Dr. Amir Hossein Poursaeed | Engineering | Best Researcher Award

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.

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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

Dr. Oluwole Famoriji | Electrical and Electronics Engineering | Best Researcher Award

Dr. Oluwole Famoriji | Electrical and Electronics Engineering | Best Researcher Award

Assoc. Prof. at University of Johannesburg, South Africa

Engr. Dr. Oluwole John Famoriji is an accomplished academic and researcher in Electrical and Information Engineering, with specialization in Communication Engineering, Antenna Array Signal Processing, and Artificial Intelligence. He holds a Ph.D. in Electronic Science and Technology from the University of Science and Technology of China, backed by numerous awards, including the prestigious CAS-TWAS President’s Fellowship and the Innovation Spirit Award. With over a decade of teaching and research experience across Nigeria, China, and South Africa, he currently serves as an Associate Professor at Achievers University, Owo. Dr. Famoriji is a recognized reviewer for top-tier journals like IEEE Access and IET Communications and has served as an external examiner at international universities. He is a member of COREN, NSE, and IEEE, and is proficient in simulation tools such as MATLAB and CST. His work reflects a strong blend of academic rigor, global collaboration, and practical application in modern engineering challenges.

Professional Profile 

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Education

Engr. Dr. Oluwole John Famoriji has a well-rounded and international academic background in Electrical and Electronics Engineering. He earned his Ph.D. in Electronic Science and Technology from the University of Science and Technology of China (USTC) in 2019, under the prestigious CAS-TWAS Presidential Fellowship. Prior to that, he obtained his M.Eng. in Communication Engineering from the Federal University of Technology, Akure in 2014, and his B.Eng. in Electrical/Electronics Engineering from Ladoke Akintola University of Technology in 2009. His early education was completed in Igbajo, Osun State, Nigeria. Throughout his academic journey, he demonstrated consistent excellence, culminating in international recognition during his Ph.D. studies. His education spans both advanced theoretical frameworks and applied technical training, positioning him effectively in fields like signal processing, antennas, and intelligent systems. Dr. Famoriji’s educational path reflects a strong foundation for high-impact research and global academic collaboration.

Professional Experience

Dr. Oluwole John Famoriji brings over 14 years of progressive academic and research experience across Africa and Asia. He is currently an Associate Professor at Achievers University, Owo, Nigeria, where he teaches and supervises projects in Communication Engineering and Signal Processing. Prior roles include a Postdoctoral Fellowship at the University of Johannesburg (2021–2023) and various teaching positions at Afe Babalola University, where he rose from Lecturer II to Senior Lecturer between 2014 and 2021. He also served as a Teaching Assistant at the Federal University of Technology, Akure, and completed his NYSC teaching at Federal Polytechnic, Kaura Namoda. Dr. Famoriji has demonstrated academic leadership and global engagement, serving as an external examiner in both China and South Africa. His career trajectory showcases a blend of teaching excellence, mentorship, and research productivity, making him a respected figure in the engineering education community.

Research Interest

Dr. Famoriji’s research focuses on advanced topics in Communication Engineering, particularly Antenna Array Signal Processing, Applied Electromagnetics, RF Propagation, and Artificial Intelligence. His work integrates theoretical modeling with practical engineering solutions, using tools such as MATLAB, HFSS, CST, and OptiSystem. His interests extend into intelligent systems and soft computing, emphasizing adaptive technologies in wireless communications and biomedical applications. His contributions aim to solve real-world engineering problems, including efficient spectrum use, smart antenna systems, and AI-driven communication protocols. Through interdisciplinary approaches, Dr. Famoriji seeks to enhance connectivity, signal clarity, and system intelligence in modern communication networks. He has actively contributed as a reviewer for renowned journals like IEEE Access, IET Signal Processing, and IEEE Transactions on Antennas and Propagation, reflecting his expertise and peer recognition in the field. His ongoing research supports the advancement of next-generation wireless and intelligent communication systems across academic and industrial applications.

Award and Honor

Dr. Oluwole John Famoriji has received several prestigious awards that highlight his academic excellence and research impact. Most notably, he was awarded the CAS-TWAS Ph.D. President Fellowship by the Chinese Academy of Sciences and The World Academy of Sciences, an internationally competitive recognition for outstanding doctoral scholars. During his Ph.D. at USTC, he also received the Innovation Spirit Award (2016) and Outstanding Research Assistant Award (2017) from the Micro-/Nano Electronic Systems Integration Center. These accolades underscore his creativity, work ethic, and innovation in high-tech research environments. In addition, he is an active member of global engineering bodies such as the IEEE, the Nigerian Society of Engineers (NSE), and the Council for the Regulation of Engineering in Nigeria (COREN). His service on technical committees and student leadership roles further reflect his commitment to academic and professional excellence. These honors position him as a standout researcher in his field.

Conclusion

Dr. Oluwole John Famoriji is a dynamic and accomplished researcher whose career spans high-level academic training, impactful research, and international collaboration. His expertise in Communication Engineering, RF technologies, and intelligent systems has contributed significantly to academic advancement and real-world engineering applications. His trajectory—from a Ph.D. fellow in China to an Associate Professor in Nigeria and a Postdoctoral Fellow in South Africa—illustrates his global outlook and commitment to research excellence. With numerous awards, strong publication review credentials, and leadership roles in academic settings, he exemplifies the qualities of an innovative scholar and mentor. Although more detail on publications and grant leadership would further strengthen his profile, Dr. Famoriji’s blend of experience, technical depth, and academic service makes him a compelling candidate for recognition such as the Best Researcher Award. His work continues to inspire collaboration and advancement in the field of electrical and communication engineering.

Publications Top Notes

  • Title: An intelligent deep learning-based direction-of-arrival estimation scheme using spherical antenna array with unknown mutual coupling
    Authors: OJ Famoriji, OY Ogundepo, X Qi
    Year: 2020
    Citations: 58

  • Title: Radio frequency propagation mechanisms and empirical models for hilly areas
    Authors: FJ Oluwole, OY Olajide
    Year: 2013
    Citations: 54

  • Title: Channel Estimation and Peak‐to‐Average Power Ratio Analysis of Narrowband Internet of Things Uplink Systems
    Authors: MS Ali, Y Li, MKH Jewel, OJ Famoriji, F Lin
    Year: 2018
    Citations: 28

  • Title: Evaluation and modelling of UHF radiowave propagation in a forested environment
    Authors: T Ayekomilogbon Olufemi, O Famoriji John, O Olasoji Yekeen
    Year: 2013
    Citations: 28

  • Title: Electromagnetic machine learning for estimation and mitigation of mutual coupling in strongly coupled arrays
    Authors: OJ Famoriji, T Shongwe
    Year: 2023
    Citations: 27

  • Title: Design of a multiband hexagonal patch antenna for wireless communication systems
    Authors: AO Fadamiro, JD Ntawangaheza, OJ Famoriji, Z Zhang, F Lin
    Year: 2022
    Citations: 24

  • Title: Source Localization of EM Waves in the Near‐Field of Spherical Antenna Array in the Presence of Unknown Mutual Coupling
    Authors: OJ Famoriji, T Shongwe
    Year: 2021
    Citations: 22

  • Title: A test of the relationship between refractivity and radio signal propagation for dry particulates
    Authors: FJ Oluwole, OM Olayinka
    Year: 2013
    Citations: 22

  • Title: Path loss prediction in Tropical regions using machine learning techniques: A case study
    Authors: OJ Famoriji, T Shongwe
    Year: 2022
    Citations: 20

  • Title: Design of H-Tree fractal slots frequency reconfigurable hexagonal patch antenna using PIN diodes
    Authors: AO Fadamiro, OJ Famoriji, RS Zakariyya, Z Zhang, F Lin
    Year: 2019
    Citations: 20

  • Title: Critical review of basic methods on DoA estimation of EM waves impinging a spherical antenna array
    Authors: OJ Famoriji, T Shongwe
    Year: 2022
    Citations: 19

  • Title: Direction-of-arrival estimation of electromagnetic wave impinging on spherical antenna array in the presence of mutual coupling using a multiple signal classification method
    Authors: OJ Famoriji, T Shongwe
    Year: 2021
    Citations: 19

  • Title: A multiple element calibration algorithm for active phased array antenna
    Authors: AO Fadamiro, AAH Semomhe, OJ Famoriji, F Lin
    Year: 2019
    Citations: 19

  • Title: Design of a simple circularly polarised dual‐frequency reconfigurable microstrip patch antenna array for millimetre‐wave applications
    Authors: OJ Famoriji, S Yang, Y Li, W Chen, A Fadamiro, Z Zhang, F Lin
    Year: 2019
    Citations: 18

  • Title: Multi-source DoA estimation of EM waves impinging spherical antenna array with unknown mutual coupling using relative signal pressure based multiple signal classification approach
    Authors: OJ Famoriji, T Shongwe
    Year: 2022
    Citations: 16

Xingjia Li | Engineering | Best Researcher Award

Dr. Xingjia Li | Engineering | Best Researcher Award

Senior Engineer at Shanghai Liangxin Electrical Co. Ltd, China

Dr. Xingjia Li is a promising early-career researcher who earned his Ph.D. in Mechanical Engineering from Jiangsu University in 2023. He is currently a Postdoctoral Associate at the postdoctoral workstation of Shanghai Liangxin Electrical Co., Ltd. in Shanghai, China. His research focuses on robotics and electrical systems, with a particular emphasis on sensor data processing using machine learning techniques. Dr. Li is dedicated to advancing human-centered applications by enhancing the reliability, intelligence, and security of robotic systems in daily life. His interdisciplinary approach integrates mechanical engineering, electronics, and artificial intelligence, aligning with the evolving demands of modern technology. While still in the early stages of his research career, his industry collaboration and applied research focus position him as a strong candidate for future leadership in his field. Dr. Li’s work holds potential for significant contributions to smart systems and intelligent automation in real-world environments.

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Education

Dr. Xingjia Li obtained his Ph.D. in Mechanical Engineering from Jiangsu University, Zhenjiang, China, in 2023. During his doctoral studies, he focused on the integration of robotics and intelligent systems, building a strong foundation in both theoretical and applied aspects of mechanical and electrical engineering. His education emphasized sensor systems, automation, and machine learning, which prepared him for interdisciplinary research and practical implementation in advanced robotics. Dr. Li demonstrated strong academic performance and research capabilities throughout his graduate studies, contributing to academic discussions and research forums. His educational background reflects a rigorous training in engineering principles, analytical thinking, and innovation, which has shaped his approach to problem-solving in complex systems. Through research projects, seminars, and collaboration with faculty, he developed a deep understanding of how mechanical systems can be enhanced through intelligent control and data-driven methods, laying the groundwork for his postdoctoral research and future contributions to intelligent automation.

Professional Experience

Following his Ph.D., Dr. Xingjia Li joined the postdoctoral workstation at Shanghai Liangxin Electrical Co., Ltd., a key player in the electrical technology industry. In this role, he has been actively involved in research and development, focusing on advanced robotics and intelligent systems. His work emphasizes real-world implementation of sensor-based machine learning techniques to enhance system performance, reliability, and human-machine interaction. At Liangxin, Dr. Li collaborates with both engineering teams and academic partners to design and improve intelligent robotic systems that can operate efficiently in complex environments. His professional experience bridges academia and industry, allowing him to apply theoretical models to practical challenges in automation and electrical systems. This hands-on engagement with cutting-edge technologies has not only expanded his technical skill set but also positioned him as a valuable contributor in the emerging fields of smart manufacturing and AI-powered industrial automation, where reliability and adaptive performance are critical.

Research Interest

Dr. Xingjia Li’s research interests lie at the intersection of robotics, electrical systems, and machine learning, with a strong focus on sensor data processing for human-centered applications. He is passionate about enhancing the intelligence, reliability, and safety of robotic systems operating in dynamic environments. His work aims to empower robots with the ability to interpret complex sensory inputs through machine learning algorithms, thereby enabling real-time decision-making and adaptive behavior. He is particularly interested in applications that improve quality of life, such as assistive robotics, industrial automation, and intelligent monitoring systems. By integrating advanced data analytics and control strategies, Dr. Li seeks to develop systems that can function autonomously with minimal human intervention while maintaining high levels of trust and safety. His interdisciplinary approach combines the strengths of mechanical design, signal processing, and artificial intelligence, positioning him to contribute meaningfully to the advancement of next-generation robotics and smart systems.

Award and Honor

As a rising researcher in the field of intelligent robotics, Dr. Xingjia Li is at the beginning of his professional recognition journey. While specific awards and honors have not been listed in the available information, his acceptance into a postdoctoral research position at Shanghai Liangxin Electrical Co., Ltd. itself signifies recognition of his academic potential and technical proficiency. The opportunity to work in a dedicated industrial research environment reflects a high level of trust in his expertise and capability to contribute to meaningful innovation. His early involvement in cutting-edge projects and interdisciplinary work also positions him as a strong candidate for future academic and industrial awards. As he continues to publish research, develop prototypes, and contribute to real-world solutions, it is expected that Dr. Li will accumulate professional honors that recognize his growing impact in the fields of robotics, electrical systems, and intelligent automation technologies.

Conclusion

Dr. Xingjia Li is an emerging researcher whose interdisciplinary expertise bridges mechanical engineering, robotics, and artificial intelligence. With a strong educational foundation from Jiangsu University and practical postdoctoral experience at Shanghai Liangxin Electrical Co., Ltd., he is well-positioned to make significant contributions to the field of intelligent systems. His research aims to improve human-robot interaction and automation reliability through advanced sensor data processing and machine learning techniques. Though still in the early stages of his career, Dr. Li’s work shows great promise for practical impact in industry and society. His commitment to innovation, real-world application, and cross-disciplinary collaboration sets the stage for a distinguished research trajectory. With continued focus, publication, and recognition, Dr. Li has the potential to emerge as a thought leader in the development of smart, adaptive, and secure robotic systems that support both industrial and human-centered needs.

Publications Top Notes

Velislava Lyubenova | Engineering | Best Researcher Award

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

Shekhar Suman | Engineering | Young Scientist Award

Dr. Shekhar Suman | Engineering | Young Scientist Award

Research Scientist at Borah University of Texas at Tyler, United States

Dr. Shekhar Suman Borah is a Post-Doctoral Research Associate at the Centre of Robotics & Intelligent Systems, University of Texas at Tyler, USA. He holds a Ph.D. in Electronics & Communication Engineering from IIIT Guwahati, with a strong academic foundation in Analog VLSI Design, Memristors, and Signal Processing. His prolific research output includes over 25 publications in reputed journals and conferences, four book chapters, and editorial and peer-review contributions to leading journals. Dr. Borah has also secured research funding for AI-based hardware-software systems and contributed to projects at Bhabha Atomic Research Centre. His work spans advanced circuit design, environmental sensing, and precision agriculture using UAVs. He has delivered invited talks and participated in international conferences across India, the USA, and Japan. A committed IEEE member, Dr. Borah combines technical excellence with interdisciplinary collaboration, positioning him as a promising candidate for awards recognizing young scientific talent.

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Education

Dr. Shekhar Suman Borah has a strong academic foundation in electronics and communication engineering. He earned his Ph.D. from the Indian Institute of Information Technology (IIIT) Guwahati in 2022, where he specialized in analog signal processing and current-mode circuit design. Prior to this, he completed his M.Tech with First Class from KIIT University, Bhubaneswar, and his B.E. from Visvesvaraya Technological University, Karnataka, also with First Class honors. His academic journey reflects a consistent focus on electronics, signal processing, and circuit design, particularly in analog VLSI systems. During his doctoral studies, he developed expertise in the use of memristors, current-mode building blocks, and oscillator/filter design, forming the basis for much of his later research. His educational trajectory demonstrates both depth and specialization, equipping him with the technical proficiency and theoretical grounding necessary for advanced research and innovation in modern electronics and intelligent systems.

Professional Experience

Dr. Borah currently serves as a Post-Doctoral Research Associate at the Centre of Robotics & Intelligent Systems, University of Texas at Tyler, USA. Previously, he was a Research Associate at the Bhabha Atomic Research Centre (BARC), Mumbai, contributing to projects in the Radiation Safety Systems Division. He has over five years of academic teaching assistance experience in labs related to analog VLSI, communication systems, and integrated circuits. His role in grant-funded projects—particularly an AI-based tutoring tool for hardware-software co-design—underscores his engagement in interdisciplinary research. He has collaborated with several international researchers and contributed to publications across areas such as memristive circuits, environmental sensing, UAV applications, and edge computing. His growing leadership in research, combined with a solid background in academic and national research institutions, marks him as a well-rounded scientist with both applied and theoretical expertise across diverse sectors in electronics and intelligent system design.

Research Interest

Dr. Borah’s research interests lie at the intersection of analog VLSI design, current-mode circuits, memristors, signal processing, and computer vision. He is particularly focused on designing energy-efficient, electronically tunable circuits using novel components like current differencing buffered amplifiers (CDBAs) and memristors. His recent work explores the integration of these devices into edge-computing architectures, environmental sensing systems, and wearable electronics. He is also involved in precision agriculture using AI and UAVs for tasks like weed detection and disease assessment, showcasing his multidisciplinary reach. Dr. Borah has a strong inclination toward practical applications of circuit theory, demonstrated by his contributions to automation, energy-efficient design, and AI-driven solutions. His ability to translate theoretical models into real-world engineering solutions makes his work impactful, especially in the context of smart devices and intelligent sensing systems. This diverse and innovative portfolio reflects both his technical depth and adaptability to emerging technological trends.

Award and Honor

Dr. Shekhar Suman Borah has received several awards that highlight his academic excellence and research impact. In 2020, he won the Best Paper Award at the Springer International Conference on Communication, Circuits, and Systems (iC3S) for his innovative work on grounded negative inductance simulation. Earlier in his academic career, he was awarded the SDR Scholarship in 2010 for academic excellence and the prestigious Anandoram Barooah Award by the Government of Assam in 2009 for securing First Class with Distinction in his 10th grade. These accolades reflect both early promise and sustained contributions to his field. His participation as a peer reviewer for reputed journals and conferences like IEEE and MDPI further underscores his professional standing. Additionally, his invited talks at prominent institutions and media appearances demonstrate recognition beyond academia. Collectively, these honors validate Dr. Borah’s trajectory as a high-performing researcher with significant potential for further contributions.

Conclusion

Dr. Shekhar Suman Borah stands out as a highly qualified young researcher with a well-rounded portfolio in education, research, and professional engagement. His academic background is strong and focused, his research contributions are diverse and impactful, and his professional roles demonstrate both leadership and collaboration. He has made meaningful strides in analog circuit design, memristive technologies, and intelligent sensing systems, with applications in agriculture, environmental monitoring, and wearable technology. His ability to secure research funding, contribute to peer-reviewed literature, and deliver invited talks reflects his growing recognition in the field. Dr. Borah’s consistent track record of innovation, coupled with his dedication to both academic excellence and real-world problem-solving, makes him a strong contender for recognition such as the Young Scientist Award. His work promises continued contributions to cutting-edge technologies in electronics and intelligent systems, positioning him as a rising figure in the global scientific community.

Publications Top Notes

  • Title: MOSFET-Based Memristor for High-Frequency Signal Processing
    Authors: M. Ghosh, A. Singh, S.S. Borah, J. Vista, A. Ranjan, S. Kumar
    Year: 2022
    Citations: 46

  • Title: Electronically tunable higher-order quadrature oscillator employing CDBA
    Authors: S.S. Borah, A. Singh, M. Ghosh, A. Ranjan
    Year: 2021
    Citations: 23

  • Title: Resistorless memristor emulators: Floating and grounded using OTA and VDBA for high-frequency applications
    Authors: M. Ghosh, P. Mondal, S.S. Borah, S. Kumar
    Year: 2022
    Citations: 20

  • Title: Third order quadrature oscillator and its application using CDBA
    Authors: M. Ghosh, S.S. Borah, A. Singh, A. Ranjan
    Year: 2021
    Citations: 17

  • Title: Simple Grounded Meminductor Emulator Using Transconductance Amplifier
    Authors: A. Singh, B. S, S., G. M.
    Year: 2021
    Citations: 12

  • Title: A novel memristive neural network circuit and its application in character recognition
    Authors: X. Zhang, X. Wang, Z. Ge, Z. Li, M. Wu, S.S. Borah
    Year: 2022
    Citations: 11

  • Title: CMOS CDBA Based 6th Order Inverse Filter Realization for Low-Power Applications
    Authors: S.S. Borah, A. Singh, M. Ghosh
    Year: 2020
    Citations: 9

  • Title: Three Novel Configurations of Second Order Inverse Band Reject Filter Using a Single Operational Transresistance Amplifier
    Authors: S. Banerjee, S.S. Borah, M. Ghosh, P. Mondal
    Year: 2019
    Citations: 8

  • Title: Emerging Technologies for Automation in Environmental Sensing
    Authors: S.S. Borah, A. Khanal, P. Sundaravadivel
    Year: 2024
    Citations: 5

  • Title: Single VDTA Based Grounded Memristor Model and Its Applications
    Authors: A. Singh, S.S. Borah, M. Ghosh
    Year: 2020
    Citations: 5

  • Title: Current Differencing Buffered Amplifier Based Memristive Quadrature Oscillator
    Authors: A. Singh, S.S. Borah, M. Ghosh
    Year: 2021
    Citations: 4

  • Title: Higher order multifunction filter using current differencing buffered amplifier (CDBA)
    Authors: S.S. Borah, M. Ghosh, A. Ranjan
    Year: 2022
    Citations: 3

  • Title: A Novel Low-Power Electronically Tunable Higher-Order Quadrature Oscillator using CDBA
    Authors: S.S. Borah, A. Singh, M. Ghosh
    Year: 2021
    Citations: 3

  • Title: CDBA Based Quadrature Sinusoidal Oscillator with Non-interactive Control
    Authors: A. Singh, S.S. Borah, M. Ghosh
    Year: 2020
    Citations: 3

  • Title: Design of Thinned Linear Antenna Array using Particle Swarm Optimization (PSO) Algorithm
    Authors: S.S. Borah, A. Deb, J.S. Roy
    Year: 2019
    Citations: 3

Vassilios Sikavitsas | Chemical Engineering | Best Researcher Award

Prof. Vassilios Sikavitsas | Chemical Engineering | Best Researcher Award 

Professor at University of Oklahoma, United States

Professor Vassilios I. Sikavitsas is a distinguished researcher and educator in biomedical and chemical engineering at the University of Oklahoma. With a Ph.D. in Chemical Engineering from SUNY Buffalo and postdoctoral experience at Rice University, his work focuses on tissue engineering, cancer therapeutics, and bioreactor technologies. He has authored numerous high-impact publications and holds patents related to bone tissue engineering and scaffold design. Recognized multiple times as Best Professor by chemical engineering students, he has also mentored award-winning graduate researchers. His research bridges fundamental science and clinical application, notably in cancer exosome-based therapies and dynamic in vitro tumor models. Sikavitsas actively contributes to the scientific community through editorial board service and memberships in leading professional societies such as AIChE, BMES, and TERMIS. His commitment to interdisciplinary innovation, student development, and translational impact positions him as a leading figure in his field and a strong candidate for the Best Researcher Award.

Professional Profile

Google Scholar
Scopus Profile

Education

Professor Vassilios I. Sikavitsas holds a strong academic foundation in chemical engineering. He earned his Ph.D. (2000) and M.S. (1995) in Chemical Engineering from the State University of New York at Buffalo, where he built his expertise in biomaterials and tissue engineering. Prior to his graduate studies in the United States, he obtained a Diploma in Chemical Engineering from Aristotle University of Thessaloniki, Greece, in 1991. His educational trajectory reflects a progressive focus on biomedical applications within engineering, which laid the groundwork for his future research in regenerative medicine and bioreactor technologies. This combination of classical chemical engineering training and biomedical specialization has enabled him to operate at the intersection of engineering and life sciences, a hallmark of his interdisciplinary research. The international scope of his education also contributes to his broad perspective on engineering challenges and biomedical innovation.

Professional Experience

Professor Sikavitsas has built a distinguished academic career at the University of Oklahoma, where he currently serves as a Professor in the School of Chemical, Biological, and Materials Engineering and is affiliated with the Institute of Biomedical Engineering, Science, and Technology. He joined the university as an Assistant Professor in 2002 and was progressively promoted to Associate Professor in 2008 and Full Professor in 2015. His academic journey began with a postdoctoral research appointment in the Department of Bioengineering at Rice University from 2000 to 2002, where he deepened his expertise in tissue engineering. Throughout his academic appointments, he has established a dynamic and productive research laboratory, collaborated across disciplines, and contributed significantly to curriculum development in bioengineering. In addition to his academic duties, he serves on editorial boards and remains active in professional societies, enhancing his engagement with the broader scientific and engineering communities.

Research Interest

Professor Sikavitsas’s research is centered around tissue engineering, regenerative medicine, cancer biology, and bioreactor design. He specializes in the development of 3D biomimetic scaffolds, dynamic in vitro tumor models, and bone tissue constructs using advanced flow perfusion systems. His work investigates the role of mechanical stimulation and surface modifications in cell differentiation and tissue regeneration. In recent years, he has expanded into cutting-edge cancer research, exploring exosome-based drug delivery systems and tumor-immune interactions. His interdisciplinary projects bridge chemical engineering principles with biomedical applications, contributing to both fundamental understanding and clinical translation. Notable innovations include US patents on scaffold technology and tissue construct production. With an emphasis on bioreactor modeling and oxygen transport optimization, his work has practical implications in both regenerative therapies and anti-cancer strategies. His lab’s ability to combine experimental and computational methods distinguishes his contributions in the field of biomedical engineering.

Award and Honor

Professor Sikavitsas has received numerous awards and recognitions that reflect his excellence in research, teaching, and mentorship. He has been honored multiple times as the “Best Chemical Engineering Professor” by senior undergraduate students at the University of Oklahoma, recognizing his dedication to teaching and student engagement. As a research advisor, he has mentored students who have won prestigious accolades, including the Biomedical Engineering Society’s Best Dissertation Award and several Best Poster Awards at regional and national conferences. His achievements are further highlighted by multiple editorial board appointments in respected journals like the Journal of Functional Biomaterials and Scientifica (tissue engineering section). Additionally, his professional affiliations with AIChE, BMES, the Biomaterials Society, and TERMIS underscore his standing in the scientific community. These recognitions demonstrate his well-rounded excellence as a researcher, educator, and mentor, making him a strong role model and leader in his academic field.

Conclusion

Professor Vassilios I. Sikavitsas is a highly accomplished researcher and educator whose work bridges chemical engineering and biomedical science. His academic background, combined with over two decades of professional experience, has positioned him as a leader in tissue engineering, regenerative medicine, and cancer therapeutic research. His innovative work on bioreactors, scaffolds, and cancer exosomes has resulted in numerous peer-reviewed publications, patents, and awards. Equally committed to mentorship and education, he has been recognized for excellence in teaching and for guiding students toward national-level accolades. His involvement in editorial boards and leading scientific societies demonstrates a commitment to the advancement of science and engineering at large. Professor Sikavitsas’s sustained contributions to both research and academic service, along with his interdisciplinary impact, make him a compelling candidate for honors such as the Best Researcher Award. His career reflects a balance of innovation, collaboration, and academic leadership.

Publications Top Notes

  • Title: Fluid flow increases mineralized matrix deposition in 3D perfusion culture of marrow stromal osteoblasts in a dose-dependent manner
    Authors: GN Bancroft, VI Sikavitsas, J Van Den Dolder, TL Sheffield, CG Ambrose, et al.
    Year: 2002
    Citations: 901

  • Title: Biomaterials and bone mechanotransduction
    Authors: VI Sikavitsas, JS Temenoff, AG Mikos
    Year: 2001
    Citations: 815

  • Title: Mineralized matrix deposition by marrow stromal osteoblasts in 3D perfusion culture increases with increasing fluid shear forces
    Authors: VI Sikavitsas, GN Bancroft, HL Holtorf, JA Jansen, AG Mikos
    Year: 2003
    Citations: 595

  • Title: Formation of three‐dimensional cell/polymer constructs for bone tissue engineering in a spinner flask and a rotating wall vessel bioreactor
    Authors: VI Sikavitsas, GN Bancroft, AG Mikos
    Year: 2002
    Citations: 541

  • Title: Design of a flow perfusion bioreactor system for bone tissue-engineering applications
    Authors: GN Bancroft, VI Sikavitsas, AG Mikos
    Year: 2003
    Citations: 529

  • Title: In vitro generated extracellular matrix and fluid shear stress synergistically enhance 3D osteoblastic differentiation
    Authors: N Datta, QP Pham, U Sharma, VI Sikavitsas, JA Jansen, AG Mikos
    Year: 2006
    Citations: 521

  • Title: Effect of flow perfusion on the osteogenic differentiation of bone marrow stromal cells cultured on starch‐based three‐dimensional scaffolds
    Authors: ME Gomes, VI Sikavitsas, E Behravesh, RL Reis, AG Mikos
    Year: 2003
    Citations: 468

  • Title: Effect of bone extracellular matrix synthesized in vitro on the osteoblastic differentiation of marrow stromal cells
    Authors: N Datta, HL Holtorf, VI Sikavitsas, JA Jansen, AG Mikos
    Year: 2005
    Citations: 388

  • Title: Flow perfusion enhances the calcified matrix deposition of marrow stromal cells in biodegradable nonwoven fiber mesh scaffolds
    Authors: VI Sikavitsas, GN Bancroft, JJ Lemoine, MAK Liebschner, M Dauner, et al.
    Year: 2005
    Citations: 247

  • Title: Flow perfusion culture of marrow stromal osteoblasts in titanium fiber mesh
    Authors: J van den Dolder, GN Bancroft, VI Sikavitsas, PHM Spauwen, JA Jansen, et al.
    Year: 2003
    Citations: 205

  • Title: Pre‐culture period of mesenchymal stem cells in osteogenic media influences their in vivo bone forming potential
    Authors: H Castano‐Izquierdo, J Álvarez‐Barreto, J Dolder, JA Jansen, AG Mikos, et al.
    Year: 2007
    Citations: 203

  • Title: Tuning the biomimetic behavior of scaffolds for regenerative medicine through surface modifications
    Authors: NR Richbourg, NA Peppas, VI Sikavitsas
    Year: 2019
    Citations: 196

  • Title: Flow perfusion improves seeding of tissue engineering scaffolds with different architectures
    Authors: JF Alvarez-Barreto, SM Linehan, RL Shambaugh, VI Sikavitsas
    Year: 2007
    Citations: 171

  • Title: Polypyrrole thin films formed by admicellar polymerization support the osteogenic differentiation of mesenchymal stem cells
    Authors: H Castano, EA O’Rear, PS McFetridge, VI Sikavitsas
    Year: 2004
    Citations: 158

  • Title: Influence of the in vitro culture period on the in vivo performance of cell/titanium bone tissue‐engineered constructs using a rat cranial critical size defect model
    Authors: VI Sikavitsas, J Dolder, GN Bancroft, JA Jansen, AG Mikos
    Year: 2003
    Citations: 150

Oladele Afolalu | Engineering | Best Researcher Award

Dr. Oladele Afolalu | Engineering | Best Researcher Award

Postdoctoral Fellow at Durban University of Technology, South Africa

Dr. Oladele Felix Afolalu is a distinguished researcher and academic in the field of Electrical and Telecommunications Engineering. Born on August 29, 1976, in Nigeria, he has made significant contributions to the advancement of ICT, telecommunications, and enterprise networking. With a strong passion for innovation, he has worked extensively in academia, research, and industry collaborations to improve modern communication systems. Currently a Postdoctoral Fellow at the Durban University of Technology, South Africa, Dr. Afolalu has played a crucial role in developing cutting-edge solutions in 5G networks, interference coordination, and network optimization. His leadership in academic institutions, numerous publications, and participation in international conferences reflect his dedication to research excellence. As a member of several prestigious engineering societies, including IEEE (USA & South Africa), COREN, and MNSE, he continues to impact the engineering community through mentorship, teaching, and groundbreaking studies in the field of telecommunications and ICT.

Professional Profile

Education

Dr. Afolalu’s academic journey is marked by a strong foundation in electrical and electronic engineering, with degrees from top institutions in Nigeria and South Africa. He earned his Ph.D. in Electrical and Telecommunication Engineering from the University of Cape Town, South Africa, where he specialized in 5G network optimization and inter-cell interference coordination. Prior to that, he completed an M.Sc. in Electronic/Electrical Engineering from Obafemi Awolowo University, Nigeria, where his research focused on communication systems and signal processing. His undergraduate studies culminated in a B.Eng. (Hons.) in Electrical/Electronics Engineering from the Federal University of Technology, Akure. Additionally, he holds a National Diploma in Electrical/Electronics Engineering from Federal Polytechnic, Ado-Ekiti. His diverse academic background has provided him with expertise in ICT systems, telecommunications, and engineering education, equipping him to contribute significantly to cutting-edge research and technology advancements.

Professional Experience

Dr. Afolalu has amassed over two decades of experience in teaching, research, and academic administration. He served as Head of the Department and Principal Lecturer at Federal Polytechnic, Ede, Nigeria, where he played a key role in curriculum development, student mentorship, and research supervision. He also worked as an Adjunct Senior Lecturer and Acting Head of Department at Joseph Ayo Babalola University, where he was instrumental in advancing research initiatives in physics electronics. His postdoctoral research at Durban University of Technology, South Africa, involves cutting-edge projects in enterprise networking and ICT systems. Additionally, he has served as a tutor at the University of Cape Town, helping students enhance their understanding of telecommunication systems. Throughout his career, he has been actively involved in examination committees, research committees, and industrial training programs, contributing significantly to the development of engineering education in Nigeria and beyond.

Research Interests

Dr. Afolalu’s research is centered on wireless communication networks, telecommunications engineering, and ICT innovations. His primary focus is on 5G and beyond technologies, network optimization, and inter-cell interference coordination. His Ph.D. research on Ultra-Dense Networks (UDNs) has contributed to improving network efficiency and power allocation in next-generation communication systems. He has also explored the application of artificial intelligence in network performance enhancement, particularly in resource allocation and signal processing. Additionally, his research extends to renewable energy integration in communication networks, aiming for sustainable and efficient power management in ICT infrastructure. His contributions to machine learning applications in network traffic optimization and security have been recognized in top-tier journals. Through his extensive research, he aims to bridge the gap between theoretical telecommunications advancements and practical industry implementations, ensuring that emerging technologies are efficiently deployed for societal benefit.

Awards and Honors

Dr. Afolalu has been recognized for his outstanding contributions to research, engineering education, and technological innovation. He has received accolades for his work on 5G networks, including best paper awards at international conferences such as the Southern Africa Telecommunication Networks and Applications Conference (SATNAC). His research on carrier aggregation-enabled NOMA techniques for enhanced 5G network performance has gained global recognition. He has also been honored for his mentorship and academic leadership, particularly in the development of engineering curricula and innovative teaching methodologies. His membership in prestigious engineering societies such as IEEE, COREN, and MNSE further highlights his excellence in the field. Additionally, he has participated as a panelist and keynote speaker at workshops and conferences, where his expertise in wireless communication and ICT infrastructure has been widely acknowledged. His commitment to research and education continues to inspire future engineers and researchers globally.

Conclusion

Dr. Oladele Felix Afolalu has a strong research portfolio, significant academic experience, and notable contributions to ICT and 5G telecommunications. His leadership roles, professional memberships, and conference engagements make him a worthy candidate for the Best Researcher Award. Strengthening high-impact publications, industry collaborations, and international research engagements will further solidify his standing in the global research community.

Publications Top Notes

  1. Carrier Aggregation‐Enabled Non‐Orthogonal Multiple Access Approach Towards Enhanced Network Performance in 5G Ultra‐Dense Networks

    • Author(s): O Afolalu, N Ventura

    • Year: 2021

    • Citations: 10

  2. A Survey of Interference Challenges and Mitigation Techniques in 5G Heterogeneous Cellular Networks

    • Author(s): OF Afolalu, JO Petinrin, MA Ayoade

    • Year: 2016

    • Citations: 4

  3. Internet of Things and Software Applications in Patient Safety Adverse Event Detection and Reporting: A Comprehensive Literature Review

    • Author(s): OO Afolalu, SA Afolalu, OF Afolalu, OA Akpor

    • Year: 2024

    • Citations: 2

  4. Inter-Cell Interference Coordination in 5G Ultra-Dense Networks

    • Author(s): OF Afolalu

    • Year: 2021

    • Citations: 2

  5. Internet of Things Applications in Health Systems’ Equipment: Challenges and Trends in the Fourth Industrial Revolution

    • Author(s): OO Afolalu, OA Akpor, SA Afolalu, OF Afolalu

    • Year: 2024

    • Citations: 1

  6. Application of Particle Swarm Optimization Method to Economic Dispatch of Nigerian Power System Considering Valve-Point Loading Effect

    • Author(s): GA Adepoju, MA Tijani, MO Okelola, MA Ayoade, OF Afolalu

    • Year: 2021

    • Citations: 1

  7. Enterprise Networking Optimization: A Review of Challenges, Solutions, and Technological Interventions

    • Author(s): O Afolalu, MS Tsoeu

    • Year: 2025

    • Citations: Not available yet

  8. A Novel Security Solution for Efficient Connectivity in Software-Defined Wide Area Network (SD-WAN)

    • Author(s): O Afolalu, MS Tsoeu

    • Year: 2025

    • Citations: Not available yet

  9. Sickle Cell Disease Epidemiology and Management in Africa: Current Trends and Future Directions in Digital Health Technologies

    • Author(s): AO Olajumoke, O Akpor, AS Afolalu, OF Afolalu, HB Oyewole, AO Oke

    • Year: 2024

    • Citations: Not available yet

  10. Analysis of Spectrum Occupancy of Active FM Band within Federal Polytechnic Ede Northern Campus

  • Author(s): AK Adebayo, JO Agbolade, IA Bamikefa, OF Afolalu, MA Ayoade

  • Year: 2021

  • Citations: Not available

  1. Development of Induction Motor Monitoring System with Protection Against Abnormal Voltage, Current, and Temperature

  • Author(s): MA Ayoade, IA Bamikefa, MA Tijani, OF Afolalu, AK Adebayo

  • Year: 2018

  • Citations: Not available

  1. Effects of Angles of Inclinations on the Performances of Photovoltaic (PV) Arrays

  • Author(s): MA Ayoade, OF Afolalu, IA Bamikefa, MA Tijani, MA Sanusi

  • Year: 2017

  • Citations: Not available

  1. Development of a Wireless Induction Motor Unbalanced Voltage Detection and Control System for Hazardous Environments

  • Author(s): MA Ayoade, OF Afolalu, IA Bamikefa, AK Adebayo, MA Sanusi

  • Year: 2017

  • Citations: Not available

 

Charly Julien Nyobe | Civil Engineering | Best Paper Award

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:

Scopus

ORCID

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

Peng Gu | Engineering | Best Researcher Award

Assoc. Prof. Dr. Peng Gu | Engineering | Best Researcher Award

associate professor at donghua university, China

Dr. Gu Peng is an accomplished researcher specializing in ultra-precision manufacturing and intelligent processing equipment. He is currently an Associate Professor at Donghua University, following his postdoctoral research at Shanghai Jiao Tong University under the mentorship of esteemed scholars. His work focuses on advanced machining technologies, contributing to national and international research projects. With multiple high-impact publications, patents, and awards, Dr. Gu has established himself as a leading expert in precision engineering. His contributions extend beyond academia through industry collaborations, making significant advancements in manufacturing automation. He actively serves as a reviewer for top SCI journals and is recognized as an expert in China’s leading technology committees. His academic excellence, combined with his research leadership and industrial impact, positions him as a key figure in the field of intelligent manufacturing and ultra-precision machining.

Professional Profile

Education

Dr. Gu Peng obtained his Bachelor’s degree in Mechanical Design, Manufacturing, and Automation from Hefei University of Technology in 2016, graduating ranked first in his class. He pursued a Master’s-Doctoral continuous program in Mechanical Engineering at Tongji University, where he demonstrated outstanding research potential and academic excellence. During his doctoral studies, he participated in an international training program at Politecnico di Torino, Italy, expanding his expertise in advanced manufacturing technologies. His dedication to research earned him multiple national scholarships and institutional awards, including the Outstanding Doctoral Student Award at Tongji University. His education laid a solid foundation for his expertise in precision engineering, manufacturing automation, and optical surface processing.

Professional Experience

Dr. Gu Peng began his professional career as a Postdoctoral Researcher at Shanghai Jiao Tong University (2022-2024), where he worked on ultra-precision machining under the guidance of renowned scholars. In 2024, he joined Donghua University as an Associate Professor, leading projects on intelligent manufacturing technologies. He has played a critical role in multiple national research projects, including the National Natural Science Foundation of China (NSFC) Youth Fund and key industrial research initiatives. In addition to his academic roles, he has been an expert consultant for major industrial projects, contributing to the development of advanced machining equipment for aerospace, optics, and semiconductor industries. His professional experience bridges cutting-edge research and practical industrial applications, ensuring his work has both theoretical and real-world impact.

Research Interests

Dr. Gu Peng’s research focuses on ultra-precision machining, intelligent manufacturing, and automation technologies. He specializes in high-precision grinding and polishing techniques for complex optical surfaces, including microstructure arrays and freeform surfaces. His work also explores the integration of intelligent control systems and AI-driven manufacturing processes, improving efficiency and accuracy in high-performance manufacturing industries. As the Principal Investigator of multiple national research projects, he is pioneering new methodologies for ultra-precision machining, particularly in single-point oblique axis grinding and laser-assisted cutting. His research has direct applications in aerospace, semiconductor manufacturing, and high-precision optics, making significant contributions to the field.

Awards and Honors

Dr. Gu Peng has received numerous national and institutional awards for his academic excellence and research contributions. He was a recipient of the Shanghai Super Postdoctoral Fellowship, the National Scholarship for Undergraduate and Doctoral Students, and multiple Outstanding Graduate Awards from Tongji University. He has also been recognized in national technology competitions, securing top prizes in innovation and mathematical modeling contests. In addition to his academic accolades, he serves as a reviewer for leading SCI journals, including the Journal of Manufacturing Technology and Applied Surface Technology. His contributions to ultra-precision machining and automation technology have established him as a highly respected figure in both academic and industrial research communities.

Conclusion

Dr. Gu Peng is highly suitable for the Best Researcher Award, given his strong publication record, leadership in high-level research projects, and national recognition. With continued efforts in international collaborations, student mentorship, and diversification of research, he could further solidify his standing as a leading researcher in the field of ultra-precision manufacturing.

Publications Top Noted

  • Author: Gu, P., Zhu, C., Sun, Y., Wang, D., & Shi, Z.

    • Year: 2025
    • Title: Evaluation and Prediction of Wrapping Deformation in Sheet Part Grinding
    • Journal: Experimental Techniques
    • Citations: 0
  • Author: Sun, C., Gu, P., Wan, H., Lin, J., & Min, J.

    • Year: 2025
    • Title: Enhancements of Physical Microstructure and Chemical Activation on Interfacial Bonding Strength of Carbon Fiber Reinforced Polymer
    • Journal: Composites Part A: Applied Science and Manufacturing
    • Citations: 0

 

Kaili Wang | Engineering | Best Researcher Award

Ms. Kaili Wang | Engineering | Best Researcher Award

Student at NB U, China

MS Kaili Wang is a distinguished researcher in the field of gene editing and molecular diagnostics, specializing in nucleic acid detection for agricultural biotechnology. She is affiliated with Ningbo University, School of Food Science and Engineering, China, and collaborates with Zhejiang Academy of Agricultural Sciences and the State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products. With a keen interest in genetic modification detection, her research focuses on improving the precision and sensitivity of detection methods for gene-edited organisms. Her recent work on droplet digital PCR (ddPCR) for MSTN gene-edited cattle has contributed significantly to the field of regulatory science and food safety. Dedicated to advancing biotechnology applications, she plays a crucial role in shaping methodologies for genetic monitoring, ensuring consumer safety, and fostering global discussions on gene editing and its implications.

Professional Profile

Education

MS Kaili Wang pursued her higher education in biotechnology, molecular biology, and food science, which provided a strong foundation for her research career. She earned her degrees from prestigious Chinese institutions, including Ningbo University, where she specialized in food science and genetic detection methods. Her academic training emphasized molecular diagnostics, genetic engineering, and PCR-based technologies, equipping her with the expertise necessary to develop innovative detection methods for genetically modified organisms (GMOs). Throughout her education, she engaged in interdisciplinary research, gaining hands-on experience in genetic modification analysis, nucleic acid quantification, and regulatory science. Her studies were complemented by rigorous laboratory work and collaborations with leading scientists in the field. This educational background has enabled her to contribute significantly to the advancement of gene-editing detection technologies, ensuring accuracy, sensitivity, and reliability in molecular diagnostics.

Professional Experience

With extensive experience in genetic research and molecular diagnostics, MS Kaili Wang has worked as a researcher at Ningbo University and in collaboration with Zhejiang Academy of Agricultural Sciences. She has been instrumental in developing innovative nucleic acid detection methods for gene-edited organisms, particularly using droplet digital PCR (ddPCR). Her work focuses on the safety assessment, traceability, and detection of genetically modified products, making a significant impact in the field of food safety and agricultural biotechnology. She has contributed to multiple high-impact research projects, collaborating with government agencies, regulatory bodies, and scientific institutions to establish robust methodologies for genetic monitoring. Her professional expertise extends to training young researchers, publishing peer-reviewed articles, and presenting her findings at international conferences related to gene editing and food safety. Her work plays a critical role in ensuring the accurate detection and regulation of gene-edited agricultural products.

Research Interests

MS Kaili Wang’s primary research interests lie in gene editing, nucleic acid detection, food safety, and molecular diagnostics. She is particularly focused on developing and optimizing PCR-based techniques, including ddPCR, qPCR, and CRISPR-based detection methods. Her research aims to enhance the specificity, sensitivity, and reliability of gene-editing detection, ensuring consumer safety and regulatory compliance. She is also deeply interested in the traceability of genetically modified organisms (GMOs) and their impact on food production, security, and public health. Through her work, she seeks to bridge the gap between scientific advancements and regulatory frameworks, contributing to the development of robust detection technologies that can be applied on a global scale. By integrating biotechnology with food safety regulations, she aims to provide innovative solutions for ensuring transparency in agricultural biotechnology and fostering public trust in gene-edited products.

Awards and Honors

Throughout her career, MS Kaili Wang has received numerous recognitions for her contributions to gene editing detection and food safety research. She has been honored with awards from academic institutions, regulatory bodies, and biotechnology organizations for her innovative work in nucleic acid quantification and molecular diagnostics. Her research on ddPCR-based detection of MSTN gene-edited cattle has gained international recognition, positioning her as a leading scientist in genetic monitoring and food safety regulation. She has been invited as a keynote speaker at scientific conferences, sharing her expertise on gene editing detection methodologies. Additionally, she has received grants and funding from government agencies to further her research in gene-editing detection and its application in regulatory science. Her dedication and contributions to biotechnology and food safety continue to make a profound impact, earning her a reputation as a pioneering researcher in the field.

Conclusion

MS Kaili Wang’s research is highly innovative and impactful, making significant contributions to gene editing detection and food safety monitoring. The work demonstrates scientific excellence, regulatory relevance, and technical robustness, making them a strong candidate for the Best Researcher Award. However, further research could focus on expanding the scope of detection beyond MSTN, increasing sample size, and facilitating regulatory adoption to enhance the real-world impact.

Publications Top Noted

Author: Kaili Wang, Yi Ji, Cheng Peng, Xiaofu Wang, Lei Yang, Hangzhen Lan, Junfeng Xu, Xiaoyun Chen
Year: 2025
Citation: Wang, K.; Ji, Y.; Peng, C.; Wang, X.; Yang, L.; Lan, H.; Xu, J.; Chen, X. (2025). “A Novel Quantification Method for Gene-Edited Animal Detection Based on ddPCR.” Biology, 14(2), Article 0203. DOI: 10.3390/biology14020203.
Source: Multidisciplinary Digital Publishing Institute (MDPI)