Mengyao Li | Engineering | Best Researcher Award

Dr. Mengyao Li | Engineering | Best Researcher Award

Student at Nanyang Technological University Singapore

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

Professional Profile

Education

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

Professional Experience

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

Research Interests

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

Awards and Honors

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

Conclusion

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

Publications Top Noted

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

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

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

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

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

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

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

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

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

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

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

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

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)

 

Ananya Kuri | Engineering | Best Researcher Award

Ms. Ananya Kuri | Engineering | Best Researcher Award

Scientist | R&D Project Manager at Siemens AG, Germany

Ananya Kuri is an accomplished R&D Project Manager at Siemens AG, specializing in electrical power engineering and grid stability. With over 10 years of experience in the power systems sector, she has played a pivotal role in dynamic performance analysis, inverter-based resource modeling, and power grid optimization. Ananya holds a Ph.D. from FAU Erlangen (dissertation under review) and an M.Sc. in Electrical Power Engineering from RWTH Aachen University. She is known for her leadership in managing complex projects, mentoring teams, and collaborating with global customers. Her expertise lies in enhancing power system stability, modeling and analyzing power plants, and supporting grid compliance efforts. Ananya’s work spans across consulting, R&D, and training, with significant contributions to Siemens’ technology in power systems and microgrids. Her professional journey reflects a blend of innovation, technical excellence, and strong industry engagement, making her a respected figure in the energy sector.

Professional Profile

Education

Ananya Kuri’s academic credentials lay a solid foundation for her extensive career in power systems engineering. She holds a Ph.D. in Electrical Engineering from FAU Erlangen, where her dissertation is currently under review. Prior to this, she completed her M.Sc. in Electrical Power Engineering from RWTH Aachen University, one of Germany’s premier technical institutions. During her time at RWTH Aachen, Ananya developed a deep understanding of electrical power technologies and systems, which has been pivotal in her professional journey. Her B.Eng. in Electrical and Electronics Engineering from M.S. Ramaiah Institute of Technology in Bangalore, India, provided her with early insights into power systems, further shaping her technical expertise. Throughout her academic tenure, Ananya demonstrated a strong commitment to research, resulting in multiple published works and contributions to cutting-edge developments in the power systems domain, paving the way for her successful professional career.

Professional Experience

Ananya Kuri’s professional experience spans a decade of working with Siemens AG, where she has made significant contributions in both consulting and research roles. She began her career as a Senior Power Systems Consultant and Portfolio Element Owner in Siemens’ Digital Grid, focusing on transmission systems, inverter-based resources, and power grid stability. Her technical expertise was key in the modeling and analysis of various Siemens power systems products, including the Power Plant Controller and Microgrid Controller. Ananya has also held leadership roles as an R&D Project Manager, where she led projects like ENSURE Phase 3 for inverter-based resources and kurSyv for corrective system management in distribution networks. She has mentored teams, managed global consulting projects, and played an integral role in Siemens’ advancements in grid compliance, ensuring Siemens’ power systems meet the evolving needs of modern electrical grids. Her extensive work with international clients and R&D initiatives highlights her strong professional impact.

Research Interests

Ananya Kuri’s research interests lie primarily in the areas of power system stability, grid integration, and inverter-based technologies. Her work revolves around enhancing the dynamic performance of power grids, with a focus on transient stability, small-signal analysis, and frequency regulation. Ananya is particularly interested in the modeling and control of inverter-based resources, as these technologies are crucial in supporting the transition to renewable energy sources and the modernization of grid infrastructures. Her research also extends to the development of advanced control strategies for microgrids and power plants, aiming to improve grid stability and resilience. She is actively involved in R&D projects that address the operational challenges of integrating renewable energy into power systems, such as enhanced inverter control techniques. Ananya’s contributions to power system modeling, grid compliance studies, and dynamic simulations aim to drive innovations in power system operations and support the reliable and efficient operation of future grids.

Awards and Honors

Ananya Kuri’s outstanding contributions to the field of power systems engineering have earned her recognition within both the academic and professional communities. She has been actively involved in global research and development initiatives and has contributed to numerous successful consulting projects. Although specific awards are not mentioned, her leadership roles in industry-standard working groups like CIGRE and IEC, along with her involvement in over 35 working groups and 17+ published works, underscore her high standing in the industry. Ananya’s influence extends beyond her immediate work at Siemens, as she is recognized as a key member of international committees shaping the future of power system operations and standards. Her expertise in developing Siemens’ key products, such as the SICAM Power Plant Controller and Microgrid Controller, also highlights her significant contributions to the global energy sector. These honors and recognitions reflect her impact as a thought leader in electrical power engineering.

Conclusion

Ananya Kuri is highly suitable for the Best Researcher Award based on her extensive experience, leadership in R&D, technical expertise, and contributions to global research projects. Her work in inverter control strategies, grid stability, and model development for Siemens’ products directly addresses the challenges facing modern power systems. The only area for improvement would be completing her Ph.D. and further enhancing her public engagement. Overall, she represents the qualities of a forward-thinking researcher with significant industry impact.

Publications Top Noted

Title: Power Dispatch Capacity of a Grid-Forming Control Based on Phase Restoring Principle
Authors: A. Kuri, Ananya; R. Zurowski, Rainer; G. Mehlmann, Gert; M. Luther, Matthias
Journal: IEEE Systems Journal
Year: 2023
Citations: 3

 

Fred Lang | Engineering | Best Researcher Award

Mr. Fred Lang | Engineering | Best Researcher Award

President at Exergetic Systems Limited, United States

Fred D. Lang, P.E., P.Eng., is a distinguished power plant engineer with over 50 years of experience in energy systems, nuclear safety, and thermal performance monitoring. Renowned across North America and Europe, he has significantly contributed to power plant engineering through software innovation, advanced testing methodologies, and novel monitoring techniques. As the President of Exergetic Systems Limited, he has developed industry-transforming tools for power plant efficiency and safety. His contributions include consulting for major utilities and government agencies in the U.S., Canada, Sweden, and Japan, focusing on nuclear safety, fossil emissions monitoring, and performance analysis. Lang’s expertise spans simulation, plant design, exergy analysis, and fuel efficiency optimization, making him a leader in the energy sector. His commitment to research and technological advancements has led to groundbreaking methodologies that enhance power plant performance and operational safety, earning him a reputation as an innovator in the field.

Professional Profile

Education

Fred D. Lang has a strong academic background in nuclear engineering, mechanical engineering, and business administration. He earned his Bachelor of Science in Nuclear Engineering from Kansas State University, where he developed a deep understanding of power generation and reactor safety. He further advanced his expertise with a Master of Science in Mechanical Engineering from the University of Idaho, completing coursework at the Idaho National Laboratory, a leading nuclear research facility. To complement his technical knowledge with management skills, he pursued a Master of Business Administration (MBA) from the University of Oregon. In addition to his formal degrees, Lang holds several professional certifications, including a California Energy Auditor Certificate (#5872). He is a licensed Professional Engineer (P.E.) in California for mechanical and nuclear engineering and an active P.Eng. in British Columbia (#54236). His diverse educational background has provided him with the expertise to drive innovation in power plant engineering.

Professional Experience

Fred D. Lang has had an illustrious career spanning over five decades in power plant engineering. He is the President of Exergetic Systems Limited, a company specializing in power plant performance monitoring and efficiency solutions. Previously, he founded and led Exergetic Systems, Inc., which for nearly 40 years served major utilities across North America with software and engineering services. Lang is known as the “Father of PEPSE,” a widely used power plant simulation software. His expertise includes thermodynamic analysis, emissions monitoring, and nuclear safety systems. He has conducted hundreds of power plant studies and has been involved in 33 thermal performance evaluation projects, each lasting several months. His professional experience also includes consulting for Babcock & Wilcox, Exxon Nuclear (now Framatome), and government agencies in Sweden and Japan on critical nuclear safety issues. His work has shaped modern approaches to fuel monitoring, efficiency testing, and safety in power generation.

Research Interests

Fred D. Lang’s research focuses on power plant thermodynamics, nuclear safety, emissions monitoring, and exergy analysis. His work aims to enhance the efficiency, safety, and sustainability of fossil-fuel and nuclear power plants. A major area of his research is the development of advanced monitoring techniques, such as the Input/Loss Method, which allows real-time determination of fuel chemistry, calorific value, and heat rate in coal-fired power plants. Another significant contribution is the NCV Method, a groundbreaking approach to nuclear reactor monitoring, neutron flux measurement, and coolant flow analysis, which improves nuclear safety. Lang has also developed innovative instrumentation for emissions testing, heat balance analysis, and fuel efficiency optimization. His research integrates software development, thermodynamic modeling, and real-world application, ensuring that power plants operate more efficiently while reducing environmental impact. His findings have led to significant improvements in plant performance and fuel economy worldwide.

Awards and Honors

Fred D. Lang has received numerous accolades for his contributions to power plant engineering and nuclear safety. He holds 38 patents, including 22 in the U.S. and 16 in Canada, Australia, and Europe, covering innovations in power plant instrumentation, Rankine cycle modifications, and emissions monitoring technologies. His pioneering Input/Loss Method and NCV Method have been recognized as transformative advancements in the energy sector. Lang has been invited by major utilities and government agencies to develop new technologies, including a 2021 invitation to design a novel nuclear plant monitoring system. His software tools, such as PEPSE, EX-FOSS, and THERM, are used by leading power utilities worldwide. In addition to his technical achievements, he has been honored for his mentorship and leadership in the engineering field. His work has redefined power plant efficiency, fuel monitoring, and nuclear safety standards, earning him a reputation as a pioneer in the industry.

Conclusion

Fred D. Lang is a highly deserving candidate for the Best Researcher Award, given his profound contributions to power plant engineering, groundbreaking patents, and practical innovations in thermal performance and nuclear safety. While strengthening academic publications and mentorship efforts could further solidify his influence, his technical advancements have already had a significant impact on the industry. His work represents a paradigm shift in power plant monitoring and nuclear reactor safety, making him a strong contender for this recognition.

Publications Top Noted

  • Lang, F. D. (Year Unknown). “Verified Knowledge of Nuclear Power Plants Using the NCV Method.” Conference Paper. Citations: 0

  • Lang, F. D., Mason, D., & Rodgers, D. A. T. (Year Unknown). “Effects on Boiler Efficiency Standards and Computed Coal Flow Given Variable Ambient Oxygen and Humidity.” Conference Paper. Citations: 0

 

Chung-Horng Lung | Engineering | Best Researcher Award

Chung-Horng Lung | Engineering | Best Researcher Award

Full Professor at Carleton University, Canada

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

Professional Profile

Education

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

Professional Experience

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

Research Interests

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

Awards and Honors

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

Conclusion

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

Publications Top Noted

📖 Journal Articles

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

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

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

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

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

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

🎤 Conference Papers

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

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

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

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

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

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

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

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

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

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

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

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

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

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

 

Arvind Chaurasiya | Engineering | Best Researcher Award

Mr. Arvind Chaurasiya | Engineering | Best Researcher Award

Student at Sardar Vallabhbhai National institute of technology, India

Arvind Chaurasiya is a dedicated and passionate Structural Engineer currently working with Systra India since July 2023. With a strong foundation in structural design, he is well-versed in Indian Standards and Eurocode for structural designs. Arvind has always exhibited a drive for continuous learning and innovation in the ever-evolving field of structural engineering. His dynamic approach to design, coupled with a genuine interest in technologies that boost productivity, efficiency, and quality, makes him an emerging talent in the field. He is particularly known for his analytical skills and for effectively contributing to high-stakes infrastructure projects across various countries. Arvind’s curiosity and commitment to enhancing structural engineering practices ensure that he is not just a professional but an engineer who strives to push the boundaries of his discipline with each project.

Professional Profile

Education

Arvind Chaurasiya completed his education with a Bachelor’s degree in Civil Engineering, which laid the foundation for his career in structural engineering. Throughout his academic journey, he demonstrated a keen interest in structural dynamics, design principles, and load-bearing systems. His education included in-depth coursework on various Indian Standards, Eurocodes, and modern structural analysis techniques. He also participated in various seminars and workshops on advanced software tools like Midas Civil and Staad Pro, which gave him the skills needed to transition smoothly into his professional career. Arvind’s educational background not only provided him with a solid technical base but also instilled in him a passion for lifelong learning, driving him to continuously explore new technologies and approaches in structural design.

Professional Experience

Arvind’s professional experience includes working on several high-profile international projects that have honed his skills in structural design and analysis. Currently employed at Systra India, he has been involved in projects like the High-Speed Rail Project in the United Kingdom and Standard Gauge Railway in Tanzania. His role spans from designing detailed project reports to performing complex load calculations and structural analysis using software like Midas Civil and Staad Pro. Notably, Arvind has worked on the design of structural elements like culverts, retaining walls, and bridges, contributing to large-scale infrastructure initiatives. His experience in these diverse projects has not only strengthened his technical expertise but also expanded his understanding of international design practices and safety standards. His contribution to projects such as the UAE Oman Rail Link further solidifies his position as a rising star in the field.

Research Interests

Arvind’s primary research interest lies in improving the efficiency and sustainability of structural designs. He is particularly focused on integrating advanced technologies into the design process to optimize material usage, reduce construction time, and enhance structural performance. Arvind is deeply intrigued by the potential of automation, AI-based tools, and machine learning algorithms in revolutionizing the way structures are designed and analyzed. His goal is to explore innovative ways of designing energy-efficient, eco-friendly, and cost-effective infrastructure systems that align with the growing emphasis on sustainable development. Additionally, Arvind is passionate about researching advanced finite element analysis (FEA) techniques and their application in real-world structural engineering problems, aiming to reduce errors and improve safety outcomes in design.

Awards and Honors

Although Arvind Chaurasiya is at the beginning stages of his career, his contribution to several high-profile international engineering projects has garnered recognition among his peers and supervisors. His meticulous approach to project design and analysis, along with his commitment to quality, has earned him appreciation for his work on infrastructure projects like the High-Speed Rail Project in the UK and Mwanza to Isaka Railway Project in Tanzania. Though still early in his career, Arvind’s ongoing focus on developing innovative structural designs and utilizing cutting-edge technologies has positioned him as a promising candidate for future awards and honors. As he continues to accumulate experience and further his research interests, he is expected to make significant strides in both academic and professional recognition, contributing to the field of structural engineering in a more impactful way.

Conclusion

Arvind Chaurasiya exhibits strong technical expertise and practical experience, especially with international and high-profile projects. His ability to work with advanced structural engineering tools and his enthusiasm for new technologies are commendable and position him as a promising candidate in the field. However, for the Best Researcher Award, there is room for improvement in areas related to research output and innovation. To be fully suitable for such an award, Arvind would benefit from publishing more research, contributing original ideas to the field, and demonstrating how his work has pushed the boundaries of structural engineering theory and practice.

Publications Top Noted

1. Optimization of Geometric Properties of Deck Arch Steel Bridge Using Analytical Study
  • Authors: Chaurasiya, A., Biswal, A., Tamizharasi, G., Goel, R.
  • Year: 2025
  • Publication: Lecture Notes in Civil Engineering, Volume 550, pp. 173–180.
  • Citations: 0
2. Cyber Security Terrain and Thwarting Cyber Attacks Using Artificial Intelligence
  • Authors: Sharma, S., Dwivedi, R.K., Upadhyay, N., Kashyap, P., Chaurasiya, A.K.
  • Year: 2024
  • Publication: Lecture Notes in Electrical Engineering, Volume 1191, pp. 679–685.
  • Citations: 0

 

Anna Plichta | Engineering | Best Researcher Award

Mrs. Anna Plichta | Engineering | Best Researcher Award

Research and Teaching Assistant Professor, Cracow University of Technology, Poland

Dr. Anna Plichta is a Research and Teaching Assistant Professor at Cracow University of Technology, Poland, where she also works at the International Center of Education. With a multifaceted background in Comparative Literature and Computer Science, she combines insights from the humanities with advanced computational techniques. Dr. Plichta holds a PhD in Computer Science from Politechnika Wrocławska (2019) and has a strong academic foundation with degrees from Jagiellonian University and Politechnika Krakowska. Her interdisciplinary research focuses on machine learning, artificial intelligence, and applied computer science, with practical applications in energy systems, motor diagnostics, and microbiology. With a commitment to educational excellence and international collaboration, Dr. Plichta has been a key figure in research and teaching at the university for over a decade.

Profile

Strengths for the Award

  1. Diverse Research Interests and Impact: Dr. Plichta’s work spans multiple domains including comparative literature, computer science, machine learning, electrical engineering, and applied mathematics. This interdisciplinary approach showcases her ability to bridge distinct fields, offering innovative solutions to complex problems. Notably, her research on bacterial classification using machine learning methods and energy consumption forecasting using machine learning reflects her versatility and the relevance of her work to contemporary scientific and industrial challenges.
  2. High Citation Impact: Her publication titled “Deep learning approach to bacterial colony classification” has received 134 citations, which demonstrates significant influence and recognition in the scientific community. This kind of citation impact highlights the relevance and utility of her research findings.
  3. Technological Innovation: Her contributions to induction motor fault detection using machine learning techniques (e.g., simulated annealing and genetic algorithms) are highly practical, with clear industrial applications. This emphasizes her role in driving innovation in applied fields, particularly in electromechanical systems and energy sectors, making her work not only academic but also relevant to real-world problems.
  4. Academic Leadership and Teaching: As a Research and Teaching Assistant Professor at Cracow University of Technology, Dr. Plichta combines academic instruction with significant research involvement. Her active engagement in the International Center of Education is a testament to her dedication to fostering a new generation of researchers and students.
  5. Publication Quality: Dr. Plichta consistently publishes in peer-reviewed journals and presents at high-level conferences like those organized by the European Council for Modelling and Simulation. This speaks to her engagement with the broader academic community and her ability to produce high-quality research.

Areas for Improvement

  1. Collaboration and Interdisciplinary Work: While Dr. Plichta’s interdisciplinary work is commendable, further expanding collaborations with other research groups and international institutions could enhance the visibility and impact of her work. Expanding collaborative efforts, especially with industry partners, could help bring more practical applications to the forefront.
  2. Public Outreach and Dissemination: While her publications and citations are notable, there could be a more concerted effort to engage with the general public or non-academic stakeholders, particularly in areas like bacterial classification and energy forecasting, where her research could have significant societal impact. This could include public lectures, podcasts, or participation in science communication events.
  3. Further Publishing in High-Impact Journals: Publishing in higher-impact journals (e.g., Nature, IEEE Transactions) could further boost the international recognition of her work. While her current journal choices are respected, elevating the visibility of her research in top-tier outlets may further her career and contribute to the recognition of her as a leading expert in her field.

Education

Dr. Anna Plichta’s academic journey blends the study of literature and technology. She earned a BA in Comparative Literature (2005) and MA in Comparative Literature (2007) from Jagiellonian University. Her fascination with technology led her to pursue an MA in Computer Science (2010) from Politechnika Krakowska, followed by a PhD in Computer Science from Politechnika Wrocławska (2019). Her doctoral research focused on applying computational methods to real-world engineering challenges, a field that bridges the gap between theoretical knowledge and practical applications. With this strong foundation, she applies machine learning and AI techniques to diverse areas such as energy forecasting, motor fault detection, and bacterial classification. Dr. Plichta’s educational background not only demonstrates her expertise in both the arts and sciences but also her commitment to lifelong learning and interdisciplinary research.

Experience 

Dr. Anna Plichta has had a distinguished career as a Research and Teaching Assistant Professor at Cracow University of Technology since 2010. She has been an integral part of the university’s International Center of Education since 2015, fostering international research collaboration. Dr. Plichta’s professional experience spans both teaching and research, with a particular emphasis on computational techniques applied to energy systems, mechanical engineering, and biology. She has developed and taught courses related to machine learning, AI, and applied computer science. Her academic leadership extends to guiding postgraduate students and conducting collaborative research projects. Dr. Plichta’s expertise in energy consumption modeling, motor diagnostics, and microbial classification has positioned her as a thought leader in these domains, contributing to over 17 published works. She is also involved in the advancement of international education, contributing to the university’s global research network.

Research Focus 

Dr. Anna Plichta’s research focuses on applying machine learning and artificial intelligence to solve complex problems in fields ranging from energy systems to biological data analysis. Her work in forecasting energy consumption uses advanced computational techniques to predict energy demands in clusters, supporting sustainable energy solutions. In the area of electromechanical engineering, she has applied genetic algorithms and wavelet analysis to detect faults in induction motors, such as inter-turn short circuits. Additionally, her research in microbiology explores the use of image analysis and neural networks to identify bacterial species, contributing to more accurate and efficient diagnostic methods. Dr. Plichta is deeply invested in interdisciplinary research, bringing together computational methods with practical applications in industries such as energy, engineering, and healthcare. She is particularly interested in improving the accuracy and efficiency of diagnostic techniques and optimizing energy consumption through AI-driven models.

Publication 

  1. Forecasting Energy Consumption in Energy Clusters using Machine Learning Methods 📊💡
  2. Matrix Similarity Analysis of Texts Written in Romanian and Spanish 📚🔍
  3. Identification of Inter-turn Short-Circuits in Induction Motor Stator Winding Using Simulated Annealing ⚡🔧
  4. Application of Genetic Algorithm for Inter-turn Short Circuit Detection in Stator Winding of Induction Motor ⚙️🧠
  5. Recognition of Species and Genera of Bacteria by Means of the Product of Weights of the Classifiers 🦠🔬
  6. Application of Image Analysis to the Identification of Mass Inertia Momentum in Electromechanical Systems with Changeable Backlash Zone ⚙️🔍
  7. Application of Wavelet-Neural Method to Detect Backlash Zone in Electromechanical Systems Generating Noises 🔧🌊
  8. Methods of Classification of the Genera and Species of Bacteria Using Decision Tree 🌱📈
  9. Deep Learning Approach to Bacterial Colony Classification 🧬🤖
  10. The DDS Synthesizer (for FPGA Platform) for the Purpose of Research and Education 💻📚

Conclusion

Dr. Anna Plichta is a highly suitable candidate for the Best Researcher Award due to her multidisciplinary approach, significant research contributions, high citation impact, and leadership in academia. She has demonstrated a consistent ability to tackle complex challenges through computational methods, contributing valuable knowledge to both the scientific community and industrial sectors. Her work, particularly in machine learning and electromechanical systems, is both innovative and impactful.While there are always areas for improvement, such as expanding collaborative efforts and public outreach, these do not overshadow her significant academic achievements. Dr. Plichta’s track record of high-quality research and teaching, along with her contribution to solving real-world problems, make her an excellent contender for the Best Researcher Award.

Mahmoud Mossa | Engineering | Best Researcher Award

Assoc Prof Dr. Mahmoud Mossa | Engineering | Best Researcher Award

Associate Professor, Electrical Engineering Department, Faculty of Engineering, Minia University, Egypt

Dr. Mahmoud Mohamed, also known as Mahmoud A. Mossa, is a distinguished Associate Professor in the Department of Electrical Engineering at Minia University in Egypt, with significant research contributions across Egypt and Italy. His expertise centers around electrical engineering, focusing on control systems, renewable energy, and microgrid applications. With a strong international academic and research background, Dr. Mohamed has made impactful strides in sustainable energy systems through innovative adaptive control and protection schemes.

Publication Profile

Google Scholar

Education 🎓

Ph.D. in Industrial Engineering – Università degli Studi di Padova, Italy (2014–2017). M.Sc. in Electrical Engineering – Minia University, Egypt (2010–2013). B.Sc. in Electrical Engineering – Minia University, Egypt (2003–2008)

Experience 💼

Associate Professor – Minia University, Egypt (2023–Present), Assistant Professor – Minia University, Egypt (2018–Present), Postdoctoral Researcher – Università degli Studi di Padova, Italy (2021–2022), Research Fellow (Borsisti) – Università degli Studi di Padova, Italy (2017–2018),Doctoral Researcher – Università degli Studi di Padova, Italy (2014–2017)

Research Interests 🔍

Dr. Mohamed’s research spans renewable energy, advanced control systems, DC microgrid applications, and wind energy systems. His work emphasizes innovative approaches to adaptive control, predictive methods for energy optimization, and protection schemes to enhance system resilience, particularly in renewable energy and microgrid contexts.

Awards 🏆

Dr. Mohamed has been recognized for his research contributions in electrical engineering and sustainable energy applications, with several publications featured in high-impact journals.

Selected Publications 📚

Adaptive Control Approach for Accurate Current Sharing and Voltage Regulation in DC Microgrid Applications
Energies, 2024. DOI: 10.3390/en17020284

Application and Comparison of a Modified Protection Scheme Utilizing a Proportional–Integral Controller with a Conventional Design to Enhance Doubly Fed Induction Generator Wind Farm Operations during a Balanced Voltage Dip
Processes, 2023. DOI: 10.3390/pr11102834

Enhancing the Performance of a Renewable Energy System Using a Novel Predictive Control Method
Electronics, 2023. DOI: 10.3390/electronics12163408

Enhancement of LVRT Ability of DFIG Wind Turbine by an Improved Protection Scheme with a Modified Advanced Nonlinear Control Loop
Processes, 2023. DOI: 10.3390/pr11051417

 

Nasimuddin | Engineering | Best Researcher Award

Dr. Nasimuddin | Engineering | Best Researcher Award

Principal Scientist I2R ASTAR  Singapore

Nasimuddin is a Principal Scientist at the Institute for Infocomm Research (I²R), part of A*STAR in Singapore. With a distinguished career in RF and antenna engineering, he has contributed extensively to the fields of wireless power transmission, sensor design, and advanced antenna systems for a variety of applications including satellite communications and energy harvesting. Nasimuddin’s work bridges industry and academia, evidenced by his collaborations, industry technology transfers, and numerous patents.

profile

Google scholar.com

Education 🎓

  • Ph.D. in Electronic Science (2004): University of Delhi, India
    Thesis: Analysis and design of multilayer slow-wave microstrip structures and multilayered microstrip antennas.
  • M.Tech. in Microwave Electronics (1998): University of Delhi, India
  • M.Sc. in Electronics (1996): Jamia Millia Islamia, India
  • B.Sc. in Physics, Mathematics, Chemistry (1994): Jamia Millia Islamia, India

Experience 🏢

Nasimuddin has held various research and teaching roles. Since 2006, he has been part of I²R, A*STAR Singapore, where he currently serves as a Principal Scientist. He was an Honorary Research Associate and Fellow at Macquarie University in Australia (2009–2020) and held a Postdoctoral Research Fellowship under an ARC Discovery Project at Macquarie University (2004–2006). He has also conducted specialized courses in RF energy harvesting applications at NIT Silchar, India.

Research Interests 🔬

Nasimuddin’s research interests include:

  • Advanced antenna engineering for sensor and wireless systems
  • High-gain, compact metamaterial-based antennas
  • Printed and flexible electronics
  • Beam steering antennas and phased array systems
  • RF energy harvesting and wireless power transmission systems
    His research focuses on microwave and millimeter-wave antennas, addressing challenges in satellite communication, RFID, and beamforming technologies.

Awards 🏆

  • Singapore Manufacturing Federation Award (2014): Recognized for contributions to TVWS Transceiver Radio Technology (team award).
  • Dedicated Service Award (2022): Honored for 15 years at I²R, Singapore.
  • Long Service Awards (2012, 2017): For 5 and 10 years at I²R, Singapore.
  • Young Scientist Award (2005): Awarded by the International Union of Radio Science (URSI).
  • M.Tech. Merit Scholarship (1996): University of Delhi, for outstanding academic performance.

Publications Top Notes📚:

Dielectric Resonator Antennas for RF Energy-Harvesting/Wireless Power Transmission Applications: A State-of-the-Art Review – IEEE Antennas and Propagation Magazine, 2024. Cited by 12 articles.

Rectifier Circuits for RF Energy Harvesting and Wireless Power Transfer Applications: A Comprehensive Review Based on Operating Conditions – IEEE Microwave Magazine, 2023. Cited by 18 articles.

5G/Millimeter-Wave Rectenna Systems for RF Energy Harvesting/Wireless Power Transmission Applications: An Overview – IEEE Antennas and Propagation Magazine, 2023. Cited by 25 articles.

A Single-Feed Wideband Circularly Polarized Dielectric Resonator Antenna Using Hybrid Technique with a Thin Metasurface – IEEE Access, 2022. Cited by 10 articles.

Quantifying the Impact of Slow Wave Factor on Closed-Loop Defect-Based WPT Systems – IEEE Transactions on Instrumentation and Measurement, 2022. Cited by 8 articles.

Assoc Prof. Dr. Chunlu Qian | Engineering | Best Researcher Award

Assoc Prof. Dr. Chunlu Qian | Engineering | Best Researcher Award

Assoc Prof. Dr. Chunlu Qian, Yangzhou University, China

Chunlu Qian is an Associate Professor and Department Chair at the School of Food Science and Engineering, Yangzhou University, China. With a passion for postharvest physiology, he specializes in enhancing fruit quality through innovative preservation techniques. His work not only advances academic knowledge but also contributes significantly to the food industry.

Profile

Scopus

Orcid

Education 🎓

Dr. Qian completed his Bachelor’s degree in Horticulture Science from Henan Agriculture University in 2005. He then earned his Master’s in Vegetable Science from Zhejiang University in 2007, followed by a Ph.D. in Food Science, focusing on postharvest cucumber physiology, in 2013.

Experience 💼

Since April 2013, Dr. Qian has served as an Assistant Professor and later as an Associate Professor at Yangzhou University. He has also gained international experience as a Visiting Scientist at Nagoya University, Japan, enhancing his research perspectives and methodologies.

Research Interest 🔍

Dr. Qian’s research primarily revolves around postharvest physiology of fruits, focusing on methods to maintain fruit quality during storage using physical and chemical treatments. His interests also include studying flavor changes during the growth and preservation processes, which he incorporates into his teaching of various food science courses.

Awards 🏆

Dr. Qian has been recognized for his contributions to the field with several awards, although specific details on nominations or accolades are not provided in the available information.

Publication Top Notes 📚

Cai et al. (2024) – Study on quality and starch characteristics of powdery and crispy Lotus Roots, Foods.

Qian et al. (2024) – Effects of melatonin on postharvest water bamboo shoots, Food Chemistry: Molecular Sciences.

Zhang et al. (2024) – Role of PbrWRKY62 in scald development of pear fruit, Molecular Horticulture.

Ding et al. (2023) – Flavor characteristics of ten peanut varieties, Foods.

Qian et al. (2023) – Texture and flavor changes of lotus root, Foods.