Prof. Dr. Jafar keighobadi | Automated Machine Learning (AutoML) | Best Researcher Award

Professor at Tabriz university, Iran

Dr. Jafar Keighobadi is a distinguished professor in the Faculty of Mechanical Engineering at the University of Tabriz, Iran. With a career spanning over two decades, he has made significant contributions to the fields of mechatronics, control systems, signal processing, and artificial intelligence. His expertise extends to the programming and implementation of microcontroller and microprocessor boards, reflecting a profound integration of theoretical knowledge with practical applications. Throughout his tenure, Dr. Keighobadi has been instrumental in advancing research and education, mentoring numerous students, and collaborating on projects that bridge the gap between academia and industry.

Profile

Scopus

Education

Dr. Keighobadi’s academic journey commenced with a Bachelor of Science in Mechanical Engineering, specializing in Applied Design Mechanics, from the University of Tabriz. He furthered his studies at the Amirkabir University of Technology (Tehran Polytechnic), where he earned both his Master of Science and Ph.D. in Mechanical Engineering. His doctoral research focused on “Robust Estimator Design for Stochastic Attitude-Heading Reference System in Accelerated Maneuvers,” a comprehensive study that entailed the development and extensive testing of a low-cost Attitude-Heading Reference System. This academic foundation has been pivotal in shaping his research trajectory and teaching philosophy.

Experience

Dr. Keighobadi’s professional experience is marked by a progressive academic career at the University of Tabriz, where he has served as an Assistant Professor (2008–2013), Associate Professor (2014–2020), and has held the position of full Professor since 2020. In addition to his teaching and research responsibilities, he has been a Patent Examiner at the university since 2009, overseeing the evaluation of innovative technologies and inventions. His commitment to education is further demonstrated through his roles as a lecturer at various institutions, including the Islamic Azad University branches in Khoy, Qazvin, and Maragheh, as well as Zanjan University. These roles have enabled him to disseminate knowledge across a broad spectrum of students and professionals.

Research Interests

Dr. Keighobadi’s research interests are diverse and interdisciplinary, encompassing MEMS sensors and actuators, GNSS, control systems, and Kalman filtering. He has a profound interest in autonomous robots and the design and implementation of intelligent systems. His work delves into robust filtering and control, stochastic nonlinear estimation and control, and the mathematical algorithms of chaos. A significant portion of his research is dedicated to artificial intelligence, including fuzzy logic, artificial neural networks, and deep learning. Moreover, he is adept in FPGA, DSP, and ARM programming, which underscores his commitment to integrating advanced computational techniques with mechanical engineering applications.

Awards

Throughout his illustrious career, Dr. Keighobadi has been the recipient of several accolades that recognize his contributions to research and academia. Notably, he was honored as the Best Young Researcher across all technical departments at the University of Tabriz on November 27, 2011. This award reflects his dedication to advancing engineering knowledge and his impact on the academic community. Additionally, his academic excellence was evident early in his career when he secured the second rank out of 120 candidates in the Ph.D. entrance exam at Amirkabir University of Technology on June 18, 2001. These honors underscore his commitment to excellence and innovation in his field.

Publications

Dr. Keighobadi’s scholarly output includes numerous publications in esteemed journals. A selection of his notable works includes:

“Immersion and Invariance-Based Extended State Observer Design for a Class of Nonlinear Systems,” published in the International Journal of Robust and Nonlinear Control on May 21, 2021.

“Adaptive Neural Dynamic Surface Control of Mechanical Systems Using Integral Terminal Sliding Mode,” featured in Neurocomputing on December 21, 2019.

“Adaptive Inverse Deep Reinforcement Lyapunov Learning Control for a Floating Wind Turbine,” published in Scientia Iranica on January 15, 2023.

“Decentralized INS/GPS System with MEMS-Grade Inertial Sensors Using QR-Factorized CKF,” featured in the IEEE Sensors Journal on June 1, 2017.

“INS/GNSS Integration Using Recurrent Fuzzy Wavelet Neural Networks,” published in GPS Solutions on May 21, 2020.

“Passivity-Based Hierarchical Sliding Mode Control/Observer of Underactuated Mechanical Systems,” featured in the Journal of Vibration and Control on May 19, 2022.

“Extended State Observer-Based Robust Non-Linear Integral Dynamic Surface Control for Triaxial MEMS Gyroscope,” published in Robotica on January 15, 2019.

These publications highlight Dr. Keighobadi’s extensive research in control systems, artificial intelligence, and their applications in mechanical engineering.

Conclusion

Dr. Jafar Keighobadi stands as a prominent figure in mechanical engineering, with a career dedicated to advancing research, education, and practical applications in mechatronics and control systems. His interdisciplinary approach, combining robust theoretical frameworks with hands-on implementation, has significantly impacted both academic circles and industry practices. As a mentor, researcher, and educator, Dr. Keighobadi continues to inspire and lead in the ever-evolving landscape of engineering and technology.