysis of nonlinear conductive heat transfer problems, Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (5) (2021), 1-8. š„
R. Abedzadeh Maafi, S. Etemadi Haghighi, M.J. Mahmoodabadi, Pareto optimal design of a fuzzy adaptive hierarchical sliding-mode controller for an XZ inverted pendulum system, IETE Journal of Research (2021). š
Conclusion
Dr. Mohammad Javad Mahmoodabadiās academic and research career exemplifies excellence in mechanical engineering and control systems. His innovative work in optimization algorithms, machine learning, and mechanical design has earned him recognition as a leader in his field. With a strong publication record and significant contributions to the academic community, he is a well-deserving candidate for the “Best Researcher Award.” His ability to blend theoretical advancements with practical applications, along with his mentorship of future researchers, positions him as a key figure in the development of engineering solutions for complex systems. Dr. Mahmoodabadiās dedication to advancing knowledge, combined with his academic leadership and impactful research, makes him an outstanding nominee for this prestigious award.