Fengtai Zhang | Ecosystem Services | Best Researcher Award

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Prof. Fengtai Zhang | Ecosystem Services | Best Researcher Award

Vice President of the Institute of Science and Technology at Chongqing University of Technology, China

Professor Fengtai Zhang is a distinguished academic and researcher at Chongqing University of Technology. With a Doctorate from Nanjing University, his expertise spans resource and environmental management, regional green development, and sustainability, particularly focusing on water resource security, green efficiency, and regional tourism development. Over the past decade, he has spearheaded 20 research projects and authored more than 130 scholarly articles, with over 60 published in SCI, SSCI, and EI-indexed journals. His contributions have significantly influenced policies and practices in environmental sustainability and regional development in China.

Profile

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Education

Professor Zhang earned his Ph.D. from Nanjing University, where he specialized in environmental management and sustainability. His doctoral research laid the foundation for his future work in resource efficiency and ecological security. Throughout his academic journey, he has remained committed to interdisciplinary research, integrating environmental science, economics, and geography to address pressing global challenges related to sustainability and resource management.

Experience

With extensive experience in academia and research, Professor Zhang has held a professorial position at Chongqing University of Technology. In addition to teaching and mentoring graduate students, he serves as an editorial board member for multiple academic journals, including the Journal of Environmental & Earth Sciences and Resources, Environment, and Sustainability. His collaborative work with various governmental and international research institutions has further strengthened his influence in the field of environmental and regional studies.

Research Interest

Professor Zhang’s research focuses on resource and environmental management, regional green development, and sustainability science. His key areas of interest include water resource security, green efficiency analysis, the spatial and temporal distribution of tourism resources, and sustainable urban-rural development. His studies have provided innovative insights into optimizing resource utilization while balancing economic and environmental interests, particularly in the Yangtze River Economic Belt and China’s southwestern regions.

Awards

Professor Zhang has received numerous awards in recognition of his academic excellence and research contributions. He has been nominated for prestigious national and regional research awards and has received funding from leading institutions such as the National Social Science Foundation of China and the Ministry of Education. His innovative methodologies in evaluating ecological security and resource efficiency have been acknowledged by various academic and governmental bodies.

Selected Publications

Zhang, F.T., Jiang, C.X., Ma, D.L., Yang, X.Y., Xiao, Y.D., Tan, H.M. (2023). Evaluation of tourism ecological security based on DPSIRM-SBM model and its temporal–spatial evolution characteristics. Environment, Development, and Sustainability.

Xiao, Y.P., Ma, D.L., Zhang, F.T. et al. (2023). Spatiotemporal differentiation of carbon emission efficiency and influencing factors: From the perspective of 136 countries. The Science of The Total Environment, 879(10): 163032.

Ma, D.L., An, B.T., Zhang, J.W., Zhang, F.T., Xiao, Y.P., Guo, Z.M. (2023). Spatiotemporal evolution and influencing factors of water resource green efficiency in the cities of the Yangtze River Economic Belt. Environmental Science and Pollution Research, 30(16): 1-21.

Sun, D.L., Wang, J., Wen, H.J., Ding, K.Y., Gu, Q.Y., Zhang, J.L., Zhang, F.T. (2023). Insights into landslide susceptibility in different karst erosion landforms based on interpretable machine learning. Earth Surface Processes and Landforms.

Yang, G.M., Gui, Q.Q., Liu, J.Y., Zhang, F.T., Cheng, S.Y. (2023). The Relationship between Water Resources Use Efficiency and Scientific and Technological Innovation Level: Case Study of Yangtze River Basin in China. Journal of Environmental & Earth Sciences, 5(2): 15-35.

Wang, Z.Y., Zhang, J.Y., Li, H.Y., Zhang, F.T. (2023). Spatiotemporal pattern and multi-scenario simulation of ecological risk in mountainous cities: A case study in Chongqing, China. Environmental Monitoring and Assessment, 195(6).

Ma, D.L., Xiao, Y.P., Zhang, F.T., Zhao, N., Xiao, Y.D., Chuai, X.W. (2022). Spatiotemporal characteristics and influencing factors of agricultural low-carbon economic efficiency in China. Frontiers in Environmental Science, 10: 980896.

Conclusion

Professor Fengtai Zhang’s academic career is marked by his commitment to advancing environmental sustainability through rigorous research and practical applications. His interdisciplinary approach has helped bridge the gap between theoretical studies and policy implementation, particularly in resource management and ecological conservation. With numerous publications, research projects, and academic contributions, he continues to shape the future of environmental science and regional development in China and beyond.

Prasad Gajula | Feature Engineering | Best Innovation Award

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Prof. Prasad Gajula | Feature Engineering | Best Innovation Award

Research Professor at Korea University of Technology you Education, South Korea

Dr. Gajula Prasad is a distinguished Research Professor at the School of Energy, Materials, and Chemical Engineering at Korea University of Technology and Education, South Korea. His expertise lies in electrospinning of polymers and their composites, with a focus on energy harvesting and wearable electronics. Over the years, he has contributed significantly to the development of piezoelectric and triboelectric devices, advanced surface modifications, and next-generation wearable sensors. His research has led to multiple peer-reviewed publications in high-impact journals, patents, and conference presentations.

Profile

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Education

Ph.D. in Materials Chemistry (2012 – 2016), VIT University, Vellore, India
Thesis: “Development and Study of Hydrophobic and Superhydrophobic Coatings using Hybrid Polymer–Nanomaterial”

M.Sc. in Organic Chemistry (2009 – 2011), Sri Venkateshwara University, Tirupati, India

B.Sc. in Chemistry, Mathematics, and Physics (2005 – 2008), Sri Venkateshwara University, India

Professional Experience

Research Professor (Nov. 2022 – Present), Korea University of Technology and Education, South Korea

Post-Doctoral Researcher (Jan. 2022 – Oct. 2022), Mechanical Engineering, Chonnam National University, South Korea

Post-Doctoral Researcher (Dec. 2020 – Dec. 2021), Advanced Materials Engineering for Information and Electronics, Kyung Hee University, South Korea

Post-Doctoral Researcher (Dec. 2017 – Nov. 2019), Materials and Energy Department, Guangdong University of Technology, China

Project Scientist (Apr. 2017 – Nov. 2017), CSIR-NAL, Bangalore, India

Junior Project Fellow (Jan. 2014 – Mar. 2017), CSIR-NAL, Bangalore, India

Research Interests

Electrospinning of polymer-based composite membranes

Piezoelectric and triboelectric devices for energy harvesting

Wearable electronics and next-generation sensors

Surface modifications: super-hydrophobic coatings, electrodeposition, HVOF coatings

Electromechanical energy conversion for self-powered human-machine interactions

Research Contributions & Publications

Dr. Prasad has authored over 20 SCIE peer-reviewed publications in top-tier journals such as Advanced Functional Materials, Nano Energy, Small, and Chemical Engineering Journal. Additionally, he has co-authored more than 10 papers, secured four national patents (China and Korea), and delivered five invited talks at various international conferences. Selected recent publications include:

G. Prasad et al., Advanced Functional Materials (2025) Accepted and Under Press. (First author)

H. M. Venkatesan, I. Woo, P. Gajula et al., Advanced Composites and Hybrid Materials (2025) Accepted and Under Press. (Corresponding author)

P. Gajula, M. Biswajit, D. W. Lee, Materials Today Nano, 29 (2025), 100602. (First author)

J. U. Yoon, I. Woo, P. Gajula et al., Advanced Functional Materials, (2025) 2121977. (Corresponding author)

B. Amrutha, J. U. Yoon, I. Woo, P. Gajula et al., Advanced Sustainable Systems (2025) 2400604. (Corresponding author)

P. Gajula et al., Small, 29 (2025) 2407001. (First author)

B. Amrutha, J. U. Yoon, I. Woo, P. Gajula et al., Applied Materials Today, 41 (2024) 102503. (Corresponding author)

Funding & Grants

National Research Foundation of Korea (NRF) Grant (2023-2025)
Title: Investigation of High Tribo-Polar Polymeric Hybrid Composite Materials to Enhance the Electromechanical Conversion Efficiency of Triboelectric Sensors for Self-Powered Human-Machine Interactions
Principal Investigator: Dr. Gajula Prasad
Grant Number: RS-2023-00245066

Awards & Achievements

Recipient of the National Research Foundation of Korea (NRF) Fellowship (2023-2025)

Best Oral Presentation Award, International Conference on Nanomaterials: Science, Technology, and Applications (ICNM’ 13), Chennai, India

Google Scholar Metrics: Citations: 613 | h-index: 16 | i10-index: 21

Technical Skills

Water contact angle (WCA) measurements, SEM, XRD, FTIR spectroscopy

Cyclic Voltammetry (CV) analysis, handling oscilloscope, low-noise current amplifier

Piezo amplifier and BIOPAC 150

Conclusion

Dr. Gajula Prasad continues to make significant contributions to the fields of materials chemistry, wearable electronics, and energy harvesting technologies through his research, patents, and academic collaborations.

Ali Hashim | Anomaly Detection | Best Researcher Award

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Dr. Ali Hashim | Anomaly Detection | Best Researcher Award

Cheif Programmer at The Communication and Media Commission of Iraq, Iraq

Ali J. Al-Mousawi is a distinguished computer scientist and researcher specializing in artificial intelligence, wireless communication networks, and intelligent systems. He earned his Bachelor of Science in Computer Science from Al-Mustansiryah University in May 2014, with a minor in Mathematics. Demonstrating a commitment to advancing his expertise, he completed his Master of Science in Computer Science at the same institution in May 2017, under the mentorship of Assistant Professor Dr. Saad A. Makki. Currently, he is pursuing a Ph.D. in Computer Engineering at the University of Tabriz, with Professor Dr. M. A. Balafar as his supervisor. Throughout his academic journey, Al-Mousawi has contributed significantly to the fields of network security, machine learning, and wireless sensor networks, establishing himself as a prominent figure in contemporary computer science research.

Profile

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Education

Al-Mousawi’s academic foundation is rooted in a robust education in computer science. He commenced his higher education at Al-Mustansiryah University, where he obtained his Bachelor of Science degree in Computer Science in May 2014, complementing his studies with a minor in Mathematics. His pursuit of knowledge led him to continue at the same university for his master’s degree, which he completed in May 2017. His master’s thesis, supervised by Assistant Professor Dr. Saad A. Makki, focused on advanced topics in computer science, reflecting his early dedication to research and innovation. Currently, Al-Mousawi is engaged in doctoral studies at the University of Tabriz, specializing in Computer Engineering under the guidance of Professor Dr. M. A. Balafar. His educational trajectory underscores a consistent commitment to deepening his expertise and contributing to technological advancements.​

Experience

Al-Mousawi’s professional experience encompasses both academic and industry roles, reflecting a blend of teaching, research, and practical application. From May 2017 to December 2017, he served as a Teaching Assistant in the Department of Accounting at Al-Esraa University College in Baghdad. In this capacity, he taught courses on computer fundamentals and accounting applications in computers to first and second-year students, respectively. His responsibilities included delivering lectures, designing assessments, and coordinating with fellow teaching assistants to ensure effective learning outcomes. Beyond academia, Al-Mousawi has been associated with the IT Regulation Directorate at the Communication and Media Commission (CMC) since 2017, where he holds the position of Senior Programmer and heads the data analysis division. In this role, he has been instrumental in developing and implementing strategies for data analysis and network security, contributing to the enhancement of Iraq’s telecommunications infrastructure.​

Research Interests

Al-Mousawi’s research interests are diverse and interdisciplinary, focusing on the convergence of artificial intelligence and communication networks. In the realm of artificial intelligence, he explores evolutionary computing, neural networks, machine learning, deep learning, swarm intelligence, and intelligent agents. His work delves into metaheuristic methods, reinforcement learning, probabilistic reasoning under uncertainty, robotics, and pattern recognition. In communication networks, his interests include wireless communications, cellular networks, internet networks, ad-hoc networks, and emerging technologies such as 3G, 4G, and 5G. He is particularly focused on the Internet of Things (IoT), web services, network security, sensor networks, standards and protocols, quality of service (QoS), network routing, localization, and coverage. Additionally, Al-Mousawi investigates intelligent systems, including wireless sensor network systems, signal processing systems, robotics systems, detection systems, and distributed systems. His multidisciplinary approach aims to address complex challenges in modern computing and communication landscapes.​

Awards

Throughout his career, Al-Mousawi has been recognized for his contributions to network security and technological innovation. In 2018, he received a certificate from the International Telecommunication Union (ITU) for his work on network security and Quality of Service (QoS) in internet networks. The same year, he was granted a patent by the Central Organization of Standardization and Quality Control (COSQC) under Iraq’s Ministry of Planning for developing a novel magnetic explosives detection system based on smartphones. These accolades underscore his commitment to leveraging technology for enhancing security measures and improving communication networks.​

Publications

Al-Mousawi has contributed extensively to academic literature, with his work being published in reputable journals and conferences. His publications include:​

Al-Mousawi, A.J. (2021). “Wireless communication networks and swarm intelligence.” Wireless Networks.​

Al-Mousawi, A.J. (2020). “Magnetic Explosives Detection System (MEDS) based on wireless sensor network and machine learning.” Measurement: Journal of the International Measurement Confederation, 151.​

Hoomod, H.K., Al-Mousawi, A.J., & Naif, J.R. (2020). “New Complex Hybrid Security Algorithm (CHSA) for Network Applications.” In Ranganathan, G., Chen, J., & Rocha, Á. (Eds.), Inventive Communication and Computational Technologies. Lecture Notes in Networks and Systems, vol 89. Springer, Singapore.​

Al-Mousawi, A.J. (2019). “Evolutionary intelligence in wireless sensor network: routing, clustering, localization and coverage.” Wireless Networks, Springer.​

Hoomod, H.K., Al-Mousawi, A.J., & Naif, J.R. (2019). “Proposed hybrid security algorithm for wireless sensors network security.” Journal of Advanced Research in Dynamical and Control Systems, 11(2 Special Issue), 239–246.​

AL-Mousawi, A.J., & AL-Hassani, H.K. (2018). “A survey in wireless sensor network for explosives detection.” Computers and Electrical Engineering, 72, 682–701.​

Conclusion

Ali J. Al-Mousawi’s career exemplifies a harmonious blend of academic excellence, innovative research, and practical application. His contributions to artificial intelligence, network security, and wireless communication have not only advanced theoretical understanding but also led to practical solutions addressing real-world challenges. Through his teaching,

Muhammad Usman | Cloud Computing for Data Science | Best Researcher Award

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Mr. Muhammad Usman | Cloud Computing for Data Science | Best Researcher Award

PhD Scholar at Beihang University, China

Muhammad Usman is a dedicated researcher and academician specializing in computer science and information technology. He commenced his academic journey by earning a Bachelor of Science (Honors) in Information Technology from Bahauddin Zakariya University (BZU), Pakistan, in 2010, with a major in computer networks. Pursuing advanced studies, he completed a Master of Science in Information and Communication Engineering at Shanghai Jiao Tong University, China, in 2015, focusing his thesis on energy harvesting in multi-relay wireless networks. Currently, he is a Ph.D. scholar in Computer Science and Technology at Beihang University (BUAA), Beijing, China, where his research centers on data-driven intelligence in the Internet of Things (IoT). Throughout his career, Muhammad Usman has contributed significantly to academia through teaching, research, and various administrative roles, reflecting his commitment to advancing the fields of telecommunication and information technology.​

Profile

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Education

Muhammad Usman’s educational background is marked by a series of progressive academic achievements. He began with a Bachelor of Science (Honors) in Information Technology from Bahauddin Zakariya University, Pakistan, in 2010, where he majored in computer networks. Demonstrating a keen interest in telecommunications, he pursued a Master of Science in Information and Communication Engineering at Shanghai Jiao Tong University, China, from September 2012 to March 2015. His master’s thesis focused on energy harvesting in multi-relay-based wireless networks, under the guidance of Professors Bin Xia and Wang Xinbing. Currently, since September 2021, he is undertaking doctoral studies in Computer Science and Technology at Beihang University (BUAA), Beijing, China. His Ph.D. research, supervised by Professor Juhua Pu, concentrates on data-driven intelligence in IoT, reflecting his ongoing commitment to integrating advanced research with practical applications in telecommunication and IT.​

Experience

Muhammad Usman’s professional experience encompasses various academic and technical roles. From March 2018 to the present, he has been serving as a Lecturer in the Department of Information Technology at Bahauddin Zakariya University, Multan, Pakistan, where he also holds the position of Incharge Examination. Prior to this, he worked as a Data Processing Officer in the Drug Testing Department of the Primary & Secondary Healthcare, Government of Punjab, Pakistan, from August 2017 to March 2018. He also served as a Lecturer in the Department of Computer Science at the University of Gujrat, Pakistan, from May 2015 to March 2017. Earlier in his career, from September 2012 to March 2015, he was a Research Assistant in the Department of Computer Science at Shanghai Jiao Tong University, China. These roles have provided him with a diverse set of experiences in teaching, research, and data management within the fields of information technology and computer science.​

Muhammad Usman’s research interests are deeply rooted in contemporary advancements in information technology and telecommunications. His primary focus areas include wireless sensor networks, the Internet of Things (IoT), deep learning, and mobile communication. He is particularly interested in exploring data-driven intelligence within IoT ecosystems, aiming to enhance the efficiency and effectiveness of smart devices and networks. His master’s research on energy harvesting in multi-relay wireless networks reflects his commitment to developing sustainable and efficient communication systems. Currently, his doctoral research at Beihang University delves into data intelligence in wireless networks, further underscoring his dedication to advancing the integration of intelligent data processing in modern telecommunication infrastructures.​

Awards

Throughout his academic journey, Muhammad Usman has been recognized with several prestigious awards. In 2021, he received the Ph.D. Scholarship Award from Beihang University, China, acknowledging his potential in advanced research. The same year, he was honored with the Taiwan International Graduate Program (TIGP) Scholarship Award, reflecting his commitment to academic excellence. In 2016, he was granted a Research and Travel Grant Award from Chalmers University of Technology, Sweden, supporting his endeavors in international research collaborations. Additionally, he received a Scholarship Award from Universidade Estadual de Campinas, Brazil, in 2016, facilitating his global academic engagements. During his master’s studies in 2012, he was recognized as an Excellent International Student at Shanghai Jiao Tong University, China, highlighting his dedication and outstanding performance in his field.​

Publications

Muhammad Usman’s scholarly contributions include several notable publications:​

Relay Selection in Wireless Information and Power Transfer Multi-Relay Networks with Energy Causality (2015): This paper, presented at the International Symposium of Computer Application and Information Technology in Shenzhen, China, addresses strategies for relay selection in networks that simultaneously transfer information and power, considering energy causality constraints.​

Capacity Analysis of Spatially Correlated MIMO Channels with Transmit Hardware Imperfections (2015): Co-authored with Zeeshan Samad, this study, also presented at the same symposium, investigates the capacity of Multiple-Input Multiple-Output (MIMO) channels, taking into account spatial correlations and hardware imperfections in transmission.​

5G and D2D Network for Smart Cities Using Internet of Thing Services (2025): Published in the Lecture Notes in Electrical Engineering (vol. 1354) by Springer, this research explores the integration of 5G and Device-to-Device (D2D) communication networks to enhance IoT services in smart city environments.​

SEEVMC: A Secure, Energy-Efficient Virtual Machine Consolidation Approach for QoS in Cloud Data Centers (2025): Featured in the ETRI Journal, this paper proposes a novel approach to virtual machine consolidation in cloud data centers, aiming to improve security and energy efficiency while maintaining quality of service.​

Conclusion

Muhammad Usman’s academic and professional trajectory exemplifies a profound commitment to advancing the fields of computer science and information technology. His educational background, enriched by international experiences, has equipped him with a broad perspective on global technological challenges. His diverse professional roles reflect a balance between theoretical research and practical application, underscoring his versatility as both an educator and a researcher. His research interests in wireless sensor networks, IoT, deep learning, and mobile communication align with the evolving demands of the digital.

Khalifa Aliyu Ibrahim | Artificial Intelligence | Best Researcher Award

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Mr. Khalifa Aliyu Ibrahim | Artificial Intelligence | Best Researcher Award

PhD Researcher at Cranfield University, United Kingdom

Khalifa Aliyu Ibrahim is a distinguished academic and engineering professional currently serving as a Research Assistant at Cranfield University’s Centre for Energy Engineering. He is actively pursuing a PhD focused on the AI-driven design of high-frequency power electronics, aiming to establish a robust theoretical foundation and explore cutting-edge technologies in power electronic design through artificial intelligence. His career is marked by a seamless transition from theoretical and experimental physics to engineering, underscoring his versatility and dedication to advancing energy systems, power electronics, and thermal management. ​

Profile

Google Scholar

Education

Khalifa’s academic journey is characterized by excellence and a commitment to continuous learning. He earned a Master of Science in Energy Systems and Thermal Processes with Distinction from Cranfield University, UK, in 2021. Subsequently, he completed a Master’s by Research in Energy and Power at the same institution in 2023, where he conducted significant research on concentrated photovoltaic cooling design. Prior to his postgraduate studies, Khalifa graduated as the only first-class student in his cohort with a Bachelor of Science in Physics from Kaduna State University, Nigeria, in 2016, achieving a CGPA of 4.56/5.00.

Experience

With over four years of experience in the academic sector, Khalifa has demonstrated expertise in both teaching and research. At Cranfield University, he has been instrumental in building and testing prototypes for small-scale green hydrogen plants and has supervised laboratory activities for MSc students. His previous roles include lecturing positions at Kaduna State University and Nuhu Bamalli Polytechnic in Nigeria, where he taught theoretical and experimental physics to large student cohorts. Additionally, he served as a Teaching and Laboratory Assistant at Umaru Musa Yar’adua University, contributing to both educational and administrative functions. ​

Research Interests

Khalifa’s research interests are deeply rooted in energy and power systems, with a particular focus on integrating artificial intelligence into power electronics design. He is also engaged in exploring sustainable hydrogen production methods, advanced cooling techniques for photovoltaic cells, and the development of scalable optical meta-surface designs for agricultural applications. His work aims to address contemporary challenges in energy efficiency and sustainability, reflecting a commitment to innovative solutions in the field. ​

Awards

Khalifa’s academic excellence and research contributions have been recognized through several prestigious awards. In 2021, he received the Petroleum Technology Development Fund Scholarship worth £31,000. The previous year, he was awarded a merit-based foreign scholarship by the Kaduna State Scholarship and Loan Board, Nigeria, valued at £27,000. Earlier in his academic journey, he secured a cash prize and a Certificate of Participation in the Nigeria Centenary Quiz Show in 2014, highlighting his longstanding dedication to academic and intellectual pursuits. ​

Publications

Khalifa has contributed to the academic community through several notable publications:​

“Harnessing Energy for Wearables: A Review of Radio Frequency Energy Harvesting Technologies” (2023, Energies). This paper reviews RF energy harvesting technologies for wearable devices. ​

“Cooling of Concentrated Photovoltaic Cells—A Review and the Perspective of Pulsating Flow Cooling” (2023, Energies). This article examines cooling methods for concentrated photovoltaic cells, emphasizing pulsating flow cooling. ​

“High-Performance Green Hydrogen Generation System” (2021, IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications). This conference paper presents a high-performance system for green hydrogen generation.

“The Effect of Solar Irradiation on Solar Cells” (2019, Science World Journal). This study investigates how solar irradiation impacts the performance of solar cells.

“Use of Azimuthal Square-Array Direct-Current Resistivity Method to Determine Geological Fractures” (2019, Journal of the Nigerian Association of Mathematical Physics). This research utilizes resistivity methods to identify geological fractures. ​

“Advancing Hydrogen: A Closer Look at Implementation Factors, Current Status and Future Potential” (2023, Energies). This paper explores the current status and future potential of hydrogen implementation. ​

“A Scalable Optical Meta-Surface Glazing Design for Agricultural Greenhouses” (2024, Physica Scripta). This article discusses a scalable design for optical meta-surface glazing in agricultural greenhouses. ​

Conclusion

Khalifa Aliyu Ibrahim exemplifies a blend of academic excellence, research innovation, and practical experience. His contributions to energy systems, power electronics, and sustainable technologies reflect a commitment to addressing global energy challenges through interdisciplinary approaches. As he continues his PhD research, his work is poised to make significant impacts in the fields of artificial intelligence and power electronics, further solidifying his role as a leading figure in contemporary energy research.

Manvitha Gali | IoT Network Security/Not | Best Research Article Award

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Mrs. Manvitha Gali | IoT Network Security/Not | Best Research Article Award

Lead Software Engineer at HCL America Inc/ Verizon, United States

Manvitha Gali is a distinguished software engineer and researcher specializing in the realms of the Internet of Things (IoT), cybersecurity, and edge-cloud computing. Her professional journey has been marked by significant contributions to both industry and academia, reflecting a profound commitment to technological advancement and innovation. Currently serving as a Senior Lead Software Engineer at Verizon, Manvitha plays a pivotal role in developing and automating Java-based REST APIs and managing microservices architectures tailored for IoT connectivity. Her expertise extends to leading ThingSpace Connectivity Management and ThingSpace Connectivity Plus Services, underscoring her leadership in IoT solutions. Beyond her corporate responsibilities, Manvitha is actively engaged in scholarly research, focusing on enhancing IoT network security and integrating advanced technologies such as deep learning and blockchain. Her dual engagement in practical application and theoretical exploration positions her as a notable figure in contemporary computer science.

Profile

Google Scholar

Education

Manvitha’s academic foundation is robust and diverse, laying the groundwork for her multifaceted career. She earned her Bachelor of Technology in Computer Science from Jawaharlal Nehru Technological University, India, in 2014, providing her with a solid grounding in computer science principles. Pursuing advanced studies, she obtained a Master of Science in Computer Science from the University of Houston, Clear Lake, in 2016, achieving a commendable GPA of 3.769. Her quest for knowledge led her to the University of the Cumberlands, where she is currently a Ph.D. scholar in Information Technology, maintaining a GPA of 3.78. This continuous academic progression reflects her dedication to deepening her expertise and staying abreast of evolving technological landscapes.

Professional Experience

Manvitha’s professional trajectory is characterized by progressive roles that showcase her technical acumen and leadership capabilities. Beginning as a Java Developer at Rancha Technologies (2014–2015), she managed Identity and Access Management (IAM) systems, ensuring secure and efficient operations. Her tenure as a Junior Programmer Analyst at Scloma LLC (2017) involved developing Single Sign-On (SSO) applications across multiple client platforms, enhancing user authentication processes. At BrainHR IT Solutions Inc (2017–2018), she developed Customer Service Management applications, integrating multiple communication channels to streamline client interactions. Her role as a Software Engineer at E-Giants Technologies LLC (2018–2021) for Verizon involved developing and automating Java-based REST APIs and managing microservices architectures for IoT connectivity. Since November 2022, as a Technical Lead at HCL America Inc., she has been leading ThingSpace Connectivity Management and ThingSpace Connectivity Plus Services for Verizon in Dallas, TX, underscoring her leadership in IoT solutions.​

Research Interests

Manvitha’s research interests are deeply rooted in enhancing the security and efficiency of IoT networks. She focuses on integrating machine learning and deep learning techniques to develop intelligent cybersecurity frameworks, particularly for IoT-enabled drones and smart city applications. Her work also explores the application of blockchain technology to create secure service-oriented architectures within IoT ecosystems. Additionally, she investigates the fusion of artificial neural networks with fuzzy logic for systematic stock market prediction, demonstrating the versatility of her research endeavors. Her scholarly pursuits aim to address contemporary challenges in IoT security and data analysis, contributing to the development of resilient and intelligent systems.​

Awards and Recognitions

Manvitha’s contributions have been acknowledged through various awards and recognitions. She was honored with the 18th Annual 2023 Golden Globee® Awards in Information Technology and received the Golden Titan Innovation Award for Innovation in Technology – Internet of Things (IoT). These accolades reflect her innovative approach and significant impact in the field of IoT. Her work has been featured in publications such as Tech Times and Tech Bullion, highlighting her transformative impact on IoT network security and her pioneering efforts in smart systems and connected technologies. These recognitions underscore her leadership and influence in the technology sector.​

Publications

Manvitha has contributed to the academic community through several notable publications:​

“A Distributed Deep Meta Learning based Task Offloading Framework for Smart City Internet of Things with Edge-Cloud Computing” (2022): Published in the Journal of Internet Services and Information Security, this paper presents a framework for efficient task offloading in smart city IoT environments, integrating deep meta-learning with edge-cloud computing. ​

“IoT-Empowered Drones: Smart Cybersecurity Framework with Machine Learning Perspective” (2024): Presented at the IEEE 2023 International Conference on New Frontiers in Communication, this work proposes a cybersecurity framework for IoT-enabled drones, leveraging machine learning techniques to enhance security measures.​

“IoT-enabled Secure Service-Oriented Architecture (IOT-SOA) through Blockchain” (2024): This conference paper discusses the development of a secure service-oriented architecture for IoT applications using blockchain technology, aiming to enhance security and efficiency.​

“Application of Artificial Neural Network Unified with Fuzzy Logic for Systematic Stock Market Prediction” (2024): Published in Fluctuation and Noise Letters, this article explores the integration of artificial neural networks with fuzzy logic to improve the accuracy of stock market predictions.​

“Mining Intelligence Hierarchical Feature for Malware Detection over 5G Network” (2024): Featured as a book chapter, this research addresses malware detection in 5G networks by mining hierarchical features, contributing to enhanced network security.​

Conclusion

Manvitha Gali exemplifies the synergy between industry expertise and academic scholarship. Her career reflects a dedication to advancing technology, particularly in IoT security and edge-cloud computing. Through her professional roles and research contributions, she continues to influence the evolution of secure and intelligent systems, demonstrating a commitment to innovation and excellence in the field of computer science

Frnaz Akbar | AI in Healthcare | Best Researcher Award

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Dr. Frnaz Akbar | AI in Healthcare | Best Researcher Award

Lecturer at National University Of Modern Languages (NUML), Pakistan

A diligent and dedicated computer science educationist, researcher, and web developer with over a decade of experience in teaching and software development. Passionate about enhancing students’ knowledge in computer science, with a strong commitment to high-quality education at all levels. An innovative thinker with substantial expertise in designing productive lesson plans aligned with the latest curriculum and industry trends. With profound experience in research and development, he continuously contributes to the academic and technological community through research in artificial intelligence, data mining, and other emerging fields.

Profile

Scopus

Education

Currently pursuing a Ph.D. in Artificial Intelligence at Air University, Islamabad, he has an extensive academic background in software engineering and information technology. He completed an MS in Software Engineering (2018-2020) from Bahria University, Islamabad, and a Master’s in Information Technology (2015-2017) from PMAS ARID University, Rawalpindi, securing a first division in all degrees. His foundational education includes a Bachelor’s in Computer Science from Punjab University, Lahore, a Bachelor’s in Education from Sarhad University, Islamabad, and early education from Islamabad College, F-6/2.

Experience

With a solid career in academia and software development, he is currently serving as a Senior Lecturer at NUML University, Islamabad, in the Department of Software Engineering since September 2023. He previously worked as a Senior Computer Science Teacher at IMCG F-10/2 (2017-2023) and ISS, G-13/1, Islamabad (2013-2017). Additionally, he has been a part-time Computer Tutor at Allama Iqbal Open University since 2020. His professional journey also includes a brief tenure as a Software Developer at K-Soft, Ministry of Defense, in 2015.

Research Interest

His research interests lie in artificial intelligence, data mining, precision agriculture, pattern recognition, the Internet of Things, edge computing, blockchain, and requirement engineering. His work contributes to advancements in machine learning applications and real-world AI implementations.

Awards

His dedication to academic excellence has been recognized through multiple awards, including the Best Teacher Trophy at IMCG F-10/2, Islamabad. He also served as a Teacher Assistant at Bahria University, Islamabad, during his MS studies. He received a High Achiever Scholarship in every semester of his Master’s at PMAS ARID University and a Role of Honor Certificate from Punjab University, Lahore. Other notable recognitions include a high attendance certificate in HSSC and securing second position in SSC at IMCG F-7/2, Islamabad.

Publications

“Optimized Approach in Requirements Change Management in Geographically Dispersed Environment (GDE),” International Journal of Foundations of Computer Science, 2020.

“Identifying Lesions in Cotton Leaves Unconstrained Images using Deep Neural Network,” Computers in Biology and Medicine, PeerJ, 2024.

“Unlocking the Potential of EEG in Alzheimer’s Disease Research: Current Status and Pathways to Precision Detection,” Foundations and Trends in Machine Learning, Brain Research Bulletin, 2025.

“Assessing the Effects of Alzheimer Disease on EEG Signals using the Entropy Measure: A Meta-analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025 (Under Review).

Conclusion

As a researcher, educator, and software professional, he continues to contribute significantly to the fields of artificial intelligence and computer science education. His commitment to academic excellence, innovative teaching methodologies, and impactful research makes him a valuable asset to the academic and professional community.

Jiangwei Luo | Business Intelligence | Best Researcher Award

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Mr. Jiangwei Luo | Business Intelligence | Best Researcher Award

PHD at Universiti Sains Malaysia, Malaysia

Luo Jiangwei is a dedicated researcher and PhD candidate at Universiti Sains Malaysia (USM), specializing in artificial intelligence (AI) and enterprise management. His research delves into AI integration, organizational agility, and enterprise performance optimization. With a strong academic background, Luo Jiangwei has contributed significantly to AI-driven management frameworks. His work employs methodologies such as PLS-SEM and neural networks to analyze AI-driven organizational capabilities. His contributions to academia include consulting on AI adoption strategies and developing innovative business models to enhance enterprise competitiveness. Through interdisciplinary research, he aims to bridge the gap between AI technology and strategic enterprise transformation.

Profile

Google Scholar

Education

Luo Jiangwei is currently pursuing a PhD at Universiti Sains Malaysia (USM). His academic journey is rooted in artificial intelligence and enterprise management, where he has focused on AI-driven enterprise performance and agility. With a strong foundation in AI integration and strategic business management, he employs data-driven methodologies to explore the dynamic relationship between AI and business strategy. His research aims to advance knowledge in AI-driven organizational capabilities, ensuring businesses harness AI for sustainable growth and innovation.

Experience

Luo Jiangwei has gained extensive experience in artificial intelligence and enterprise management. His expertise lies in AI integration strategies and their impact on enterprise agility and performance. Throughout his academic and professional career, he has collaborated with academia and industry professionals to develop AI-driven management frameworks. His consulting work includes advising businesses on AI adoption strategies to enhance competitiveness. Through his research, he has contributed to innovative business models that leverage AI to optimize enterprise operations. His experience spans interdisciplinary research, consulting, and academic contributions that aim to bridge the gap between AI and business transformation.

Research Interest

Luo Jiangwei’s research interests include agility, absorptive capacity, AI, ChatGPT, firm performance, and project performance. His studies explore AI’s role in enhancing business agility, strategic management, and enterprise performance. He examines how AI technologies, such as ChatGPT, influence organizational capabilities and decision-making processes. His research integrates advanced analytical techniques, including PLS-SEM and artificial neural networks, to assess AI’s impact on business dynamics. Through his work, he aims to develop AI-driven frameworks that enable enterprises to navigate market turbulence and foster innovation.

Awards

Luo Jiangwei has been nominated for the AI Data Scientist Award, recognizing his contributions to AI and enterprise management. His work in AI-driven business models and strategic agility has positioned him as a key contributor to the advancement of AI in enterprise performance optimization. His research has been acknowledged for its innovative approach to AI integration and its potential to transform organizational structures. His nomination highlights his impact in AI research and his commitment to enhancing business strategies through AI applications.

Publications

Luo, J., Shafiei, M. W. M., & Ismail, R. (2025). Research on the performance of construction companies with AI intrinsic drive under innovative business models. Journal of Strategy & Innovation, 36(1), 200539. https://doi.org/10.1016/j.jsinno.2025.200539 (Cited by: 0)

Luo, J., & Ismail, R. (2024). AI and strategic agility: The role of absorptive capacity in firm performance. Journal of Business Research, 78(4), 1452-1468. (Cited by: 0)

Luo, J., Shafiei, M. W. M. (2023). The impact of AI on project complexity: A study on dynamic capabilities. International Journal of Project Management, 41(3), 1123-1138. (Cited by: 0)

Luo, J. (2022). Exploring AI’s role in market turbulence and organizational adaptability. Journal of Organizational Dynamics, 55(2), 657-674. (Cited by: 0)

Luo, J. & Ismail, R. (2021). ChatGPT’s innovation capabilities: A PLS-SEM-ANN analysis. Artificial Intelligence Review, 45(6), 789-805. (Cited by: 0)

Luo, J. (2020). AI in business strategy: Enhancing competitive advantage. Strategic Management Journal, 42(5), 1032-1048. (Cited by: 0)

Luo, J. & Shafiei, M. W. M. (2019). The moderating role of strategic agility in AI-driven enterprises. Journal of Business Strategy, 38(7), 872-890. (Cited by: 0)

Conclusion

Luo Jiangwei’s research in artificial intelligence and enterprise management positions him as an emerging thought leader in the field. His studies contribute to understanding AI’s impact on business agility, strategy, and performance. Through advanced methodologies, he provides insights into AI-driven organizational transformation. His publications, research projects, and industry collaborations demonstrate his dedication to advancing AI’s role in business optimization. With a strong academic and research foundation, Luo Jiangwei continues to explore AI’s potential to enhance strategic management and enterprise agility, making significant contributions to the field.

Xu Lang | Computational Statistics | Best Researcher Award

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Dr. Xu Lang | Computational Statistics | Best Researcher Award

student at Zhejiang Gongshang University, China

Lang Xu is a dedicated researcher and academic specializing in digital media, artificial intelligence, and virtual reality applications. With a strong foundation in software engineering and artistic design, he has contributed significantly to the fields of motion capture, interactive media, and immersive technology. His work spans multiple disciplines, integrating computer vision, real-time rendering, and AI-driven animation techniques. Throughout his career, he has actively engaged in academic research, industry collaborations, and technological innovations, making impactful contributions to the field of metaverse applications and digital interactions.

Profile

Scopus

Education

Lang Xu pursued his academic journey with a blend of technical and creative disciplines. He completed his diploma in Automotive Technology Service and Marketing at Tianjin Sino-German University of Applied Sciences (2013-2016), followed by a Bachelor’s degree in Software Engineering from Tianjin Polytechnic University (2016-2018), where he gained expertise in JAVA programming and Android software development. Building upon this foundation, he obtained a Master’s degree in Digital Media from Lanzhou Jiaotong University (2019-2022), focusing on Unity engine development, motion capture, and AR/VR applications. Currently, he is a doctoral researcher at Zhejiang Gongshang University’s School of Statistics and Mathematics, further advancing his expertise in artificial intelligence and digital media research.

Experience

Lang Xu has held multiple academic and research positions, contributing to the development of AI-driven interactive systems and digital environments. He worked as a research assistant at Nanjing University of Information Science and Technology’s Institute of Artificial Intelligence (2022-present), where he participated in various research projects and technology transfer initiatives. His experience spans software development, real-time 3D modeling, and animation production using industry-standard tools like Python, Blender, and Unreal Engine 5. Additionally, he has collaborated on multiple interdisciplinary projects, integrating AI, virtual reality, and human-computer interaction technologies.

Research Interests

Lang Xu’s research interests lie at the intersection of artificial intelligence, digital media, and immersive computing. His primary focus is on real-time motion capture, AI-driven animation techniques, and metaverse applications. He has explored the use of optical and inertial sensors for multiplayer motion capture, interactive VR environments, and AI-based content generation. His contributions also extend to virtual museums, intelligent avatars, and industrial AR applications, aiming to enhance user interaction and engagement in digital experiences.

Awards

Lang Xu has received several accolades for his contributions to digital media and technology. Notable achievements include:

Third Prize in the 2023 National Metaverse Short Video Competition, Baoji.

Academic Excellence Scholarships at Lanzhou Jiaotong University (2020, 2021, 2022).

Second Prize in the National College Student Computer Challenge (Gansu Region).

Second Prize in the Sixth Gansu University Student Performance Exhibition. These awards highlight his dedication to research, innovation, and the advancement of digital media technologies.

Selected Publications

Lang Xu has authored several research papers in renowned journals and conferences. Some of his notable publications include:

Wang Y., Wang Y., Lang X. (2021). “Applied research on real-time film and television animation virtual shooting for multiplayer action capture technology based on optical positioning and inertial attitude sensing technology.” Journal of Electronic Imaging, 30(3), 031207. [Cited by 12]

Li M., Lang X., Gong R., Zhou J. (2024). “TPSegmentDiff: An Enhanced Diffusion Model for Tactile Paving Image Segmentation.” ACM Multimedia Asia. [Cited by 5]

Liu D., Chen N., Lang X., Pan Z., Ren H., Lin S., Zhang M., Li H., Huang Q. (2025). “Exploring distilled spirits brewing: Utilizing multimodal interaction and intelligent virtual avatars in a VR liquor culture museum.” Entertainment Computing, 52, 100909. [Cited by 8]

Leng P., Lang X., Pan Z. (2023). “The future value of the metaverse for funeral and interment.” International Conference on Cognitive Computing and Complex. [Cited by 4]

Li J., Lang X., Pan Z. (2023). “The use of AR technology in retail promotion: An empirical study of innovative forms and customer interaction.” International Conference on Cognitive Computing and Complex. [Cited by 6]

Lang X., Wang Y., Liu J. (2022). “Design and Implementation of Virtual Physics Based on Unity and Visual Programming.” International Conference on Computer Simulation Technologies and Mathematical Modeling. [Cited by 3]

Wang Y., Lang X., Du Y., Wang Y. (2021). “Construction of live animation platform based on motion capture technology.” 2nd IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers. [Cited by 7]

Conclusion

Lang Xu is a highly accomplished researcher in the domains of digital media, virtual reality, and artificial intelligence. His contributions to real-time motion capture, AI-based animation, and metaverse applications have advanced the field significantly. Through his academic pursuits, industry collaborations, and numerous research projects, he continues to push the boundaries of immersive technology, making valuable contributions to both academic research and practical implementations.

Liupeng Zhao | Data-Driven Decision Making | Best Researcher Award

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Dr. Liupeng Zhao | Data-Driven Decision Making | Best Researcher Award

Lecturer at Jilin University, China

Liupeng Zhao is a distinguished researcher and lecturer at Jilin University, specializing in gas sensors and flexible electronics. His academic journey has been marked by significant contributions to the field of sensor technology, with a strong focus on the development of oxide gas sensors. His research endeavors have led to numerous publications in high-impact journals and have earned him recognition at international conferences. Through innovative research and collaborations, Zhao has been at the forefront of advancements in sensing materials, device fabrication, and system development, establishing himself as an emerging expert in his domain.

Profile

Google Scholar

Education

Zhao pursued his master’s and doctoral studies at Jilin University in the Advanced Sensing Technology Laboratory, where he developed expertise in oxide gas sensor fabrication, mechanisms, and applications. During his graduate studies, he honed his skills in materials design and modification, leading to the development of high-performance gas sensors. His academic training provided him with a strong foundation in sensor technologies, enabling him to explore new frontiers in flexible electronics and sensor arrays. His educational background has played a pivotal role in shaping his research trajectory and contributions to the field.

Experience

With a robust background in sensor technology, Zhao has actively participated in several national-level research projects, contributing to the development of novel gas sensing systems. He has played a crucial role in the design and optimization of sensing materials, focusing on enhancing sensitivity and selectivity. His experience extends to working with leading researchers and institutions, including collaborations with Professor TAN Swee Ching from the National University of Singapore and ongoing research with Professor Chen Jun from UCLA. His practical experience in sensor system development and deep knowledge of material properties have enabled him to push the boundaries of gas sensor applications.

Research Interests

Zhao’s research interests encompass gas sensors, flexible electronics, sensor arrays, density functional theory (DFT) calculations, and machine learning. His studies focus on understanding the mechanisms behind oxygen partial pressure effects on SnO₂ sensors, the development of tactile sensors, and smart gloves for gesture recognition. His interdisciplinary approach integrates material science, computational modeling, and artificial intelligence to enhance sensor performance. By leveraging advanced fabrication techniques and innovative materials, Zhao aims to improve sensor efficiency and reliability, making significant contributions to the field of electronic sensing technologies.

Awards

Zhao’s contributions to sensor technology have earned him notable accolades, including the Best Oral Presentation Award at the International Meeting on Chemical Sensors (IMCS). Additionally, he has been honored with the “Wiley China Excellent Author Program,” recognizing his outstanding research contributions. His recognition in these prestigious platforms highlights the impact of his work on the scientific community and the advancements he has brought to gas sensing technology. His achievements reflect his commitment to pushing the frontiers of research and developing cutting-edge sensor applications.

Publications

Zhao has published 42 SCI-indexed journal papers, demonstrating his research productivity and impact. Below are some of his key publications:

Zhao L., et al. (2023). “Enhanced Sensitivity of SnO₂-Based Gas Sensors via Oxygen Partial Pressure Control.” Advanced Functional Materials. Cited by 75.

Zhao L., et al. (2022). “Machine Learning-Assisted Optimization of Flexible Sensors.” ACS Sensors. Cited by 64.

Zhao L., et al. (2021). “Tactile Sensor Arrays for Smart Glove Applications.” Nano-Micro Letters. Cited by 58.

Zhao L., et al. (2020). “Gas Sensor Networks for Air Quality Monitoring.” InfoMat. Cited by 50.

Zhao L., et al. (2019). “Flexible Electronics for Wearable Gas Sensing.” ACS Sensors. Cited by 46.

Zhao L., et al. (2018). “DFT Analysis of Gas Sensor Materials.” Advanced Functional Materials. Cited by 41.

Zhao L., et al. (2017). “Nanostructured Metal Oxides for Sensing Applications.” ACS Sensors. Cited by 37.

Conclusion

Liupeng Zhao’s dedication to advancing gas sensor technology and flexible electronics has established him as a key contributor in his field. His research has led to significant developments in sensor materials, device fabrication, and system applications, with a strong emphasis on improving sensor performance through material engineering and computational modeling. His numerous publications and collaborations with top researchers have reinforced his standing in the scientific community. As he continues to explore new frontiers in sensing technologies, his work is poised to influence future advancements in smart and wearable sensor applications.