Asma Mahgoub | Engineering | Innovative Research Award

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Innovative Research Award

Asma Mahgoub
Affiliation Qatar University
Country Qatar
Scopus ID 57207733885
Documents 11
Citations 106
h-index 4
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-6469-9039

Asma Mahgoub
Qatar University,Qatar

Asma Mahgoub is affiliated with Qatar University and has developed an emerging research profile in engineering with particular emphasis on semantic communication, artificial intelligence, machine learning, image understanding, and next-generation wireless systems. Her scholarly publications investigate methods that improve communication efficiency while maintaining semantic fidelity across modern digital networks.[1]

Abstract

This article summarizes the academic profile of Asma Mahgoub in recognition of her nomination for the Innovative Research Award. Her research combines semantic communication, explainable artificial intelligence, image captioning, transformer models, and intelligent networking to improve data transmission efficiency and communication quality. The body of work demonstrates interdisciplinary engineering research addressing future communication infrastructures, including 6G and edge intelligence, while contributing practical methodologies for semantic-aware information exchange.[2]

Keywords

Semantic Communication, Engineering, Artificial Intelligence, Transformer Models, Image Captioning, Edge Learning, 6G Networks, Explainable AI, Deep Learning, Machine Learning.

Introduction

Modern communication systems increasingly focus on semantic information rather than conventional bit-level transmission. This paradigm supports efficient utilization of bandwidth while preserving contextual meaning. Asma Mahgoub’s publications contribute to this evolving discipline by integrating natural language processing, vision-language models, and engineering optimization into semantic communication frameworks suitable for intelligent wireless environments.[3]

Research Profile

According to the provided scholarly indicators, the researcher has authored 11 indexed publications with 106 citations and an h-index of 4. The publication record reflects consistent engagement in emerging engineering topics including semantic text communication, image semantic transmission, explainable metrics, BERT embeddings, and transformer-based communication architectures. These contributions indicate sustained participation in internationally recognized engineering research.[4]

Research Contributions

  • Advanced transformer-based semantic communication systems.
  • Developed explainable metrics for semantic image communication.
  • Integrated image captioning with intelligent communication models.
  • Investigated semantic communication for future 6G and edge learning platforms.
  • Applied BERT embeddings to improve text semantic transmission.

Publications

  • Document-Level Transformer-Based Text Semantic Communication System (2026).
  • Efficient Explainable Metric for Semantic Communication of Images Using Image Captioning (2026).
  • Metaverse Unbound: Semantic Communication, 6G and Edge Learning (2025).
  • Semantic Communication of Images Using Image Generation and Image Captioning Models (2025).
  • On Using BERT Embeddings for Text Semantic Communication (2024).

Research Impact

The published work contributes to efficient information exchange in intelligent communication systems through semantic-aware methodologies. Research on explainability, multimodal learning, and transformer architectures supports future developments in engineering applications including smart networks, autonomous systems, and next-generation wireless communication technologies.[5]

Award Suitability

The Innovative Research Award recognizes researchers demonstrating originality, scholarly quality, and measurable academic contribution. Based on the documented publication record, citation performance, and interdisciplinary engineering research, Asma Mahgoub’s work aligns with these objectives through meaningful contributions to semantic communication research and advanced intelligent networking technologies.

Conclusion

Asma Mahgoub has established an active research portfolio focused on semantic communication and intelligent engineering systems. Her publications address practical and theoretical challenges relevant to future communication technologies while demonstrating continued scholarly development. The combination of research productivity, citation influence, and innovation supports recognition within international academic award programs.

External Links

References

  1. Mahgoub A. Document-Level Transformer-Based Text Semantic Communication System. Machine Learning and Knowledge Extraction. 2026. DOI: 10.3390/make8080225
  2. Mahgoub A. Efficient Explainable Metric for Semantic Communication of Images Using Image Captioning. IEEE Access. 2026. DOI: 10.1109/ACCESS.2026.3654009
  3. Mahgoub A. Metaverse Unbound: A Survey on Synergistic Integration Between Semantic Communication, 6G, and Edge Learning. IEEE Access. 2025. DOI: 10.1109/ACCESS.2025.3555753
  4. Mahgoub A. Semantic Communication of Images Using Image Generation and Image Captioning Models. 2025. DOI: 10.1007/978-981-96-1483-7_11
  5. Mahgoub A. On Using BERT Embeddings for Text Semantic Communication. HONET 2024. DOI: 10.1109/HONET63146.2024.10822884

 

Oluwole Famoriji | Engineering | Innovative Research Award

Published on by Academic Excellence

 

Innovative Research Award

Oluwole Famoriji
Affiliation Federal University of Technology and Environmental Sciences, Iyin-Ekiti, Nigeria
Country Nigeria
Scopus ID 57193136350
Documents 64
Citations 472
h-index 15
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0003-1357-3935

Oluwole Famoriji
Federal University of Technology and Environmental Sciences, Iyin-Ekiti, Nigeria

Oluwole Famoriji is an engineering researcher whose scholarly work emphasizes power systems, renewable energy integration, antenna technologies, electromagnetic analysis, and machine learning applications for intelligent electrical engineering. His publication portfolio demonstrates sustained contributions to advanced engineering research while addressing practical challenges involving energy optimization, communication systems, and computational prediction methods. The combination of peer-reviewed publications, measurable citation impact, and interdisciplinary collaborations reflects continued academic engagement within internationally recognized journals and conferences.[1]

Abstract

The academic profile of Oluwole Famoriji illustrates continued research activity in electrical and electronic engineering with a strong emphasis on intelligent systems, renewable energy, machine learning, and electromagnetic modelling. His work integrates theoretical development with engineering applications to improve prediction accuracy, voltage regulation, wireless communication performance, and sustainable energy management. The available publication record and citation indicators demonstrate consistent scientific productivity and international collaboration across multiple engineering disciplines.[2]

Keywords

  • Engineering
  • Machine Learning
  • Power Systems
  • Renewable Energy
  • Electromagnetic Radiation
  • Antenna Arrays
  • Artificial Intelligence

Introduction

Modern engineering increasingly depends on intelligent computational approaches to address energy efficiency, communication reliability, and infrastructure resilience. Oluwole Famoriji’s research aligns with these priorities by combining advanced analytical techniques with practical engineering solutions. His investigations contribute to renewable energy coordination, machine learning prediction, electromagnetic modelling, and wireless system optimization, supporting technological development within rapidly evolving engineering environments.[3]

Research Profile

The researcher has produced 64 indexed scholarly documents with 472 citations and an h-index of 15, reflecting measurable scientific influence. His publications span internationally recognized journals including IEEE Access, Applied Sciences, Energies, and other peer-reviewed engineering outlets. Research themes consistently focus on machine learning, intelligent power systems, antenna technologies, and computational engineering methods.[4]

Research Contributions

Major contributions include intelligent photovoltaic energy coordination under uncertainty, machine learning estimation of electromagnetic radiation near 5G infrastructure, multiclass support vector machine methods for direction-of-arrival estimation, systematic reviews of artificial intelligence in power system prediction, and structural electromagnetic modelling for millimeter-wave antenna performance. Collectively these studies advance engineering knowledge through computational innovation and practical system analysis.[5]

Publications

  • An Intelligent Technique for Coordination and Control of PV Energy and Voltage-Regulating Devices in Distribution Networks Under Uncertainties (2025).
  • Machine Learning Approach for Ground-Level Estimation of Electromagnetic Radiation in the Near Field of 5G Base Stations (2025).
  • A Multiclass Support Vector Machine Based Direction-of-Arrival Estimation Technique using Spherical Antenna Array (2024).
  • Machine Learning Approaches for Power System Parameters Prediction: A Systematic Review (2024).
  • Modeling of Coupled Structural Electromagnetic Statistical Concept for Examining Performance Sensitivity of Antenna Array to Distortion at Millimeter-Wave (2024).

Research Impact

The research demonstrates relevance to sustainable energy, smart electrical networks, telecommunications, and intelligent engineering systems. Citation performance and publication consistency indicate recognition by the academic community. The interdisciplinary nature of the work supports technological advancement through data-driven engineering methodologies and computational optimization.[6]

Award Suitability

Based on the documented scholarly record, Oluwole Famoriji demonstrates qualities associated with the Innovative Research Award, including sustained publication activity, interdisciplinary engineering research, international collaboration, and measurable scientific impact. His contributions to intelligent energy systems and computational engineering align with the objectives of recognizing innovation that advances engineering knowledge and practical applications.

Conclusion

The academic achievements of Oluwole Famoriji reflect a balanced combination of research productivity, engineering innovation, and scholarly influence. His investigations in renewable energy, machine learning, electromagnetic systems, and intelligent power networks contribute to contemporary engineering research while supporting future developments in sustainable and computational technologies.

External Links

References

  1. Scopus Author Profile. Research metrics and indexed publications. https://www.scopus.com/pages/authors/57193136350
  2. Famoriji O.J. et al. An Intelligent Technique for Coordination and Control of PV Energy and Voltage-Regulating Devices in Distribution Networks Under Uncertainties. Energies (2025). DOI: 10.3390/en18133481
  3. Famoriji O.J. Machine Learning Approach for Ground-Level Estimation of Electromagnetic Radiation in the Near Field of 5G Base Stations. Applied Sciences (2025). DOI: 10.3390/app15137302
  4. Famoriji O.J. A Multiclass Support Vector Machine Based Direction-of-Arrival Estimation Technique using Spherical Antenna Array. Indonesian Journal of Electrical Engineering and Informatics (2024).
  5. Makanju T.D., Shongwe T., Famoriji O.J. Machine Learning Approaches for Power System Parameters Prediction: A Systematic Review. IEEE Access (2024). DOI: 10.1109/ACCESS.2024.3397676
  6. Famoriji O.J. Modeling of Coupled Structural Electromagnetic Statistical Concept for Examining Performance Sensitivity of Antenna Array to Distortion at Millimeter-Wave. Applied Sciences (2024). DOI: 10.3390/app14167111

 

Eirini Eleni Tsiropoulou | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Eirini Eleni Tsiropoulou | Engineering | Best Researcher Award

Assoc. Prof. Dr. Eirini Eleni Tsiropoulou, Arizona State University, United States

Dr. Eirini Eleni Tsiropoulou is a tenured Associate Professor at the School of Electricahttps://academicexcellenceawards.com/eirini-eleni-tsiropoulou-engineering-best-researcher-award-2472/engil, Computer, and Energy Engineering at Arizona State University. Born in Athens, Greece, she is a U.S. lawful permanent resident fluent in Greek, English, and German. With expertise in game theory, reinforcement learning, distributed decision-making, and artificial intelligence-driven cyber-physical systems, Dr. Tsiropoulou has significantly contributed to optimizing dynamic systems under uncertainty. Her research focuses on resource orchestration in constrained environments and control of interdependent systems. Before joining Arizona State University, she held academic and research positions at the University of New Mexico, the University of Maryland, and the University of Texas at Dallas. She has been recognized globally for her contributions to engineering, including prestigious awards for research excellence, outstanding reviewing, and best paper distinctions. As a leader in her field, she serves on various IEEE committees and continues to shape the future of smart and adaptive systems.

Professional Profile

Scopus

Orcid

Google Scholar

Suitability of Dr. Eirini Eleni Tsiropoulou for the Research for Best Researcher Award

Dr. Eirini Eleni Tsiropoulou is a distinguished researcher in Electrical, Computer, and Energy Engineering, currently serving as an Associate Professor with tenure at Arizona State University. Her research focuses on game theory, reinforcement learning, distributed decision-making, and optimization in dynamic systems, demonstrating a strong interdisciplinary approach to complex problem-solving. Her extensive professional experience across prestigious institutions—including the University of New Mexico, Sandia National Laboratories, and the University of Maryland—underscores her leadership in academia and applied research.

Her impressive record of accolades highlights her significant contributions to the field. She has received numerous awards for research excellence, including the IEEE Early Career Award, multiple Best Paper Awards, and the NSF CRII Award, which showcases her ability to secure competitive funding. Furthermore, her recognition as an IEEE Senior Member and her leadership in various IEEE conferences and technical committees reinforce her impact on the global research community.

🎓 Education

Dr. Eirini Eleni Tsiropoulou holds a Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), where she specialized in optimal resource allocation in next-generation wireless networks. She also earned an MBA in Project Management from NTUA, ranking in the top 1% of her class. Her MBA thesis focused on emissions analysis in power sectors through mathematical modeling. Additionally, she holds a five-year Diploma in Electrical and Computer Engineering from NTUA, again ranking among the top 1% of her class. Her diploma thesis explored game-theoretic approaches to power control in CDMA networks. Through her rigorous academic training, Dr. Tsiropoulou developed a strong foundation in systems optimization, distributed algorithms, and network management, setting the stage for her impactful research career. Her interdisciplinary education blends engineering excellence with strategic project management, equipping her to address complex challenges in modern technological systems.

💼 Professional Experience

Dr. Tsiropoulou is currently an Associate Professor with Tenure at Arizona State University. Previously, she held the same role at the University of New Mexico (UNM). She also served as a PO Contractor at Sandia National Laboratories, contributing to high-impact national security projects. Earlier, she worked as an Assistant Professor at UNM, a Postdoctoral Associate at the University of Maryland and the University of Texas at Dallas, and a Research Fellow at NTUA. Her career spans academia, research, and collaboration with industry and government agencies. She has led multiple NSF-funded projects and guided students in cutting-edge research. Her expertise in reinforcement learning, cyber-physical systems, and optimization has led to transformative advancements in wireless networks and intelligent systems. She actively contributes to IEEE conferences and editorial boards, shaping the future of network science and engineering through interdisciplinary innovation and leadership.

🏅 Awards & Recognition

Dr. Tsiropoulou has received numerous prestigious awards for her contributions to engineering. She was honored as an Excellent Reviewer by IEEE Transactions on Network Science and Engineering (2024) and the IEEE OJCOMS (2024). She won the Best Paper Runner-up Award from IEEE Transactions on Mobile Computing (2023) and received the Research and Creative Works Leader Award at UNM (2023). Recognized for excellence in education, she earned the IEEE Albuquerque Section’s Outstanding Engineering Educator Award (2021). Her research contributions were acknowledged with the IEEE Communications Society Early Career Award (2020) and multiple Best Paper Awards at top-tier conferences like INFOCOM and BRAINS. She was named an IEEE Senior Member (2021) and served on elite IEEE technical committees. Before joining UNM, she received the N2 Women Rising Stars in Networking and Communications Award (2017). Her accolades underscore her leadership and innovative contributions to engineering and academia.

🌍 Research Skills On Engineering

Dr. Tsiropoulou’s research expertise spans game theory, reinforcement learning, optimization of dynamic systems, and distributed decision-making. She specializes in designing adaptive cyber-physical systems for resource-constrained environments, ensuring efficiency in networked infrastructures. Her work integrates stochastic modeling and artificial intelligence to tackle real-world engineering problems. She has made significant contributions to network resource orchestration, security, and autonomous systems control. A key aspect of her research is the application of software-defined networking and AI-driven optimization in complex, uncertain environments. Her interdisciplinary approach enables the development of robust, intelligent frameworks for next-generation wireless networks and smart infrastructures. She has successfully led multiple NSF-funded research projects, collaborating with academia and industry. As an editorial board member for top IEEE journals, she advances knowledge in network science and engineering. Her pioneering research continues to drive innovation in computational intelligence, cybersecurity, and real-time system optimization.

📖 Publication Top Notes

  • Data offloading in UAV-assisted multi-access edge computing systems under resource uncertainty
    Authors: PA Apostolopoulos, G Fragkos, EE Tsiropoulou, S Papavassiliou
    Citation: 170
    Year: 2021
    Journal: IEEE Transactions on Mobile Computing 22 (1), 175-190

  • Game theory for wireless communications and networking
    Authors: Y Zhang, M Guizani
    Citation: 162
    Year: 2011
    Publisher: CRC Press

  • Risk-aware data offloading in multi-server multi-access edge computing environment
    Authors: PA Apostolopoulos, EE Tsiropoulou, S Papavassiliou
    Citation: 161
    Year: 2020
    Journal: IEEE/ACM Transactions on Networking 28 (3), 1405-1418

  • Machine learning and intelligent communications
    Authors: XL Huang, X Ma, F Hu
    Citation: 145
    Year: 2018
    Journal: Mobile Networks and Applications 23, 68-70

  • Interest, energy and physical-aware coalition formation and resource allocation in smart IoT applications
    Authors: EE Tsiropoulou, ST Paruchuri, JS Baras
    Citation: 141
    Year: 2017
    Conference: 51st Annual Conference on Information Sciences and Systems (CISS), 1-6

  • Wireless powered public safety IoT: A UAV-assisted adaptive-learning approach towards energy efficiency
    Authors: D Sikeridis, EE Tsiropoulou, M Devetsikiotis, S Papavassiliou
    Citation: 115
    Year: 2018
    Journal: Journal of Network and Computer Applications 123, 69-79

  • Resource Allocation in Next-Generation Broadband Wireless Access Networks
    Authors: C Singhal, S De
    Citation: 115
    Year: 2017
    Publisher: IGI Global

  • Interest-aware energy collection & resource management in machine to machine communications
    Authors: EE Tsiropoulou, G Mitsis, S Papavassiliou
    Citation: 111
    Year: 2018
    Journal: Ad Hoc Networks 68, 48-57

  • Big data in complex and social networks
    Authors: MT Thai, W Wu, H Xiong
    Citation: 110
    Year: 2016
    Publisher: CRC Press

  • Price and risk awareness for data offloading decision-making in edge computing systems
    Authors: G Mitsis, EE Tsiropoulou, S Papavassiliou
    Citation: 103
    Year: 2022
    Journal: IEEE Systems Journal 16 (4), 6546-6557

AWAIS KHAN | Engineering | Best Researcher Award

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Assist. Prof. Dr. AWAIS KHAN | Engineering | Best Researcher Award

👤 Assist. Prof. Dr. AWAIS KHAN, Beijing Institute of Technology Zhuhai Campus, China

Dr. Awais Khan is an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, specializing in advanced control systems, renewable energy technologies, and interval observers. With a PhD in Control Theory and Control Engineering from South China University of Technology, Dr. Khan has made significant contributions to mechatronics and control engineering during his tenure as a Postdoctoral Research Fellow at Shenzhen University. His research is recognized for its innovative approach, particularly in the application of control systems in energy-efficient technologies. A prolific researcher and published author, Dr. Khan has been actively involved in securing research funding and publishing in top-tier journals. His passion for both teaching and research allows him to foster a dynamic learning environment for students while contributing to the advancement of technology in engineering and energy sectors.

Professional Profile

Google Scholar

🌟 Summary of Suitability for the Research for Best Researcher Award

Awais Khan’s impressive academic background and research trajectory make him highly suitable for the Research for Best Researcher Award. He currently serves as an Assistant Professor at the Beijing Institute of Technology, where he leads cutting-edge research in advanced control systems, renewable energy technologies, and interval observers. His teaching excellence, combined with his groundbreaking research contributions, aligns well with the award’s criteria, which honors those making significant academic and technological advancements.

Awais Khan’s postdoctoral experience at Shenzhen University further solidifies his research prowess, particularly in mechatronics and control engineering. His work has been recognized in reputable journals, with a consistent record of impactful publications in high-impact platforms such as IEEE Transactions and the Journal of the Franklin Institute. He has demonstrated leadership in securing research funding and fostering interdisciplinary collaboration.

🎓   Education 

Dr. Awais Khan holds a PhD in Control Theory and Control Engineering from the South China University of Technology (2016–2020), where his research focused on interval observers and their applications to control theory. Prior to that, he earned a Master’s degree in Electrical Engineering from the University of Engineering and Technology (UET) Lahore (2014–2016). Dr. Khan’s academic journey began with a Bachelor of Science in Electronics Engineering from UET Peshawar (2009–2013), which laid the foundation for his expertise in engineering and control systems. Throughout his academic career, he has received several scholarships, including the prestigious Chinese Government Scholarship for his PhD studies. His educational background is complemented by his active participation in various research projects, workshops, and technical conferences, enabling him to stay at the forefront of advancements in control systems, renewable energy technologies, and energy-efficient engineering solutions.

💼   Professional Experience 

Since 2022, Dr. Awais Khan has been an Assistant Professor at the Beijing Institute of Technology, Zhuhai Campus, where he teaches a range of courses, including C/C++, Probability & Statistical Analysis, Circuits & Electronics, and Physics. His role involves both delivering high-quality lectures and conducting groundbreaking research in advanced control systems, renewable energy, and interval observers. Prior to this, Dr. Khan was a Postdoctoral Research Fellow at Shenzhen University (2020–2022), where he worked on mechatronics and control engineering, developing innovative technologies in interdisciplinary research collaborations. His work on interval observers for nonlinear systems garnered attention, leading to publications in reputable journals. Dr. Khan has also contributed to National Natural Science Foundation of China projects, enhancing the understanding of control systems in uncertain environments. His teaching and research experience are central to his contributions to the field, shaping future engineers and advancing the integration of energy-efficient technologies.

🏅 Awards and Recognition 

Dr. Awais Khan has been recognized for his outstanding contributions to control systems and engineering through several prestigious awards and honors. Notably, he received the Best Presentation Award at the EECR in 2018, reflecting his excellence in research communication. His doctoral research, supported by the Chinese Government Scholarship, marked a milestone in the development of interval observers for linear and nonlinear systems. In addition, Dr. Khan serves as an editor for Technological Innovations & Energy and has been an active member of professional organizations, such as the IEEE and the International Association of Engineers, since 2024. His scholarly work has been widely recognized, with numerous publications in leading journals and conferences. He continues to secure research grants, supporting the advancement of innovative technologies in control systems and energy efficiency. Dr. Khan’s contributions to both academia and the engineering community have made him a respected figure in the field.

🌍  Research Skills On Engineering

Dr. Awais Khan possesses a deep proficiency in advanced control systems, renewable energy technologies, and interval observers. His research expertise spans control theory, nonlinear systems, and energy-efficient technologies, focusing on their applications in both academia and industry. With a strong background in mechatronics and control engineering, he has developed innovative solutions for system stability and energy optimization. Dr. Khan is skilled in designing interval observers for dynamic systems, particularly in uncertain environments, and has published extensively on the subject. His work also explores adaptive control strategies for robotics and power systems, leveraging cutting-edge technologies such as SiC and GaN. Dr. Khan is proficient in several programming languages, including Matlab, Simulink, Python, and C/C++, enabling him to implement complex models and simulations for his research. His skills in interdisciplinary collaboration and securing funding for research projects further highlight his versatility and commitment to advancing technological solutions in engineering.

 📖 Publication Top Notes

  • A survey of interval observers design methods and implementation for uncertain systems
    A Khan, W Xie, Z Bo, LW Liu
    Journal of the Franklin Institute, 358(6), 3077-3126, 2021
    Citation: 52
  • Design and Applications of Interval Observers for Uncertain Dynamical Systems
    A Khan, W Xie, Z Langwen, LW Liu
    IET Circuits, Devices & Systems, 14(6), 721-740, 2020
    Citation: 48
  • Path Planning for Wheeled Mobile Robot in Partially Known Uneven Terrain
    B Zhang, G Li, Q Zheng, X Bai, Y Ding, A Khan
    Sensors, 22(14), 5217, 2022
    Citation: 41
  • Finite‐time nonsingular terminal sliding mode control of converter‐driven DC motor system subject to unmatched disturbances
    A Rauf, M Zafran, A Khan, AR Tariq
    International Transactions on Electrical Energy Systems, 31(11), e13070, 2021
    Citation: 26
  • Interval state estimation for linear time-varying (LTV) discrete-time systems subject to component faults and uncertainties
    A Khan, W Xie, L Zhang, Ihsanullah
    Archives of Control Sciences, 29(2), 289-305, 2019
    Citation: 22
  • Set-Membership Interval State Estimator Design Using Observability Matrix for Discrete-Time Switched Linear Systems
    A Khan, LW Liu, W Xie
    IEEE Sensors Journal, 20(11), 6121-6129, 2020
    Citation: 20
  • Interval State Estimator Design for Linear Parameter Varying (LPV) Systems
    A Khan, X Bai, Z Bo, P Yan
    IEEE Transactions on Circuits and Systems II: Express Briefs, 68(8), 2865-2869, 2021
    Citation: 19
  • Finite‐time functional interval observer for linear systems with uncertainties
    L Liu, W Xie, A Khan, L Zhang
    IET Control Theory & Applications, 14(18), 2868-2878, 2020
    Citation: 14
  • Fault detection and diagnosis for a class of linear time-varying (LTV) discrete-time uncertain systems using interval observers
    Z Yi, W Xie, A Khan, B Xu
    2020 39th Chinese Control Conference (CCC), 4124-4128, 2020
    Citation: 14
  • Interval State Estimator Design Using the Observability Matrix for Multiple Input Multiple Output Linear Time-Varying Discrete-Time Systems
    A Khan, W Xie
    IEEE Access, 7, 167566-167576, 2019
    Citation: 13