Dr. Hamed Khodadadi is an accomplished researcher and academic with extensive expertise in biomedical engineering, control systems, and machine learning, particularly in healthcare applications. His work focuses on developing advanced computer-aided diagnosis systems for detecting diseases such as cancer, brain disorders, cardiovascular conditions, ADHD, Parkinson’s, and Schizophrenia. He has also contributed significantly to biomedical control systems, medical drug dosing strategies, and applications of chaos theory in medical research. With a strong background in intelligent modeling, nonlinear and adaptive control, and optimization techniques, Dr. Khodadadi has published widely and earned multiple prestigious awards recognizing his impact. His research has not only advanced scientific understanding but also demonstrated practical value through patents and innovative devices. Alongside research, he has mentored numerous graduate and doctoral students, demonstrating dedication to academic growth and leadership. His combination of innovation, productivity, and mentorship positions him as a highly influential figure in biomedical engineering and applied machine learning.

Professional Profile 

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Education

Dr. Hamed Khodadadi holds a Ph.D. in Electrical Engineering with a specialization in Control Systems from Azad University, Science and Research Branch, Tehran. His doctoral research focused on extracting nonlinear indices for image patterns and evaluating their application in cancer tumor control, bridging the gap between control theory and biomedical diagnosis. He earned his M.Sc. in Electrical Engineering, also in Control Systems, where his thesis involved designing and constructing a two-degree-of-freedom inertial stabilized platform, showcasing his strong foundation in system modeling and control. His academic journey began with a B.Sc. in Electrical Engineering at Iran University of Science and Technology, where he worked on PID controller design for pan-tilt movement in a gimbal system. This educational progression demonstrates a consistent focus on control systems with increasing application toward biomedical challenges, reflecting his ability to integrate engineering principles into healthcare innovations. His education has provided the solid technical base underpinning his interdisciplinary research career.

Experience

Dr. Khodadadi has over a decade of academic and research experience, serving as Assistant Professor and later Associate Professor at Azad University, Khomeinishahr Branch, where he supervises M.Sc. and Ph.D. students. His work includes designing advanced computer-aided diagnosis systems using biomedical signals and images for applications in cancer, cardiovascular disorders, ADHD, Parkinson’s, and Schizophrenia. He has also applied advanced control methods such as nonlinear, adaptive, fuzzy, and model predictive control to medical drug dosing, robotics, and industrial systems. His experience extends to the construction of biomedical and engineering devices, including prosthetic hands and robotic platforms. In addition to teaching graduate and undergraduate courses, he has actively guided thesis projects, contributing to the growth of young researchers. He has also undertaken collaborative roles in collecting biomedical databases, such as cardiovascular biomarkers and EEG signals, supporting clinical research. His broad experience demonstrates both depth in biomedical applications and versatility across engineering and industrial domains.

Research Focus

Dr. Khodadadi’s research centers on biomedical engineering, control systems, and machine learning, with a strong emphasis on healthcare applications. His work integrates computational intelligence, signal and image processing, and control theory to design advanced computer-aided diagnosis systems for life-threatening diseases, including various forms of cancer, brain disorders, and cardiovascular conditions. He has pioneered the application of nonlinear control, adaptive control, and metaheuristic optimization in medical drug dosing and disease modeling, contributing to precision medicine. Additionally, his research explores chaos theory and its role in biomedical image analysis, providing novel tools for early disease detection. He also investigates intelligent optimization and robust control techniques for diverse engineering applications, from robotics and power systems to industrial processes. His interdisciplinary focus blends theory with practical innovation, producing outcomes that advance both medical research and engineering systems. Ultimately, his research vision aims to improve diagnostic accuracy, treatment strategies, and patient outcomes through advanced engineering methods.

Award and Honor

Dr. Khodadadi has been recognized through numerous awards and honors that highlight his excellence in research, innovation, and mentorship. He has received multiple Best Researcher Awards at Azad University, including recognition at both departmental and institutional levels. His international visibility is reflected in honors such as Best Oral Presentation at the International Conference of Research in Europe and being a finalist for the Best Student Award at an IEEE international conference. He has also received recognition for supervising graduate theses with strong industrial impact, reflecting the practical value of his mentorship. His academic achievements include top rankings in national and Ph.D. entrance examinations, along with an Exceptional Talents Award early in his career. Furthermore, he earned the Best International Book Award at a university research festival, showcasing his contributions to scientific literature. Collectively, these accolades underscore his sustained contributions to advancing biomedical engineering, control systems, and healthcare-focused machine learning research.

Publication Top Notes

• Title: Adaptive super-twisting non-singular terminal sliding mode control for tracking of quadrotor with bounded disturbances
  Authors: H. Ghadiri, M. Emami, H. Khodadadi
  Year: 2021
  Citations: 95

• Title: Self-tuning PID controller design using fuzzy logic for half car active suspension system
  Authors: H. Khodadadi, H. Ghadiri
  Year: 2018
  Citations: 90

• Title: Heart arrhythmia diagnosis based on the combination of morphological, frequency and nonlinear features of ECG signals and metaheuristic feature selection algorithm
  Authors: V. Mazaheri, H. Khodadadi
  Year: 2020
  Citations: 83

• Title: Robust control and modeling a 2-DOF inertial stabilized platform
  Authors: H. Khodadadi, M.R.J. Motlagh, M. Gorji
  Year: 2011
  Citations: 78

• Title: The Diagnosis of Attention Deficit Hyperactivity Disorder Using Nonlinear Analysis of the EEG Signal
  Authors: Y. Kiani, A.A. Rastegari, H. Khodadadi
  Year: 2019
  Citations: 72

• Title: Human brain tumor diagnosis using the combination of the complexity measures and texture features through magnetic resonance image
  Authors: S. Salem Ghahfarrokhi, H. Khodadadi
  Year: 2020
  Citations: 54

• Title: The effects of poplar bark and wood content on the mechanical properties of wood-polypropylene composites
  Authors: V. Safdari, H. Khodadadi, S.K. Hosseinihashemi, E. Ganjian
  Year: 2011
  Citations: 53

• Title: Fuzzy logic self-tuning PID control for a single-link flexible joint robot manipulator in the presence of uncertainty
  Authors: A. Dehghani, H. Khodadadi
  Year: 2015
  Citations: 41

• Title: Designing a Neuro-Fuzzy PID Controller Based on Smith Predictor for Heating System
  Authors: A. Dehghani, H. Khodadadi
  Year: 2017
  Citations: 35

• Title: Malignant melanoma diagnosis applying a machine learning method based on the combination of nonlinear and texture features
  Authors: S. Salem Ghahfarrokhi, H. Khodadadi, H. Ghadiri, F. Fattahi
  Year: 2023
  Citations: 33

• Title: Climate control of an agricultural greenhouse by using fuzzy logic self-tuning PID approach
  Authors: M. Heidari, H. Khodadadi
  Year: 2017
  Citations: 28

• Title: Fuzzy Logic Self-tuning PID Controller Design Based on Smith Predictor for Heating System
  Authors: H. Khodadadi, A. Dehghani
  Year: 2016
  Citations: 25

• Title: Fuzzy Logic Self-Tuning PID Controller Design for Ball Mill Grinding Circuits Using an Improved Disturbance Observer
  Authors: H. Khodadadi, H. Ghadiri
  Year: 2019
  Citations: 24

• Title: Speed control of a DC motor using a fractional order sliding mode controller
  Authors: S. Heidarpoor, M. Tabatabaei, H. Khodadadi
  Year: 2017
  Citations: 23

• Title: Emerging Technologies in Medicine: Artificial Intelligence, Robotics, and Medical Automation
  Authors: M. Rezaei, S. Saei, S.J. Khouzani, M.E. Rostami, M. Rahmannia, …
  Year: 2023
  Citations: 21

Conclusion

Dr. Hamed Khodadadi’s research contributions reflect a strong blend of theoretical innovation and practical application across biomedical engineering, control systems, and machine learning. His highly cited works demonstrate significant impact in fields such as disease diagnosis, biomedical signal and image processing, and intelligent control methods. The breadth of his publications, spanning healthcare applications, robotics, and industrial systems, highlights both versatility and depth. With consistent recognition through citations, patents, and international awards, his research not only advances academic knowledge but also addresses real-world medical and engineering challenges. Collectively, his achievements establish him as a leading researcher whose contributions are both impactful and enduring, making him a deserving candidate for prestigious recognition such as the Best Researcher Award.