HAIFEI CHEN | Visual SLAM | Best Researcher Award

Assoc .Prof. Dr. HAIFEI CHEN | Visual SLAM | Best Researcher Award

Central South University of Forestry and Technology, China

Dr. Haifei Chen is an accomplished Associate Professor at the School of Mechanical and Intelligent Manufacturing, Central South University of Forestry and Technology. Born in August 1990 in Chenzhou, Hunan, he is a dedicated scholar in the field of robotics and intelligent control. With a strong academic background and robust research portfolio, he has led numerous national and provincial research projects focusing on teleoperation robotics, multi-agent coordination, SLAM, and networked control systems. His scholarly contributions include over 20 high-impact SCI-indexed journal articles and multiple patents. A recognized academic leader, Dr. Chen holds key roles in national research centers and professional societies and serves as a reviewer for top-tier IEEE journals. His research has significantly advanced space robotics and teleoperation technologies. Through innovation, leadership, and academic excellence, he has positioned himself as a promising and impactful researcher in the field of intelligent robotics.

Professional Profile 

Education🎓

Dr. Haifei Chen pursued his doctoral studies at the School of Astronautics, Northwestern Polytechnical University, beginning in September 2017. His Ph.D. specialization was in navigation, guidance, and control under the supervision of Professor Panfeng Huang, a prominent academician and expert affiliated with the National Distinguished Youth Fund and military science commissions. Dr. Chen’s doctoral research focused on time-delay modeling and compensation for space teleoperation systems, laying a strong theoretical foundation for his current work. Prior to his doctoral education, he had successfully cleared national English proficiency exams including CET-6 and achieved an IELTS score of 6.0, reflecting a solid command of the English language for academic communication. His educational experience has equipped him with expertise in robotics, control systems, and artificial intelligence, supporting his contributions to both theoretical research and engineering practice. His education forms the core of his academic identity and drives his research in intelligent robotic systems.

Professional Experience📝

Dr. Haifei Chen currently serves as an Associate Professor at the School of Mechanical and Intelligent Manufacturing, Central South University of Forestry and Technology, a position he has held since December 2023. Prior to this, he was a Lecturer at the School of Mechanical and Electrical Engineering at the same university from February 2022 to December 2023. His academic trajectory has been steadily progressive, with research and teaching roles focused on robotic teleoperation, intelligent control, and remote robotic systems. His leadership includes managing multiple funded projects, mentoring students, and contributing to institutional development as a discipline leader in forestry equipment and intelligent systems. He is also affiliated with key research centers, including the National Engineering Research Center for Economic Forest Harvesting Equipment. His experience bridges fundamental research and practical implementation, making him a vital contributor to the advancement of robotics in forestry and space technology domains.

Research Interest🔎

Dr. Haifei Chen’s research interests are deeply rooted in robotic teleoperation, intelligent control, and multi-agent system collaboration. His work explores the challenges of time-delay in remote control systems, particularly in space teleoperation, with the goal of enhancing the precision and reliability of robotic operations under communication constraints. He is also focused on visual SLAM (Simultaneous Localization and Mapping), predictive control, and networked control systems—all critical to the development of autonomous and semi-autonomous robotic platforms. His recent research involves developing teleoperation systems for agricultural and forestry robots, such as oil-tea camellia fruit picking, using advanced machine learning algorithms and sensor fusion techniques. Dr. Chen aims to bridge the gap between theoretical models and practical deployment by incorporating real-time data processing, human-robot interaction, and decision-making algorithms. These interests reflect a multidisciplinary approach, integrating robotics, AI, and control theory to create intelligent, adaptive, and scalable robotic systems.

Award and Honor🏆

Dr. Haifei Chen has earned recognition both as a researcher and a community contributor. He serves as an expert reviewer for the National Natural Science Foundation of China (NSFC), reflecting his authority in his research field. He is the Vice Director of the National Engineering Research Center for Economic Forest Harvesting Equipment and serves on the Youth Committee of the Chinese Society of Forestry and the Robotics Subcommittee. These positions highlight his leadership within the academic and scientific communities. Furthermore, Dr. Chen has served as a reviewer for several internationally renowned journals, including IEEE Transactions on Systems, Man and Cybernetics: Systems, IEEE Transactions on Mechatronics, IEEE RA-L, Acta Astronautica, and ISA Transactions. His contributions to academic peer review and research management are clear indicators of professional excellence. While individual awards are not specifically listed, his prestigious roles and responsibilities underscore his impact and growing recognition in the robotics field.

Research Skill🔬

Dr. Haifei Chen possesses a versatile and advanced set of research skills in robotics and intelligent systems. He is highly proficient in modeling and controlling time-delay in networked and remote robotic systems—skills critical for real-time space and teleoperation environments. He has strong command over predictive control algorithms, Smith predictors, and error loop correction methods. His expertise extends to multi-agent coordination, robot vision (including SLAM), and motion planning, where he integrates machine learning techniques such as CNNs, BiGRUs, and attention mechanisms for state prediction and decision-making. He is adept at developing algorithms that optimize robotic response in high-latency environments, such as relay communication-based space missions. In addition to algorithm design, he is experienced in real-time robotic system integration and experimental validation. With skills spanning simulation, hardware interfacing, and intelligent control, Dr. Chen brings a comprehensive and technically rigorous approach to research that bridges theoretical development and engineering implementation.

Conclusionđź’ˇ

Dr. Haifei Chen presents a compelling case as a young and dynamic researcher who combines technical depth, publication excellence, research leadership, and innovation in intelligent robotics and remote control systems. He shows a rare blend of academic rigor, engineering practice, and institutional responsibility.

With minor enhancements in international outreach and broader recognition, he is on a strong trajectory toward becoming a leading figure in his domain. He is not only suitable, but in fact, a competitive nominee for the Best Researcher Award.

Publications Top Noted✍

  • Title: Path Integral Policy Improvement and Dynamic Movement Primitives Fusion-Based Impedance Force Control With Error Loop Correction
    Authors: Mujie Liu, Haifei Chen, Lijun Li, Zhiqiang Ma, Yong Xu, Hui Zhang
    Year: 2025
    Citation: IEEE Transactions on Automation Science and Engineering, DOI: 10.1109/TASE.2025.3562677

  • Title: Mapping Noise Optimization of the Cartographer on the Premise of Comparative Experimental Analysis
    Authors: Xuefei Liu, Haifei Chen, Zicheng Gao, Meirong Chen, Lijun Li, Kai Liao
    Year: 2025
    Citation: Mechatronics, DOI: 10.1016/j.mechatronics.2024.103289

  • Title: Position Prediction for Space Teleoperation With SAO-CNN-BiGRU-Attention Algorithm
    Authors: Keli Wu, Haifei Chen, Lijun Li, Zhengxiong Liu, Haitao Chang
    Year: 2024
    Citation: IEEE Robotics and Automation Letters, DOI: 10.1109/LRA.2024.3498700

  • Title: Bilateral Synchronization Control of Networked Teleoperation Robot System
    Authors: Zhengxiong Liu, Haifei Chen, Panfeng Huang, Yang Yang
    Year: 2024
    Citation: International Journal of Robust and Nonlinear Control, DOI: 10.1002/rnc.7374

  • Title: Time-Delay Modeling and Simulation for Relay Communication-Based Space Telerobot System
    Authors: Haifei Chen, Zhengxiong Liu, Panfeng Huang, Zhian Kuang
    Year: 2022
    Citation: IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2021.3090806

  • Title: Time-Delay Prediction–Based Smith Predictive Control for Space Teleoperation
    Authors: Haifei Chen, Zhengxiong Liu
    Year: 2021
    Citation: Journal of Guidance, Control, and Dynamics, DOI: 10.2514/1.G005714

Mohammadreza Aghamohammadi | Deep Metric Learning | Best Researcher Award

Prof. Dr. Mohammadreza Aghamohammadi | Deep Metric Learning | Best Researcher Award

Head of Electrical Engineering epartment at  Shahid Beheshti University, Iran

Prof. MohammadReza Aghamohammadi is a distinguished academic and researcher in Electrical Engineering at Shahid Beheshti University, Iran, with over three decades of impactful contributions to power systems engineering. Currently serving as the Dean of the Faculty of Electrical Engineering, he is also the Head of the Iran Dynamic Research Center (IDRC). His career bridges academia and industry, focusing on real-world challenges such as power system stability, blackout prevention, and intelligent grid control. A leader in energy reliability, he has held numerous national roles in planning and reliability councils under Iran’s Ministry of Energy. He has guided over 80 theses at undergraduate, master’s, and Ph.D. levels, and organized key international conferences in power systems. With memberships in IEEE, Cigre, and IAEEE, Prof. Aghamohammadi is widely recognized for his technical leadership, mentorship, and sustained research excellence. His interdisciplinary expertise continues to shape the next generation of power system innovation in Iran and beyond.

Professional Profile 

Education🎓

Prof. Aghamohammadi’s academic journey spans prestigious institutions across Iran, the UK, and Japan. He earned his Bachelor of Science in Electrical Engineering from Sharif University of Technology in Tehran in 1980, laying a strong foundation in the field. He then pursued his Master’s degree in Electrical Engineering at the University of Manchester Institute of Science and Technology (UMIST), UK, graduating in 1986 with advanced expertise in electrical systems. His academic pursuit culminated in a Ph.D. in Electrical Engineering from Tohoku University in Sendai, Japan, in 1994. His doctoral research focused on the secure operation of electric power systems using neural network applications—an innovative and forward-looking topic at the time. His global academic background has equipped him with a broad and multidisciplinary understanding of electrical engineering, making him a well-rounded expert in both theoretical and applied power system studies, with an international perspective critical to energy research and innovation.

Professional Experience📝

Prof. Aghamohammadi’s professional career is marked by a unique blend of academic leadership and national-level energy sector involvement. From 1994 to 2012, he served at the Power & Water University of Technology (PWUT) as an Assistant Professor and held leadership roles including Vice Chancellor for Research and Head of the Power Industry Innovation Center. He served as a consultant to several key departments within Iran’s Ministry of Energy, including Tavanir and Moshanir Engineering Consultants. Since 2005, he has led the Iran Dynamic Research Center and has been a pivotal figure in shaping Iran’s power system strategies. At Shahid Beheshti University, he has held several roles: Head of Power Group, Head of Operation & Planning Group, and currently Dean of the Faculty of Electrical Engineering. His leadership also includes positions within the Iran Electric Reliability Council (IERC), where he contributed to strategic national planning for electrical system stability and development.

Research Interest🔎

Prof. Aghamohammadi’s research interests are deeply rooted in the stability, reliability, and intelligent control of electrical power systems. His work spans key areas such as power system security assessment, inter-area oscillations, cascading failure analysis, and blackout simulation—critical challenges in modern energy infrastructure. He has contributed extensively to voltage stability enhancement, reactive power control, and the implementation of controlled islanding strategies to prevent large-scale outages. A notable aspect of his research is the integration of artificial intelligence and neural network applications into power system operations, aligning traditional power engineering with cutting-edge computational techniques. His long-term research has been instrumental in projects such as the dynamic study of the Iranian power grid, voltage control using STATCOM, and load balancing in distribution networks. Prof. Aghamohammadi’s work not only addresses theoretical models but is directly applied in large-scale national projects, bridging academia with industry for sustainable and resilient power systems.

Award and Honor🏆

While specific individual awards are not detailed, Prof. Aghamohammadi’s honors are reflected through his extensive leadership roles, national responsibilities, and recognitions by key organizations. His appointment as Dean of the Faculty of Electrical Engineering and Director of the Iran Dynamic Research Center signify institutional trust in his expertise. He has served as Chair and Technical Head for prestigious conferences such as the International Power System Conference (1997) and the 17th International Conference on Protection and Automation (2023), recognizing his authority in the field. He is an active member of leading professional societies, including IEEE, Cigre, and IAEEE, indicating peer acknowledgment at both national and international levels. Furthermore, his role on strategic councils like the Iran Electric Reliability Council (IERC) underscores his contributions to national energy policy and planning. These cumulative recognitions and responsibilities are a testament to his status as one of Iran’s foremost experts in power system engineering and energy reliability.

Research Skill🔬

Prof. Aghamohammadi possesses a rich portfolio of advanced research skills centered on electrical power systems and intelligent energy management. He is proficient in dynamic system modeling, power system security evaluation, voltage and frequency stability analysis, and the development of preventive strategies against cascading failures and blackouts. His expertise includes simulation-based analysis, control algorithm design, and the application of artificial intelligence—especially neural networks—for enhanced grid operations. His contributions to long-term dynamic studies and reactive power control demonstrate his ability to manage complex systems with practical and scalable solutions. His research also involves technical knowledge in STATCOM applications, controlled islanding, and real-time decision-making in energy distribution networks. Moreover, he has led numerous multidisciplinary research projects and mentored graduate-level theses, indicating strong supervision and technical communication skills. These capabilities have enabled him to transform academic research into actionable insights for national grid planning and stability, making him a valuable asset to both academia and industry.

Conclusionđź’ˇ

Prof. MohammadReza Aghamohammadi’s long-standing contributions to power system engineering, deep industry-academic integration, and academic leadership strongly support his nomination for the Best Researcher Award. His influence spans research excellence, institutional leadership, and real-world application, making him a standout candidate. While some enhancements in international visibility could be beneficial, his credentials already position him as a top-tier nominee for the award.

Publications Top Noted✍

  • Title: A new approach for optimal sizing of battery energy storage system for primary frequency control of islanded microgrid
    Authors: MR Aghamohammadi, H Abdolahinia
    Year: 2014
    Citations: 370

  • Title: Intentional islanding using a new algorithm based on ant search mechanism
    Authors: MR Aghamohammadi, A Shahmohammadi
    Year: 2012
    Citations: 120

  • Title: Optimal distribution feeder reconfiguration and generation scheduling for microgrid day-ahead operation in the presence of electric vehicles considering uncertainties
    Authors: M Sedighizadeh, G Shaghaghi-shahr, M Esmaili, MR Aghamohammadi
    Year: 2019
    Citations: 82

  • Title: DT based intelligent predictor for out of step condition of generator by using PMU data
    Authors: MR Aghamohammadi, M Abedi
    Year: 2018
    Citations: 73

  • Title: Wavelet based feature extraction of voltage profile for online voltage stability assessment using RBF neural network
    Authors: S Hashemi, MR Aghamohammadi
    Year: 2013
    Citations: 70

  • Title: Application of Newton-based load flow methods for determining steady-state condition of well and ill-conditioned power systems: A review
    Authors: M Karimi, A Shahriari, MR Aghamohammadi, H Marzooghi, V Terzija
    Year: 2019
    Citations: 69

  • Title: A new approach for online coherency identification in power systems based on correlation characteristics of generators rotor oscillations
    Authors: MR Aghamohammadi, SM Tabandeh
    Year: 2016
    Citations: 63

  • Title: A novel virtual inertia control strategy for frequency regulation of islanded microgrid using two-layer multiple model predictive control
    Authors: S Oshnoei, MR Aghamohammadi, S Oshnoei, S Sahoo, A Fathollahi, …
    Year: 2023
    Citations: 55

  • Title: A three stages decision tree-based intelligent blackout predictor for power systems using brittleness indices
    Authors: MR Salimian, MR Aghamohammadi
    Year: 2017
    Citations: 53

  • Title: Decision tree analysis to identify harmful contingencies and estimate blackout indices for predicting system vulnerability
    Authors: E Aliyan, M Aghamohammadi, M Kia, A Heidari, M Shafie-khah, …
    Year: 2020
    Citations: 52

  • Title: Intelligent out of step predictor for inter area oscillations using speed-acceleration criterion as a time matching for controlled islanding
    Authors: MR Salimian, MR Aghamohammadi
    Year: 2016
    Citations: 48

  • Title: Enhancement of the LVRT capability for DFIG-based wind farms based on short-circuit capacity
    Authors: Z Rafiee, R Heydari, M Rafiee, MR Aghamohammadi, F Blaabjerg
    Year: 2022
    Citations: 44

  • Title: A new scheme of WADC for damping inter-area oscillation based on CART technique and Thevenine impedance
    Authors: S Ranjbar, MR Aghamohammadi, F Haghjoo
    Year: 2018
    Citations: 44

  • Title: Damping inter-area oscillation by generation rescheduling based on wide-area measurement information
    Authors: L Yazdani, MR Aghamohammadi
    Year: 2015
    Citations: 43

  • Title: Provision of frequency stability of an islanded microgrid using a novel virtual inertia control and a fractional order cascade controller
    Authors: S Oshnoei, M Aghamohammadi, S Oshnoei, A Oshnoei, …
    Year: 2021
    Citations: 40

  • Title: A new approach for mitigating blackout risk by blocking minimum critical distance relays
    Authors: MR Aghamohammadi, S Hashemi, A Hasanzadeh
    Year: 2016
    Citations: 35

  • Title: A deep learning-based attack detection mechanism against potential cascading failure induced by load redistribution attacks
    Authors: A Khaleghi, MS Ghazizadeh, MR Aghamohammadi
    Year: 2023
    Citations: 32

  • Title: A review on data-driven security assessment of power systems: Trends and applications of artificial intelligence
    Authors: A Mehrzad, M Darmiani, Y Mousavi, M Shafie-Khah, M Aghamohammadi
    Year: 2023
    Citations: 30

  • Title: Identification of coherent groups of generators based on synchronization coefficient
    Authors: H Davarikia, F Znidi, MR Aghamohammadi, K Iqbal
    Year: 2016
    Citations: 27

  • Title: Sensitivity characteristic of neural network as a tool for analyzing and improving voltage stability
    Authors: M Aghamohammadi, M Mohammadian, H Saitoh
    Year: [Year Not Specified]
    Citations: Not Provided (from IEEE/PES T&D Conf. proceedings)