Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

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Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

Phd Candidate at University of Exeter, United Kingdom

Amir Hossein Poursaeed is an accomplished researcher in electrical engineering with a specialization in power systems, machine learning applications, and renewable energy integration. Holding a Master’s degree from Lorestan University, he has developed a strong academic foundation complemented by an exceptional research portfolio. His work focuses on power system protection, stability, and optimization using advanced AI techniques such as explainable deep learning and quantum neural networks. With over 17 peer-reviewed journal publications, many in Q1 journals, and multiple IEEE conference contributions, his research demonstrates both depth and innovation. He collaborates with leading academics internationally and has contributed to interdisciplinary studies in environmental modeling and water resource management. Amir’s commitment to cutting-edge research in inverter-based power grids, fault diagnosis, and energy systems places him among the promising young scholars in the field. His achievements reflect a rare blend of technical expertise, research leadership, and forward-looking vision essential for shaping the future of smart grids.

Professional Profile 

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Education

Amir Hossein Poursaeed has a solid educational background in electrical engineering with a focus on power systems. He earned his Master of Science degree from Lorestan University, Iran, where he specialized in Digital Power System Protection and Power System Dynamics. His M.Sc. thesis, supervised by Professor Farhad Namdari, focused on using Support Vector Machines for wide-area protection against voltage and transient instabilities. He previously obtained his Bachelor of Science in Electrical Engineering from the same university, where he explored the optimal placement of phasor measurement units using metaheuristic algorithms. His academic performance was commendable, with a GPA of 18.87/20 in his M.Sc. program, demonstrating both technical strength and research capability. Throughout his education, he consistently focused on high-voltage systems, optimization, and smart grid technologies, laying the foundation for his research in AI-based power system protection and stability. His educational journey highlights a continuous commitment to excellence and innovation in energy systems.

Professional Experience

Amir Hossein Poursaeed has developed a robust professional profile centered around advanced power system research and academic collaboration. While specific institutional roles aren’t explicitly mentioned, his extensive list of high-impact publications indicates active involvement in collaborative research projects, particularly with institutions such as Lorestan University and international partners. He has co-authored multiple studies with recognized scholars, including Professor Farhad Namdari and Dr. P.A. Crossley, highlighting his integration into the global research community. His contributions include the design of advanced fault detection systems, AI-driven stability analysis tools, and renewable energy integration models. Additionally, his work in inter-turn fault diagnosis and real-time system protection showcases applied engineering skills with a focus on practical solutions for modern grid challenges. His experience spans theoretical research, model development, and algorithm implementation in live or simulated systems, establishing him as a well-rounded researcher in academia and an emerging leader in AI-enabled power engineering technologies.

Research Interest

Amir Hossein Poursaeed’s research interests are rooted in the intersection of electrical power systems and artificial intelligence. His primary focus includes power system stability, digital protection systems, fault detection, and the integration of renewable energy sources. He is especially passionate about leveraging advanced machine learning and explainable AI techniques for enhancing grid reliability and system monitoring. His recent work involves deep learning, support vector machines, and quantum neural networks applied to inverter-based power systems and DC microgrids—fields gaining global relevance due to the rise of decentralized energy systems. Optimization algorithms, transient analysis, and wide-area protection schemes are other key domains of his expertise. He also extends his knowledge into environmental systems, working on AI-based models for water quality assessment. This multidisciplinary approach underlines his goal of developing intelligent, robust, and real-time frameworks for smart grid operations, making his research both innovative and impactful in addressing contemporary and future challenges in energy systems.

Award and Honor

Although specific awards and honors are not listed, Amir Hossein Poursaeed’s academic and research accomplishments position him as a candidate deserving of high recognition. His publication record in prestigious Q1 journals, such as Applied Soft Computing, Energy Reports, and Sustainable Energy Technologies and Assessments, reflects scholarly excellence. His papers have introduced novel contributions to power system protection and AI-based monitoring, often co-authored with leading international experts—an indication of his growing reputation in the field. His research has also been accepted at major IEEE conferences, including the International Universities Power Engineering Conference and the International Conference on Electric Power and Energy Conversion Systems, which highlights peer recognition of his work. Moreover, his interdisciplinary research in water resource management using machine learning models demonstrates his versatility and impact beyond core power engineering. Given these achievements, he is highly deserving of academic awards, particularly those that celebrate emerging researchers and innovators in smart energy systems.

Conclusion

Amir Hossein Poursaeed is an emerging thought leader in the field of power systems and intelligent energy technologies. With a strong educational background and a research focus on AI-driven solutions for grid stability and protection, he has consistently demonstrated excellence in both theoretical innovation and practical application. His contributions span power engineering, machine learning, and even environmental sciences—showcasing his ability to bridge disciplines for impactful solutions. Through numerous high-impact publications and international conference engagements, he has established himself as a respected voice in the global research community. His work addresses critical challenges in inverter-based grids, renewable integration, and real-time monitoring, aligning perfectly with the global shift toward sustainable and resilient energy systems. Amir’s trajectory reflects not only technical brilliance but also research leadership, collaboration, and a vision for smarter, safer, and more efficient power systems. He is undoubtedly a strong candidate for honors such as the Best Researcher Award.

Publications Top Notes

  • Title: An Ultra-Fast Directional Protection Scheme for DC Microgrids Based on High-Order Synchrosqueezing Transform
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2023
    Citations: 7

  • Title: Online Transient Stability Assessment Implementing the Weighted Least-Square Support Vector Machine with the Consideration of Protection Relays
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 6

  • Title: A New Strategy for Prediction of Water Qualitative and Quantitative Parameters by Deep Learning-Based Models with Determination of Modelling Uncertainties
    Authors: M. Poursaeid, A.H. Poursaeed
    Year: 2024
    Citations: 6

  • Title: Online Voltage Stability Monitoring and Prediction by Using Support Vector Machine Considering Overcurrent Protection for Transmission Lines
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2020
    Citations: 6

  • Title: High‐Speed Algorithm for Fault Detection and Location in DC Microgrids Based on a Novel Time–Frequency Analysis
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2024
    Citations: 3

  • Title: Hydraulic Modeling of the Water Resources Using Learning Techniques
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2022
    Citations: 3

  • Title: Explainable AI-Driven Quantum Deep Neural Network for Fault Location in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari
    Year: 2025
    Citations: 2

  • Title: Simulation Using Machine Learning and Multiple Linear Regression in Hydraulic Engineering
    Authors: M. Poursaeid, A.H. Poursaeed, S. Shabanlou
    Year: 2023
    Citations: 2

  • Title: Optimized Explainable Tabular Transformer Model for Fault Localization in DC Microgrids
    Authors: A.H. Poursaeed, F. Namdari, P.A. Crossley
    Year: 2025
    Citations: 1

  • Title: Optimal Coordination of Directional Overcurrent Relays: A Fast and Precise Quadratically Constrained Quadratic Programming Solution Methodology
    Authors: A.H. Poursaeed, M. Doostizadeh, S. Hossein Beigi Fard, A.H. Baharvand, F. Namdari
    Year: 2024
    Citations: 1

Velislava Lyubenova | Engineering | Best Researcher Award

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Prof. Velislava Lyubenova | Engineering | Best Researcher Award

Academician at Bulgarian Academy of Science, Institute of Robotics, Bulgaria

Velislava Lyubenova is a distinguished Bulgarian researcher and professor with over 30 years of experience in biotechnological process control, mechatronics, and adaptive systems. She currently serves as the Head of the Mechatronic Bio/technological Systems Section at the Institute of Robotics, Bulgarian Academy of Sciences (BAS), and has held various academic and leadership roles across BAS institutions. She has led more than 10 national and international research projects, participated in numerous European programs, and supervised several PhD students. With over 200 scientific publications, many in high-impact journals, and invited lectures delivered at leading international institutions, she is widely recognized for her scientific contributions. Her expertise includes the development of innovative monitoring and control systems using tools like MATLAB and LABVIEW. An awardee of the “Marin Drinov” prize for young scientists, Lyubenova is also actively involved in academic governance, expert committees, and editorial boards, reflecting her deep commitment to scientific advancement and education.

Professional Profile 

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Education

Velislava Lyubenova holds a strong academic background in technical sciences and engineering. She earned her engineering degree in Radio Electronics from the Technical University of Sofia, followed by a Ph.D. in Automation with a dissertation focused on parameter estimation and biotechnological process monitoring. Her academic journey culminated with a Doctor of Technical Sciences degree from the Institute of System Engineering and Robotics (ISIR) at the Bulgarian Academy of Sciences (BAS), specializing in adaptive control and modeling of complex biotechnological systems. Her education blends deep technical knowledge with applied research capabilities, laying the foundation for a career in both theoretical and experimental domains. Her academic formation reflects a continuous pursuit of knowledge and specialization in interdisciplinary areas, preparing her to work across the fields of electronics, biotechnology, and control systems. This educational path has also enabled her to contribute to curriculum development and mentor future generations of researchers in her field.

Professional Experience

Professor Velislava Lyubenova has built a prolific career at the Bulgarian Academy of Sciences, progressing from a research fellow to a professor and head of department at the Institute of Robotics. Her early work in adaptive and robust control systems evolved into specialized research in bioengineering and mechatronic systems for biotechnology. She has served as Scientific Secretary at IR-BAS and has been a key figure in national expert commissions and scientific councils. Over her career, she has led and coordinated numerous national and international research projects, many involving cross-disciplinary collaboration. Her leadership roles include project management, supervision of PhD students, and delivery of advanced lecture courses. She also coordinates Erasmus programs and plays a pivotal role in academic exchange and cooperation. Her professional trajectory showcases a blend of scientific innovation, team leadership, and academic mentorship, making her a respected figure in both the Bulgarian and broader European research communities.

Research Interest

Velislava Lyubenova’s research is deeply rooted in the interdisciplinary fields of bioengineering, automation, and mechatronics. Her primary interest lies in the modeling, monitoring, and adaptive control of biotechnological processes, where she develops innovative methodologies to improve efficiency and reliability. She integrates control theory with practical applications using environments like MATLAB and LABVIEW, creating real-time monitoring systems that bridge theoretical concepts with industrial needs. Her work often addresses complex system dynamics in bioprocesses and seeks to optimize process performance through intelligent control algorithms. Additionally, she explores knowledge-based and adaptive systems that contribute to the advancement of next-generation biotechnological platforms. Her collaborative research also extends into European Union projects, educational initiatives, and technology transfer programs, reflecting a holistic approach to scientific inquiry. With a strong focus on experimental validation, her research continues to influence the development of advanced technologies in the fields of bioprocess engineering and industrial automation.

Award and Honor

Throughout her distinguished career, Velislava Lyubenova has received notable recognition for her contributions to science and research. A significant early milestone was her receipt of the “Marin Drinov” Young Scientist Award from the General Assembly of the Bulgarian Academy of Sciences in 1998—an honor bestowed upon promising researchers demonstrating exceptional scientific potential. She has also been invited to deliver over 15 specialized lectures at prestigious institutions abroad and six within Bulgaria, signifying her international recognition as a subject-matter expert. Her active involvement in over 30 international and national conferences further underscores her scientific engagement. Beyond individual accolades, her roles as a reviewer, jury member, editorial board member, and lecturer reflect a broader institutional and peer recognition of her expertise. These honors represent both her academic excellence and leadership in advancing science and education, and they demonstrate her lasting impact on the Bulgarian and global research landscape.

Conclusion

Velislava Lyubenova stands out as an accomplished and influential researcher in the fields of biotechnological systems and automation. Her extensive education, progressive professional experience, and leadership in multidisciplinary research projects position her as a key contributor to both national and international scientific advancement. Her ability to combine theoretical models with practical applications, mentor young scientists, and contribute to global academic forums speaks to her depth of expertise and dedication. She has earned peer and institutional recognition for her scientific work, making her a respected leader in her field. Her over 200 publications, contributions to prestigious journals, and active engagement in scientific committees demonstrate both productivity and academic integrity. With a strong foundation in research and innovation, and an enduring commitment to education and collaboration, Velislava Lyubenova is exceptionally well-qualified for honors such as the Best Researcher Award. Her career reflects a lifelong dedication to the pursuit of scientific excellence and societal impact.

Publications Top Notes

  • Title: Indirect adaptive linearizing control of a class of bioprocesses–Estimator tuning procedure
    Authors: MN Ignatova, VN Lyubenova, MR García, C Vilas, AA Alonso
    Year: 2008
    Citations: 31

  • Title: Kinetic characteristics of alcohol fermentation in brewing: state of art and control of the fermentation process
    Authors: V Shopska, R Denkova, V Lyubenova, G Kostov
    Year: 2019
    Citations: 21

  • Title: Adaptive control of fed-batch process for poly-beta-hydroxybutyrate production by mixed culture
    Authors: M Ignatova, V Lyubenova
    Year: 2007
    Citations: 16

  • Title: Control of biotechnological processes-new formalization of kinetics: Theoretical aspects and applications
    Authors: M Ignatova, V Lyubenova
    Year: 2011
    Citations: 15

  • Title: Model-based monitoring of biotechnological processes—a review
    Authors: V Lyubenova, G Kostov, R Denkova-Kostova
    Year: 2021
    Citations: 12

  • Title: Adaptive control of the Simultaneous Saccharification—Fermentation Process from Starch to Ethanol
    Authors: S Ochoa, V Lyubenova, JU Repke, M Ignatova, G Wozny
    Year: 2008
    Citations: 12

  • Title: An efficient hybrid of an ant lion optimizer and genetic algorithm for a model parameter identification problem
    Authors: O Roeva, D Zoteva, G Roeva, V Lyubenova
    Year: 2023
    Citations: 11

  • Title: Control of one stage bio ethanol production by recombinant strain
    Authors: V Lyubenova, S Ochoa, J Repke, M Ignatova, G Wozny
    Year: 2007
    Citations: 11

  • Title: Escherichia coli Cultivation Process Modelling Using ABC-GA Hybrid Algorithm
    Authors: O Roeva, D Zoteva, V Lyubenova
    Year: 2021
    Citations: 10

  • Title: Reaction rate estimators of fed-batch process for poly-β-hydroxybutyrate (PHB) production by mixed culture
    Authors: V Lyubenova, M Ignatova, M Novak, T Patarinska
    Year: 2007
    Citations: 10

  • Title: Dynamics Monitoring of Fed-batch E. coli Fermentation
    Authors: A Zlatkova, V Lyubenova
    Year: 2017
    Citations: 8

  • Title: Encapsulation of brewing yeast in alginate/chitosan matrix: Kinetic characteristics of the fermentation process at a constant fermentation temperature
    Authors: I Petelkov, V Lyubenova, A Zlatkova, V Shopska, R Denkova, M Kaneva, …
    Year: 2016
    Citations: 8

  • Title: On-line estimation in a distributed parameter bioreactor: Application to the Gluconic Acid production
    Authors: MR García, C Vilas, E Balsa-Canto, VN Lyubenova, MN Ignatova, …
    Year: 2011
    Citations: 8

  • Title: Metaheuristic algorithms: theory and applications
    Authors: S Ribagin, V Lyubenova
    Year: 2021
    Citations: 7

  • Title: CASCADE SENSOR FOR MONITORING OF DENITRIFICATION IN ACTIVATED SLUDGE WASTEWATER TREATMENT PROCESS
    Authors: V Lyubenova, M Ignatova
    Year: 2011
    Citations: 7

Charly Julien Nyobe | Civil Engineering | Best Paper Award

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Dr. Charly Julien Nyobe | Civil Engineering | Best Paper Award

Chercheur at Ecole Normale Supérieure d’Enseignement Technique de Douala-Cameroun, Cameroon.

Charly Julien Nyobe 🎓 is a dedicated Cameroonian researcher and educator specializing in civil engineering, biomechanics, and material sciences. Born on March 11, 1985, in Garoua-Boulaï, he has pursued an extensive academic career, earning two PhDs and multiple engineering degrees. With a passion for structural mechanics, wood engineering, and impact mechanics, he actively contributes to cutting-edge research on sustainable construction materials. Currently, he teaches at the University of Douala and collaborates on international projects. An expert in statistical analysis, finite element methods, and material characterization, Nyobe is committed to advancing engineering solutions for real-world challenges. 🚀📚

Professional Profile:

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Google Scholar

Suitability for the Award

Dr. Charly Julien Nyobe is a highly accomplished researcher in civil engineering, biomechanics, and material sciences, with extensive expertise in structural mechanics, wood engineering, and impact mechanics. His strong academic background, dual PhDs, and consistent research contributions demonstrate a deep commitment to advancing engineering knowledge, particularly in sustainable construction materials. His ability to bridge experimental, numerical, and theoretical methods in engineering makes him a strong contender for the Best Paper Award.

Education & Experience 📚

✅ Doctorate (PhD) in Mechanical Engineering – Université Gustave Eiffel, France (2022 – Ongoing)
✅ Doctorate (PhD) in Civil Engineering – École Nationale Supérieure Polytechnique de Yaoundé, Cameroon (2023)
✅ Master’s in Civil Engineering – University of Douala, Cameroon (2015)
✅ DIPET II (Master’s equivalent) in Civil Engineering – ENSET Douala, Cameroon (2011)
✅ DIPET I (Bachelor’s equivalent) in Civil Engineering – ENSET Douala, Cameroon (2009)
✅ DEUG in Computer Science – University of Yaoundé I, Cameroon (2006)
✅ Baccalauréat in Mathematics & Physics – Lycée d’Obala, Cameroon (2003)

💼 Work Experience:
✔️ Lecturer – University of Douala (2018 – Present)
✔️ Visiting Lecturer – École Supérieure de La Salle (2018 – 2022)
✔️ Lecturer – Institute of Technology, Douala (2018 – 2020)
✔️ Civil Engineering Teacher – Lycée Polyvalent de Bonabéri (2012 – 2018)

Professional Development 🚀

Charly Julien Nyobe is constantly engaged in professional development to stay at the forefront of engineering innovations. In 2023, he trained in LS-Dyna at IUT Lyon 1, France, refining his expertise in impact simulation and finite element modeling. Additionally, he enhanced his scientific visualization skills through an Inkscape training at the University of Lyon. As a member of the GDR Science du Bois (France) since 2019, he actively participates in collaborative research, focusing on wood mechanics, structural engineering, and impact analysis. His interdisciplinary approach blends experimental, numerical, and theoretical methods for innovative engineering solutions. 🌍🛠️📊

Research Focus 🔬

Dr. Nyobe’s research is centered on civil engineering, wood mechanics, and impact mechanics. His work spans mechanical characterization of materials, structural resilience, and numerical modeling. He is passionate about sustainable construction, particularly the use of tropical woods in engineering applications. His studies explore Monte Carlo simulations, Weibull statistical models, and multi-scale mechanical classification of materials. He also delves into shock mechanics, investigating crash simulations and road safety barriers using advanced software like LS-Dyna. His research contributes to eco-friendly building solutions, aiming to optimize wood-based engineering materials for durability and resilience. 🌳🏗️⚙️

Awards & Honors 🏆

🏅 2023 – PhD in Civil Engineering with “Très Honorable” distinction 🏛️
🏅 2015 – Master’s degree with “Très Bien” distinction 🎓
🏅 2011 – DIPET II with “Très Bien” distinction 🏗️
🏅 2009 – DIPET I with “Très Bien” distinction 🏢
🏅 2006 – DEUG in Computer Science with “Assez Bien” distinction 💻
🏅 2003 – Baccalauréat in Mathematics & Physics with “Assez Bien” distinction 📏

Publication Top Notes

  • Moisture content-mechanical property relationships for two okan (Cylicodiscus gabunensis) substitutes

    • Authors: Nyobe Charly Julien, Oum Lissouck René, Nyobe Nicolas Stephane, Goumgang Tassile Rolande, Ayina Ohandja Louis Max​
    • Publication Year: 2025​
    • DOI: 10.1080/17480272.2025.2476659​

  • Mode I cracking of three tropical species from Cameroon: the case of bilinga, dabema, and padouk wood

    • Authors: Rosmi Biyo’o, Achille Bernard Biwole, Rostand Moutou Pitti, Charly Julien Nyobe, Benoit Ndiwe, Emile Jonathan Onana, Emmanuel Yamb​
    • Publication Year: 2024​
    • DOI: 10.1080/17480272.2024.2314750​

  • Effect of slope of grain on mechanical properties of some tropical wood species

    • Authors: Charly Julien Nyobe, Nicolas Stéphane Nyobe, Jean Bertin Nkibeu, René Oum Lissouck, Louis Max Ayina Ohandja​
    • Publication Year: 2024​
    • DOI: 10.1080/17480272.2024.2356047​

  • A Review on Methods for Determining the Vibratory Damping Ratio

    • Authors: Nkibeu Jean Bertin, Charly Julien Nyobe, Moussa Sali, Madja Doumbaye Jerémie​
    • Publication Year: 2023​
    • DOI: 10.4236/ojce.2023.132015​

  • Determination of the Vibratory Damping Ratio: A Methodological Review

    • Authors: Nkibeu Jean Bertin, Charly Julien Nyobe, Moussa Sali, Madja Doumbaye Jerémie​
    • Publication Year: 2023​
    • DOI: 10.9734/bpi/rader/v9/1804g​

  • Variability of the mechanical strength of Congo Basin timbers

    • Author: Charly Julien Nyobe​
    • Publication Year: 2021​
    • DOI: 10.1080/17480272.2021.1912173​

Mengyao Li | Engineering | Best Researcher Award

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Dr. Mengyao Li | Engineering | Best Researcher Award

Student at Nanyang Technological University Singapore

Mengyao Li is a dedicated researcher specializing in electromagnetic fields, metasurfaces, and frequency-selective structures. With a strong academic foundation and a passion for advancing next-generation communication and radar technologies, Li has made significant contributions to the field of low-RCS antenna-radome systems, lens antennas, and THz reconfigurable intelligent surfaces. His research focuses on innovative solutions that enhance wave manipulation, beamforming, and scattering control, making a direct impact on applications in wireless communication and stealth technology. As a Ph.D. candidate at Nanyang Technological University (NTU), Singapore, under the guidance of Prof. Shen Zhongxiang (IEEE Fellow), Li has published extensively in top-tier journals and continues to explore novel electromagnetic solutions. His work not only bridges theoretical advancements with practical applications but also aligns with the future demands of 6G wireless networks and advanced sensing technologies, solidifying his position as an emerging expert in the field.

Professional Profile

Education

Mengyao Li began his academic journey with a B.S. in Electrical Engineering from the Communication University of China, Beijing, specializing in Telecommunication Engineering. Graduating in 2020 with a GPA of 3.59/4.0, he ranked among the top 8% of students and was recognized as an Outstanding Graduate of Beijing. His undergraduate research focused on reconfigurable frequency-selective absorbers, laying a strong foundation for his future work. In January 2021, he pursued a Ph.D. in Electrical and Electronic Engineering at Nanyang Technological University, Singapore, specializing in Electromagnetic Fields and Microwave Technology. Under the supervision of Prof. Shen Zhongxiang, his doctoral research centers on low-RCS integrated radome and antenna systems, aiming to develop advanced solutions for stealth technology and wireless communication. Throughout his academic career, Li has demonstrated strong analytical skills and research capabilities, contributing to the advancement of electromagnetic and antenna engineering.

Professional Experience

As a Ph.D. researcher at Nanyang Technological University, Mengyao Li has been actively engaged in cutting-edge research in the field of electromagnetic wave manipulation, metasurfaces, and antenna systems. His professional work focuses on designing low-RCS antennas, frequency-selective structures, and THz reconfigurable intelligent surfaces, contributing to innovations in stealth technology and high-frequency communication. Collaborating with leading academics and industry experts, he has developed practical solutions for beam manipulation, conformal lens antennas, and ultra-wideband absorptive structures. His research has been published in top IEEE journals, showcasing his ability to bridge theoretical concepts with practical engineering applications. In addition to research, he actively mentors junior researchers, contributes to technical discussions, and engages in academic collaborations to advance antenna and metamaterial technologies. His expertise and technical acumen make him a promising figure in the field of advanced electromagnetic applications.

Research Interests

Mengyao Li’s research interests lie at the intersection of electromagnetic wave engineering, metasurfaces, and reconfigurable intelligent surfaces (RIS), with a strong emphasis on low-RCS antenna-radome systems, lens antennas, and THz wireless communication. His work on low-scattering antenna structures contributes to stealth and radar applications, while his innovative metasurface designs enable advanced beam steering and polarization control. Additionally, he explores MEMS-based THz metasurfaces, which hold promise for 6G wireless networks and high-frequency communication systems. His research on frequency-selective structures and transmissive antennas bridges the gap between traditional electromagnetic theory and modern reconfigurable technologies. By integrating material science, physics, and advanced fabrication techniques, Li’s research aims to create high-performance, miniaturized, and dynamically tunable electromagnetic structures, making a significant impact on next-generation wireless technologies and radar systems.

Awards and Honors

Throughout his academic journey, Mengyao Li has received multiple recognitions for his research excellence. As an Outstanding Graduate of Beijing, he was acknowledged for his academic performance and early contributions to telecommunication engineering. His Ph.D. research at NTU has been supported by prestigious funding, reflecting the significance of his work in low-RCS antenna systems and metasurface engineering. His journal publications in IEEE Transactions on Antennas and Propagation and IEEE Antennas Wireless Propagation Letters further highlight his research impact in the field. Li’s innovative contributions to reconfigurable intelligent surfaces and frequency-selective radomes have been well-received in the academic community, earning him invitations to collaborate with leading researchers. With his strong research background and growing influence in electromagnetic wave control and antenna design, he continues to make valuable contributions to the field, positioning himself as a rising expert in advanced electromagnetics and wireless technology.

Conclusion

Mengyao Li is a strong candidate for the Best Researcher Award, with a solid publication record, cutting-edge research contributions, and expertise in emerging electromagnetic technologies. However, improving the real-world impact, conference visibility, and interdisciplinary collaboration could further solidify the case for this award. If these areas are strengthened, Mengyao Li could become a leading figure in electromagnetic and metasurface research.

Publications Top Noted

  • Y. Ding, M. Li, J. Su, Q. Guo, H. Yin, Z. Li, J. Song – 2020 – 70 citations
    “Ultrawideband frequency-selective absorber designed with an adjustable and highly selective notch.”
    IEEE Transactions on Antennas and Propagation 69 (3), 1493-1504

  • M. Li, L. Zhou, Z. Shen – 2021 – 30 citations
    “Frequency selective radome with wide diffusive bands.”
    IEEE Antennas and Wireless Propagation Letters 21 (2), 327-331

  • M. Li, Z. Shen – 2023 – 13 citations
    “Low-RCS transmitarray based on 2.5-D cross-polarization converter.”
    IEEE Transactions on Antennas and Propagation 71 (7), 5828-5837

  • M. Li, Z. Shen – 2023 – 5 citations
    “Integrated diffusive antenna array of low backscattering.”
    IEEE Antennas and Wireless Propagation Letters

  • M. Li, Z. Shen – 2022 – 3 citations
    “Hybrid Frequency Selective Rasorber Combining 2-D and 3-D Resonators.”
    2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI

  • M. Li, J. Su – 2020 – 1 citation
    “Wideband frequency-selective absorber based on metal cross ring.”
    2020 IEEE MTT-S International Microwave Workshop Series on Advanced

  • M. Li, Z. Shen – 2024 – Not yet cited
    “Hybrid Rasorber Based on 3-D Bandpass Frequency-Selective Structures.”
    IEEE Antennas and Wireless Propagation Letters

  • M. Li – 2024 – Not yet cited
    “Integrated radome and antenna systems of low radar cross section.”
    Nanyang Technological University (Ph.D. Dissertation)

  • M. Li, Z. Shen – 2023 – Not yet cited
    “Highly Selective Third-Order Bandpass Frequency Selective Surface.”
    2023 International Conference on Electromagnetics in Advanced Applications

  • M. Li, Z. Shen – 2023 – Not yet cited
    “Transmission Phase Controllable Rasorber Using All-Metal Cross-Polarization Converter.”
    2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI

  • M. Li, Z. Shen – 2022 – Not yet cited
    “Low-RCS Transmitarray Using Phase Controllable Absorptive Frequency-Selective Structure.”
    2022 International Conference on Electromagnetics in Advanced Applications

  • M. Li, Z. Shen – 2021 – Not yet cited
    “RCS Reduction of Slot Antenna Array Using Coding Metasurfaces.”
    2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI

Chung-Horng Lung | Engineering | Best Researcher Award

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Chung-Horng Lung | Engineering | Best Researcher Award

Full Professor at Carleton University, Canada

Dr. Chung-Horng Lung is a distinguished professor in the Department of Systems and Computer Engineering at Carleton University, Ottawa. With a career spanning over three decades in academia and industry, he has made significant contributions to software engineering, network security, and artificial intelligence. Recognized as one of the world’s top 2% most-cited researchers (Stanford-Elsevier, 2022 & 2023), his work has influenced various domains, including machine learning-based security systems, intelligent data processing, and network optimization. Prior to joining Carleton University, he held senior engineering positions at Nortel Networks, where he worked on software architecture, network traffic engineering, and MPLS-based communication technologies. His extensive research, mentorship, and interdisciplinary collaborations have earned him a reputation as a leading scholar in his field. Alongside his academic contributions, Dr. Lung is also a Professional Engineer (P.Eng.) in Ontario, further validating his expertise and impact in the engineering community.

Professional Profile

Education

Dr. Lung holds a Ph.D. in Computer Science and Engineering from Arizona State University, Tempe, earned in 1994. His journey in academia began with a Master’s degree in Computer Science and Engineering from the same institution in 1988, following a Bachelor’s degree in Computer Science and Engineering from Chung-Yuan Christian University, Taiwan, in 1982. His academic background provided him with a strong foundation in software engineering, network security, and intelligent computing. During his doctoral studies, he worked extensively on distributed systems and software engineering methodologies, laying the groundwork for his future research. His educational trajectory showcases a commitment to innovation and excellence, equipping him with the expertise needed to bridge academia and industry. Through continuous learning and research advancements, Dr. Lung has remained at the forefront of emerging technologies in computing and engineering.

Professional Experience

Dr. Lung has a rich professional background in both academia and industry. He is currently a Professor at Carleton University, where he has been a faculty member since 2001. Before becoming a full professor in 2015, he served as an Associate Professor in the same department. His industry experience includes senior roles at Nortel Networks, where he worked as a Senior Software Designer and Network Engineer on Optical Packet Interworking and MPLS-based Traffic Engineering. He was also a Senior Software Architecture Engineer at Nortel’s Software Engineering Analysis Lab (SEAL), contributing to critical advancements in software engineering and network technologies. Additionally, he has worked as an Instructor and Research Assistant at Arizona State University and a Software Engineer at Electronics Research & Service Organization in Taiwan. His diverse career path reflects his versatility and expertise in both theoretical and applied computing disciplines.

Research Interests

Dr. Lung’s research focuses on machine learning, cybersecurity, software engineering, and network optimization. His work in machine learning-based intrusion detection systems (IDS) has led to the development of AI-driven security solutions for SCADA and power systems. Additionally, his research on knowledge graphs and unstructured data processing has contributed to advancements in data-driven decision-making. His expertise extends to network traffic analysis, software reliability engineering, and intelligent data sampling, with applications in forest fire detection, industrial automation, and smart city infrastructures. His interdisciplinary approach has fostered collaborations with academic institutions, industry partners, and government agencies, ensuring that his research has real-world impact. By integrating AI, cybersecurity, and software engineering principles, Dr. Lung continues to explore innovative solutions to modern technological challenges.

Awards and Honors

Dr. Lung has received numerous accolades throughout his career, with his most notable recognition being listed among the world’s top 2% most-cited scholars (Stanford-Elsevier, 2022 & 2023). This honor reflects the global impact of his research and his contributions to computer science and engineering. Additionally, he is a registered Professional Engineer (P.Eng.) in Ontario, demonstrating his adherence to the highest professional standards in engineering. Over the years, he has received multiple best paper awards, research grants, and industry recognitions for his work in machine learning, cybersecurity, and network optimization. His mentorship of students and early-career researchers has also been acknowledged through teaching excellence awards and faculty recognitions. With a distinguished academic and professional career, Dr. Lung continues to push the boundaries of innovation in computing and engineering, solidifying his position as a leading researcher in the field.

Conclusion

Dr. Chung-Horng Lung is a highly qualified and impactful researcher, making significant contributions in Computer Science, Machine Learning, and Network Engineering. His strong publication record, industry experience, and citation impact make him a strong contender for the Best Researcher Award. Addressing minor gaps in funding details, patents, and international collaborations could further strengthen his case.

Publications Top Noted

📖 Journal Articles

1️⃣ In-Network Caching for ICN-Based IoT (ICN-IoT): A Comprehensive Survey 🏆

  • Author(s): Zhang, Z., Lung, C.-H., Wei, X., Chatterjee, S., Zhang, Z.
  • Year: 2023
  • Citations: 41 🔥
  • Published in: IEEE Internet of Things Journal

2️⃣ iCache: An Intelligent Caching Scheme for Dynamic Network Environments in ICN-Based IoT Networks 🧠

  • Author(s): Zhang, Z., Wei, X., Lung, C.-H., Zhao, Y.
  • Year: 2023
  • Citations: 17 📈
  • Published in: IEEE Internet of Things Journal

3️⃣ Knowledge Graph Generation and Application for Unstructured Data Using Data Processing Pipeline 🤖

  • Author(s): Sukumar, S.T., Lung, C.-H., Zaman, M., Panday, R.
  • Year: 2024
  • Citations: 0 (New Publication) 🚀
  • Published in: IEEE Access

🎤 Conference Papers

4️⃣ A Federated Learning Framework Based on Spatio-Temporal Agnostic Subsampling (STAS) for Forest Fire Prediction 🔥

  • Author(s): Mutakabbir, A., Lung, C.-H., Ajila, S.A., Sampalli, S., Ravichandran, T.
  • Year: 2024
  • Citations: 0 (New Publication) 🚀
  • Published in: IEEE COMPSAC 2024

5️⃣ Comparative Analysis of Real-Time Data Processing Architectures: Kafka versus MQTT Broker in IoT 📡

  • Author(s): Ho, C.L.D., Lung, C.-H., Mao, Z.
  • Year: 2024
  • Citations: 0 (New Publication) 🚀
  • Published in: IEEE ICEIB 2024

6️⃣ DDoS Flood Detection and Mitigation using SDN and Network Ingress Filtering – an Experiment Report 🛡️

  • Author(s): Marleau, S., Rahman, P., Lung, C.-H.
  • Year: 2024
  • Citations: 0 (New Publication) 🚀
  • Published in: IEEE ICEIB 2024

7️⃣ Big Data Synthesis and Class Imbalance Rectification for Enhanced Forest Fire Classification Modeling 🔥📊

  • Author(s): Tavakoli, F., Naik, K., Zaman, M., Lung, C.-H., Ravichandran, T.
  • Year: 2024
  • Citations: 0 (New Publication) 🚀
  • Published in: International Conference on Agents and Artificial Intelligence

8️⃣ Forest Fire Prediction Using Multi-Source Deep Learning 🌲🔥

  • Author(s): Mutakabbir, A., Lung, C.-H., Ajila, S.A., Purcell, R., Sampalli, S.
  • Year: 2024
  • Citations: 0 (New Publication) 🚀
  • Published in: LNICST Conference Proceedings

9️⃣ A Data Integration Framework with Multi-Source Big Data for Enhanced Forest Fire Prediction 🌍🔥

  • Author(s): Kaur, P., Naik, K., Purcell, R., Zaman, M., Mutakabbir, A.
  • Year: 2023
  • Citations: 1 📊
  • Published in: IEEE Big Data 2023

🔟 Unstructured Transportation Safety Board Findings Categorization Using the Knowledge Graph Pipeline 🚗📊

  • Author(s): Panday, R., Lung, C.-H.
  • Year: 2023
  • Citations: 1 🏆
  • Published in: IEEE Big Data 2023