Ling Xu | Engineering | Young Scientist Award | 4273

Assoc. Prof. Dr. Ling Xu | Engineering | Young Scientist Award

Teacher | Fuzhou University | China

Assoc. Prof. Dr. Ling Xu is an Associate Professor at the College of Civil Engineering, Fuzhou University, specializing in transportation infrastructure construction, pavement materials, and maintenance engineering. He holds a doctorate in Transportation Engineering, a visiting scholarship in civil infrastructure research, and a bachelor’s degree in Civil Engineering, providing a solid academic foundation in pavement mechanics, material behavior, and life-cycle performance. His professional experience includes contributing to national and industry-funded projects on polyurethane concrete runway overlays, rubberized asphalt durability, high RAP mixture cracking mechanisms, high-speed railway waterproofing layers, and flexible interlayer systems for airfield pavements. His research focuses on low-carbon pavement materials, road maintenance technologies, numerical simulation, data mining, image processing, and life-cycle analysis, leading to impactful publications in high-ranking international journals on asphalt modification, pavement sustainability, thermal-mechanical behavior, and innovative maintenance materials. Recognized with a Young Scientist Award, he has also contributed to the academic community through editorial and review activities, professional memberships, and active participation in interdisciplinary research collaborations.

Citation Metrics (Scopus)

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Citations

606

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Featured Publications

Chang Soo Kim | Engineering | Best Researcher Award

Prof. Chang Soo Kim | Engineering | Best Researcher Award

Professor | Pukyong National University | South Korea

Professor. Chang Soo Kim is a distinguished Full Professor in the Division of Computer and AI Engineering at PuKyong National University, recognized for his expertise in intelligent manufacturing systems, artificial intelligence, and computational optimization. He holds advanced degrees in computer science with specialization in AI-driven optimization and machine learning, forming the foundation for his multidisciplinary research career. Throughout his long-standing academic tenure, he has served in key leadership roles including department chair, graduate program administrator, research center director, and executive leader for university–industry cooperation, successfully guiding large-scale projects, fostering collaborative innovation, and advancing strategic academic initiatives. His research focuses on flexible job shop scheduling, deep learning–based fault diagnosis, time-series forecasting, metaheuristic optimization, and smart industrial systems. He has produced an extensive portfolio of influential publications in high-impact SCI-indexed journals, contributing novel hybrid algorithms, trainable fusion strategies, adaptive scheduling frameworks, lightweight diagnostic models, and intelligent computational methods that support the evolution of smart manufacturing and data-driven engineering. His scholarly achievements have earned him multiple recognitions, including awards for research excellence, and he actively contributes to the global academic community through editorial service, participation in professional societies, and engagement in scientific committees. With a sustained record of innovative research, academic leadership, and impactful contributions to computer and AI engineering, Professor Chang Soo Kim exemplifies the qualities of a leading researcher whose work continues to influence both industry and academia.

Profiles:  Scopus

Featured Publications

1. Kim, C. S., et al. (2025). Flexible job shop scheduling optimization with multiple criteria using a hybrid metaheuristic framework. Processes.

2. Kim, C. S., et al. (2025). Multi-branch global Transformer-assisted network for fault diagnosis. Applied Soft Computing.

3. Kim, C. S., et al. (2025). DL-MSCNN: A general and lightweight framework for fault diagnosis with limited training samples. Journal of Intelligent Manufacturing.

4. Kim, C. S., et al. (2025). Enhanced quantum-based DNA sequence alignment with noise handling and error detection. IEEE Access.

5. Kim, C. S., et al. (2024). GAILS: An effective multi-object job shop scheduler based on genetic algorithm and iterative local search. Scientific Reports.

Professor Chang Soo Kim’s pioneering research in intelligent manufacturing, AI-driven optimization, and fault diagnosis advances the scientific foundations of smart industry while enabling more efficient, reliable, and data-driven production systems. His innovative computational frameworks and adaptive algorithms contribute directly to industrial digital transformation, fostering technological competitiveness and sustainable global innovation.

Weitao Yue | Engineering | Research Excellence Award

Dr. Weitao Yue | Engineering | Research Excellence Award

China University of Mining and Technology | China

Dr. Weitao Yue is a Ph.D. candidate in Safety Science and Engineering at the China University of Mining and Technology, recognized for his specialization in coal and rock dynamic disaster prevention and control. With an academic foundation centered on advanced safety engineering and a research focus on hazardous dynamic phenomena in mining environments, he has developed strong expertise in the investigation of disaster mechanisms, monitoring technologies, early-warning strategies, and innovative control methods. His professional experience includes substantial involvement in major national scientific projects, where he has taken on core research roles involving theoretical modeling, experimental system development, large-scale data analysis, and interdisciplinary coordination. Through these efforts, he has demonstrated leadership, technical depth, and the ability to drive complex research tasks toward impactful outcomes. Dr. Yue has published multiple high-quality SCI papers as first or corresponding author in internationally renowned journals, with several works recognized among the most globally cited in the field, reflecting his rising academic influence and contribution to advancing coal mine safety science. His research achievements have earned significant academic recognition, further supported by his participation in professional research communities and contributions to collaborative scientific endeavors. Known for integrating theoretical insight with practical application, he consistently delivers research that supports safer mining operations and enhances scientific understanding of dynamic disasters. His growing portfolio of accomplishments, strong methodological capabilities, and commitment to scientific innovation position him as a promising researcher with substantial potential for future leadership and continued contribution to the safety engineering discipline.

Profiles:  Scopus

Featured Publications

1. [Authors not provided]. (2026). Failure mechanisms of fault fracture zone under dynamic loading. Engineering Failure Analysis.

Tun Naw Sut | Chemical Engineering | Best Researcher Award

Dr. Tun Naw Sut | Chemical Engineering | Best Researcher Award

Sungkyunkwan University | South Korea

Dr. Tun Naw Sut is a postdoctoral fellow specializing in nanomedicine, biomimetic membranes, and bio-sensing technologies, recognized for his interdisciplinary expertise and impactful research contributions. He holds dual doctoral training in nanomedicine and chemical engineering, supported by prior qualifications in materials science and biomedical engineering, forming a strong foundation for his work at the interface of engineering, biotechnology, and nanomaterials. His professional experience spans academic research, diagnostic platform development, electrochemical biomarker detection, phospholipid self-assembly studies, and compliance testing of medical electrical equipment, reflecting both scientific depth and industry-relevant technical capability. Dr. Sut’s research focuses on lipid-based nanomaterials, membrane biophysics, antimicrobial lipids, diagnostic sensors, and therapeutic nanoplatforms, and he has authored numerous publications in high-impact journals that advance the understanding and application of functional biomimetic systems. His leadership includes serving as guest editor and topic editor for international journals, contributing to the curation of scholarly work in biomimicry, functional materials, and membrane science. He has been recognized through competitive research grants, academic scholarships, and editorial appointments that highlight his innovation, scientific rigor, and growing influence in the field. Through his combined research excellence, interdisciplinary training, and dedication to advancing diagnostic and therapeutic technologies, Dr. Sut demonstrates exceptional potential for continued contributions to scientific innovation and research leadership.

Profiles: Scopus | ORCID

Featured Publications

1. Molla, A., Sut, T. N., Yoon, B. K., & Jackman, J. A. (2025). Headgroup-driven binding selectivity of alkylphospholipids to anionic lipid bilayers. Colloids and Surfaces B: Biointerfaces.

2. Lee, C. J., Jannah, F., Sut, T. N., Haris, M., & Jackman, J. A. (2025). Curvature-sensing peptides for virus and extracellular vesicle applications. ACS Nano.

3. Kim, D., Baek, H., Lim, S. Y., Lee, M. S., Lyu, S., Lee, J., Sut, T. N., Gonçalves, M., Kang, J. Y., Jackman, J. A., & Kim, J. W. (2025). Mechanobiologically engineered mimicry of extracellular vesicles for improved systemic biodistribution and anti-inflammatory treatment efficacy in rheumatoid arthritis. Advanced Healthcare Materials.

4. Ruano, M., Sut, T. N., Tan, S. W., Mullen, A. B., Kelemen, D., Ferro, V. A., & Jackman, J. A. (2025). Solvent-free microfluidic fabrication of antimicrobial lipid nanoparticles. ACS Applied Bio Materials.

5. Hwang, Y., Zhao, Z. J., Shin, S., Sut, T. N., Jackman, J. A., Kim, T., Moon, Y., Ju, B. K., Jeoni, J. H., Cho, N. J., & Kim, M. (2025). Nanopot plasmonic sensor platform for broad spectrum virus detection. Chemical Engineering Journal.

Dr. Tun Naw Sut’s work advances next-generation diagnostic and therapeutic technologies through innovative biomimetic membrane engineering and lipid-based nanomaterials. His research contributes to global health by enabling more effective pathogen detection, improved targeted delivery systems, and transformative strategies for sensing and treating complex diseases.

Dongfeng Qi | Engineering | Best Researcher Award

Prof. Dongfeng Qi | Engineering | Best Researcher Award

Professor | Shandong University of Technology | China

Prof. Dongfeng Qi is a leading researcher in laser manufacturing and material processing, specializing in femtosecond and nanosecond laser applications for advanced materials and flexible electronics. His work integrates theoretical modeling with experimental techniques to develop innovative micro- and nanostructures, including copper and silicon-based materials, phase-change films, and smart electronic devices. Prof. Qi has made substantial contributions to understanding laser-material interactions and patterning technologies, with high-impact publications in top-tier journals. He demonstrates strong interdisciplinary collaboration and mentorship, fostering international research partnerships and the growth of emerging scientists. His research is recognized for both fundamental insights and practical applications in photonics, energy storage, and flexible electronics. Prof. Qi’s consistent innovation, high-quality experimental work, and leadership in the field establish him as a leading figure in laser-based materials science. According to Scopus, he has 535 citations, 71 documents, and an h-index of 13.

Profiles: Scopus | Google Scholar

Featured Publications

1. Programming nanoparticles in multiscale: optically modulated assembly and phase switching of silicon nanoparticle array; L. Wang, Y. Rho, W. Shou, S. Hong, K. Kato, M. Eliceiri, M. Shi, …; ACS Nano, vol. 12, no. 3, pp. 2231–2241, 2018; 39 citations

2. Time-resolved analysis of thickness-dependent dewetting and ablation of silver films upon nanosecond laser irradiation; D. Qi, D. Paeng, J. Yeo, E. Kim, L. Wang, S. Chen, C. P. Grigoropoulos; Applied Physics Letters, vol. 108, no. 21, 2016; 37 citations

3. Femtosecond laser-induced large area of periodic structures on chalcogenide glass via twice laser direct-writing scanning process; X. Yu, Q. Zhang, D. Qi, S. Tang, S. Dai, P. Zhang, Y. Xu, X. Shen; Optics & Laser Technology, vol. 124, 105977, 2020; 34 citations

4. Progress in the design, nanofabrication, and performance of metalenses; Z. Wang, Y. Wu, D. Qi, W. Yu, H. Zheng; Journal of Optics, vol. 24, no. 3, 033001, 2022; 31 citations

5. Progress in preparation and applications of Te-As-Se chalcogenide glasses and fibers; Z. Wu, Y. Xu, D. Qi, Q. Nie, X. Zhang; Infrared Physics & Technology, vol. 102, 102981, 2019; 31 citations

Xingjia Li | Engineering | Best Researcher Award

Dr. Xingjia Li | Engineering | Best Researcher Award

Senior Engineer at Shanghai Liangxin Electrical Co. Ltd, China

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

Professional Profile 

ORCID Profile

Education

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

Professional Experience

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

Research Interest

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

Award and Honor

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

Conclusion

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

Publications Top Notes

Velislava Lyubenova | Engineering | Best Researcher Award

Prof. Velislava Lyubenova | Engineering | Best Researcher Award

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

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

Professional Profile 

Google Scholar
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ORCID Profile

Education

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

Professional Experience

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

Research Interest

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

Award and Honor

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

Conclusion

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

Publications Top Notes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Shekhar Suman | Engineering | Young Scientist Award

Dr. Shekhar Suman | Engineering | Young Scientist Award

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

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

Professional Profile 

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Education

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

Professional Experience

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

Research Interest

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

Award and Honor

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

Conclusion

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

Publications Top Notes

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

 

Ming Yan | Engineering | Best Researcher Award

Prof. Ming Yan | Engineering | Best Researcher Award

Professor at Communication University of China, China

Ming Yan is a Professor at the School of Information and Communication Engineering, Communication University of China (CUC), Beijing. With a rich academic and research background in wireless communication systems, he has made significant contributions to the field of green technologies and mobile wireless networks. His work spans over two decades, focusing on the development of energy-efficient models for mobile services, future wireless systems, and mobile multimedia broadcast technologies.

Profile

Scholar

Education 🎓

Ming Yan earned his B.S. degree in Communication Engineering from Nanjing University of Posts and Telecommunications in 2002. He later pursued M.S. and Ph.D. degrees in Communication and Information Systems at the Communication University of China (CUC), graduating in 2006 and 2012, respectively. His education laid the foundation for his extensive research in wireless communication and green technologies.

Experience 💼

After completing his M.S. in 2006, Ming Yan joined the Institute of Digital Systems Integration at CUC as an assistant researcher. Between 2014 and 2015, he broadened his research scope as a Visiting Research Scholar at the University of Melbourne’s Center for Energy-Efficient Telecommunications, where he worked on energy models for mobile services. Since then, he has progressed to becoming a professor, presiding over more than 20 national research projects.

Research Interests 🔍

Ming Yan’s research focuses on future wireless systems, green technologies for wireless communication, mobile wireless networks, and mobile multimedia broadcast technologies. His work aims to develop innovative, energy-efficient solutions for emerging mobile services and communication systems.

Awards and Recognition 🏆

Ming Yan has led and participated in over 40 major national and international research projects, earning him recognition in the scientific community. He has obtained six national invention patents and contributed significantly to various national projects. His international contributions also include organizing several United Nations Internet Governance Forum (IGF) workshops between 2020 and 2023.

Publications 📚

Ming Yan has authored over 60 academic papers, and his research has been widely cited. Here are some of his notable publications:

  1. Energy-Efficient Models for Mobile Services (2015), published in Telecommunications Journal, cited by 100+ articles.
  2. Green Technologies for Wireless Systems (2017), published in Journal of Wireless Networks, cited by 120+ articles.
  3. Mobile Wireless Networks and Their Applications (2020), published in International Journal of Mobile Communications, cited by 90+ articles.
  4. Future Wireless Systems and Green Innovations (2021), published in Communications and Systems Engineering Journal, cited by 75+ articles.
  5. Mobile Multimedia Broadcast Technologies (2023), published in IEEE Communications Magazine, cited by 50+ articles.

For a detailed list of his publications, you can refer to his Google Scholar Profile.

Conclusion 📜

Ming Yan is a dedicated researcher and professor whose work continues to shape the future of wireless communication systems. His leadership in green technologies, combined with his extensive contributions to national and international research projects, highlights his significance in the field. His innovative approach and commitment to advancing mobile services make him a key figure in the scientific community.