Mr. Ali Khoshlahjeh Sedgh | Engineering | Best Researcher Award

Co-Author at K. N. Toosi University of Technology, Iran

Ali Khoshlahjeh Sedgh is a highly motivated and accomplished electrical engineer with a deep passion for control systems and cybersecurity within cyber-physical systems. He holds both Bachelor’s and Master’s degrees in Electrical Engineering from K. N. Toosi University of Technology, where he consistently ranked among the top of his class. Ali has demonstrated excellence in academic performance, earning prestigious scholarships from the Iran National Elites Foundation and Ghalamchi Educational Foundation. His Master’s thesis, focused on implementing reinforcement learning methods for cyber-attack detection in liquid-level control systems, showcases his skill in combining theoretical models with practical application. Ali’s interests span fault detection, system identification, adaptive and robust control, and the integration of machine learning techniques such as neural networks and reinforcement learning into industrial control environments. He has authored several publications in high-ranking journals and conferences, highlighting his commitment to research and innovation. In addition to his technical expertise, he is an experienced educator and lab coordinator, having guided student projects and managed experimental research facilities. Ali’s work is characterized by a strong foundation in mathematical modeling, system design, and implementation, and his long-term vision is to contribute to the development of resilient, secure, and intelligent control systems for critical infrastructures worldwide.

Professional Profile

• Google Scholar

Education

Ali Khoshlahjeh Sedgh earned his Master of Science degree in Electrical Engineering with a specialization in Control from K. N. Toosi University of Technology, Tehran, graduating in 2024 with an outstanding GPA of 4.0 (19.08/20). His thesis, supervised by Prof. Hamid Khaloozadeh, focused on the “Practical Implementation of Reinforcement Learning Methods for Attack Detection in a Liquid Level Control Cyber-Physical System,” exemplifying his ability to integrate artificial intelligence techniques with industrial control systems. His graduate coursework included top marks in challenging subjects such as Fault Detection, System Identification, Adaptive Control, Optimal Filtering, and Robust Control. Prior to his master’s, Ali completed his Bachelor of Science in Electrical Engineering from the same university, graduating in 2021 with a GPA of 3.88/4. His undergraduate thesis involved designing a solar-powered forest fire alarm system using SMS module communication. Throughout his academic career, he consistently achieved top ranks in control engineering and was accepted into the Master’s program without an entrance exam due to his exceptional performance. Ali’s education is deeply rooted in both theoretical principles and practical experimentation, forming a strong foundation for his research in intelligent and secure control systems. His academic training reflects his dedication, curiosity, and capability for innovation in the field.

Professional Experience

Ali Khoshlahjeh Sedgh has built substantial professional experience through both academic and industrial roles, demonstrating a balance between research, teaching, and practical engineering applications. Since 2022, he has served as the Laboratory Coordinator at the Instrumentation Lab of K. N. Toosi University of Technology. In this role, he has managed research projects, supervised laboratory experiments, maintained equipment, organized exams, and supported student internships. His responsibilities included implementing cyber-physical security measures, designing experimental setups, and applying fault detection techniques in real systems. Ali’s involvement in the lab has allowed him to practically test advanced control strategies, including PI, LQT, and adaptive controllers, in coupled-tank systems. His commitment to knowledge sharing is further highlighted by his teaching experience, where he has worked as an instructor and teaching assistant in courses such as Engineering Probability. Additionally, Ali gained industry experience as an intern and later as an electrical engineer at Fahm Electronics from 2021 to 2022. During this time, he worked on medical rehabilitation equipment and industrial projects, including the design and development of a 3-degree-of-freedom platform. His strong work ethic earned him top evaluations. Ali’s professional journey showcases a dynamic profile of technical versatility, research leadership, and a strong orientation toward solving real-world engineering problems.

Research Interests

Ali Khoshlahjeh Sedgh’s research interests lie at the intersection of control engineering, cyber-physical systems, and artificial intelligence, with a focus on developing secure, resilient, and intelligent systems. He is particularly passionate about Fault Detection and Identification (FDI), where he explores both signal-based and model-based techniques to enhance system reliability in real-time industrial applications. System Identification also plays a central role in his work, allowing him to model and simulate complex dynamic systems accurately using both non-parametric and parametric methods. Ali has a strong interest in Adaptive and Robust Control, emphasizing strategies that ensure system stability and performance under uncertainties and disturbances. He is equally engaged in applying Machine Learning—especially Reinforcement Learning (RL) and Neural Networks (NN)—to control problems, including attack detection in cyber-physical systems. His recent research centers on using reinforcement learning methods to detect and mitigate cyber-attacks, such as denial-of-service (DoS), in liquid-level control systems. Through a combination of theoretical foundations and hands-on implementations, Ali aims to build control systems that can adaptively respond to anomalies and security threats. He envisions future applications of his research in smart grids, autonomous vehicles, and industrial automation, where system safety and resilience are increasingly critical in the face of evolving technological and cybersecurity challenges.

Research Skills

Ali Khoshlahjeh Sedgh possesses a robust set of research skills that span theoretical modeling, simulation, implementation, and experimental validation of advanced control systems. He is proficient in using MATLAB and Simulink for simulation and algorithm development, and has developed numerous tools for system identification, adaptive control, estimation theory, and fault detection. His coding skills in Python, C, and C++ complement his ability to apply machine learning and signal processing techniques in both time and frequency domains. Ali has implemented methods like Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and classifiers including KNN, Bayesian approaches, and Neural Networks such as MLP and RBF for fault diagnosis tasks. In estimation theory, he has used optimal filters like Kalman Filter, Wiener Filter, and maximum likelihood-based methods for state and parameter estimation. Ali has practically applied these techniques in a real coupled-tank system where he modeled and diagnosed faults and detected cyber-attacks using tools like Wireshark and protocols via Kali Linux. His control system toolbox includes robust PI controllers, LQT controllers, adaptive observers, and STR models. His strong command over experimental research, hardware-software integration, and system analysis reflects his ability to transform theoretical constructs into practical solutions for critical infrastructure systems.

Awards and Honors

Ali Khoshlahjeh Sedgh’s academic and research excellence has been consistently recognized through multiple awards and honors. He was ranked 2nd among all Master of Science students in Electrical Engineering – Control at K. N. Toosi University of Technology in 2024, a testament to his outstanding academic record and contribution to research. Earlier, in 2021, he graduated as the 3rd top student in the Control sub-major during his bachelor’s degree, which led to his direct admission into the master’s program without the need for a national entrance examination. Ali’s talent was further acknowledged through his receipt of scholarships from the Iran National Elites Foundation between 2021 and 2023, awarded to high-potential students contributing to science and technology in Iran. Additionally, he received a scholarship from the Ghalamchi Educational Foundation during his early undergraduate years in recognition of his academic promise. His active participation and presentation at international conferences—such as ITMS 2023 in Latvia—showcase his engagement with the global research community. These accolades reflect not only Ali’s scholarly dedication and innovative thinking but also his leadership potential and ability to stand out in highly competitive academic environments.

Conclusion

Ali Khoshlahjeh Sedgh represents the ideal convergence of deep technical expertise, hands-on research capability, and forward-thinking innovation in the field of control engineering. With a strong educational foundation from K. N. Toosi University of Technology and consistent recognition as a top-performing student, Ali has built a multifaceted academic and professional profile. His work bridges theory and practice, especially in developing intelligent, resilient control systems that address real-world issues such as cyber threats and fault tolerance in cyber-physical environments. Ali’s commitment to excellence is evident in his peer-reviewed publications, experimental projects, and his roles as both a laboratory coordinator and educator. He is driven by a desire to make meaningful contributions to modern engineering challenges, particularly in ensuring the security and reliability of automated systems. His future ambitions include pursuing advanced research, collaborating on interdisciplinary projects, and contributing to innovations in smart infrastructure, autonomous systems, and industrial automation. With a collaborative spirit, a deep curiosity for learning, and a relentless pursuit of practical solutions, Ali is well-positioned to lead and innovate in both academic and industry-driven environments. His journey so far reflects not just skill, but a vision for shaping the future of secure and adaptive control systems.

Publications Top Notes

1. Title: Resilient Control for Cyber-Physical Systems Against Denial-of-Service Cyber Attacks Using Kharitonov’s Theorem
   Authors: H.R. Chavoshi, A.K. Sedgh, H. Khaloozadeh
   Year: 2023
   Citations: 2

2. Title: Enhancing Cybersecurity in Nonlinear Networked Control Systems Through Robust PI Controller Design and Implementation Against Denial-of-Service Attacks
   Authors: A.H. Salasi, H.R. Chavoshi, O. Payam, A.K. Sedgh, H. Khaloozadeh
   Year: 2023
   Citations: 1

3. Title: Practical Implementation of Multiple Faults in a Coupled-Tank System: Verified by Model-Based Fault Detection Methods
   Authors: H.R. Chavoshi, A.K. Sedgh, M.A. Shoorehdeli, H. Khaloozadeh
   Year: 2023
   Citations: 1