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.

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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.

Hiyam Farhat | Digital twins | Best Researcher Award

Dr. Hiyam Farhat | Digital twins | Best Researcher Award

Lecturer | Tennessee Tech University | United States

Dr. Hiyam Farhat, a Lecturer and Assistant Director at the DOE Industrial Assessment Center in the Department of Mechanical and Nuclear Engineering at Tennessee Technological University, is a materials and mechanical engineering specialist whose work integrates advanced materials, manufacturing technologies, turbomachinery performance, and energy-efficiency research. She holds a PhD in Mechanical and Industrial Engineering, an MS in Mechanical and Materials Engineering, and a BS in Mechanical Engineering, underpinning a career that spans academic, research, and leadership roles across major engineering organizations. Her professional experience includes directing industrial assessment initiatives, managing engineering programs in the turbomachinery sector, contributing to quality and inspection systems, and teaching a broad range of engineering courses with demonstrated excellence. Her research focuses on AI-driven modeling, digital-twin development, materials degradation prediction, and clean-energy technologies, resulting in influential publications in areas such as hybrid digital-twin frameworks, gas turbine performance, flexible operation lifing criteria, and energy-storage applications. She has delivered invited presentations and contributed chapters to leading technical references, with her work supported by collaborations with national and international partners. Her recognitions include awards for technical presentations, and she maintains active engagement through memberships in professional societies such as ASME, KEEN, and the European Turbine Network. She also holds certifications in research ethics, nondestructive testing, welding inspection, quality auditing, and safety oversight. Dr. Farhat’s record reflects sustained innovation, cross-disciplinary expertise, and impactful contributions to advancing energy sustainability and intelligent engineering systems.

Profiles: Google Scholar | Scopus

Featured Publications

1. Farhat, H., & Salvini, C. (2022). Novel gas turbine challenges to support the clean energy transition. Energies, 15(15), 5474.

2. Farhat, H. (2021). Operation, maintenance, and repair of land-based gas turbines.

3. Farhat, H. (2021). Materials and coating technologies. In Operation, maintenance, and repair of land-based gas turbines (pp. 63–87).

4. Farhat, H., & Salvini, C. (2022). New lifing criterion for land-based gas turbines in flexible operation mode. Energy Reports, 8, 379–385.

5. Farhat, H. (2021). Lifetime extension: Assessment and considerations. In Operation, maintenance, and repair of land-based gas turbines (pp. 175–196).

Dr. Hiyam Farhat’s work advances intelligent energy systems by integrating AI-driven modeling, digital-twin technologies, and materials degradation analytics to enhance performance, reliability, and sustainability in turbomachinery and clean-energy applications. Her contributions support industry and national energy goals by improving efficiency, reducing emissions, and enabling data-informed lifecycle management for next-generation power systems.

Sayyid Ali Banihashemi | Engineering | Editorial Board Member

Assist. Prof. Dr. Sayyid Ali Banihashemi | Engineering | Editorial Board Member

Faculty Member | Payame Noor University | Iran

Assist. Prof. Dr. Sayyid Ali Banihashemi, Associate Professor in the Department of Industrial Engineering at Payame Noor University, is a recognized scholar specializing in project scheduling, data envelopment analysis, supply chain management, and organizational agility. He holds advanced degrees in industrial engineering with a concentration in operations research and performance evaluation, complemented by rigorous training in quantitative decision-making. His professional experience includes leading academic programs, supervising research initiatives, and contributing to major analytical and optimization projects that support organizational and operational improvement. Dr. Banihashemi’s research portfolio encompasses influential publications, high-impact citations, and methodological advancements that have shaped contemporary practices in project planning efficiency, productivity assessment, and supply chain performance. His scholarly contributions are further reflected in editorial responsibilities for reputable journals, memberships in distinguished professional societies, and certifications in advanced analytical methods. Widely cited and respected in his field, he has earned multiple recognitions for research excellence, academic service, and contributions to the industrial engineering community, establishing him as a dedicated leader committed to advancing theory and practice in operations and performance management.

Profiles: Google Scholar

Featured Publications

1. Dahmardeh, N., & Banihashemi, S. A. (2010). Organizational agility and agile manufacturing. European Journal of Economics, Finance and Administrative Sciences, 27, 178–184.

2. Banihashemi, S. A. (2011). The role of communication to improve organizational process. European Journal of Humanities and Social Sciences, 1(1), 13–24.

3. Banihashemi, S. A., Khalilzadeh, M., Shahraki, A., Malkhalifeh, M. R. M., & others. (2020). Optimization of environmental impacts of construction projects: A time–cost–quality trade-off approach. International Journal of Environmental Science and Technology, 1–16.

4. Banihashemi, S. A., & Khalilzadeh, M. (2021). Time-cost-quality–environmental impact trade-off resource-constrained project scheduling problem with DEA approach. Engineering, Construction and Architectural Management, 28(7), 1979–2004.

5. Banihashemi, S. A., Khalilzadeh, M., Antucheviciene, J., & Edalatpanah, S. A. (2023). Identifying and prioritizing the challenges and obstacles of green supply chain management in the construction industry using the fuzzy BWM method. Buildings, 13(1), 38.

Dr. Sayyid Ali Banihashemi’s work advances scientific and industrial practice by integrating optimization, sustainability, and performance evaluation to improve project delivery and supply chain systems. His research supports data-driven decision-making that enhances organizational efficiency, reduces environmental impacts, and strengthens the resilience and agility of modern industries.

Akbar Hojjati Najafabadi | Engineering | Best Industrial Research Award

Dr. Akbar Hojjati Najafabadi | Engineering | Best Industrial Research Award

Faculty at Islamic Azad University Mobarakeh Branch, Iran

Dr. Akbar Hojjati Najafabadi is a distinguished researcher in mechanical engineering with expertise in manufacturing, production, hydraulics, pneumatics, robotics, and assistive technology. His research focuses on the design and development of orthotic and rehabilitation devices for individuals with spinal cord injuries and locomotion disabilities, bridging engineering innovation with healthcare needs. He has contributed significantly to industrial research through academic publications in international journals, authored and translated technical books, and supervised projects that integrate mechanical systems with biomedical applications. Beyond academia, he has executed impactful industrial projects, including the design and installation of specialized machinery in major steel industries, showcasing his ability to translate theory into practice. As a lecturer and research leader, he has guided advanced engineering initiatives and mentored students while promoting applied industrial solutions. Recognized for his pioneering contributions, Dr. Hojjati’s work demonstrates a balance of academic rigor, industrial innovation, and social impact, positioning him as a strong industrial researcher.

Professional Profile 

Google Scholar | Scopus Profile | ORCID Profile 

Education

Dr. Akbar Hojjati Najafabadi holds a strong academic foundation in mechanical engineering, specializing in manufacturing and production. He earned his Ph.D. in Mechanical Engineering from Kashan University, where his doctoral research focused on advanced manufacturing and production processes with applications in assistive technologies. Prior to that, he completed his master’s degree at Iran University of Science and Technology, gaining expertise in industrial systems and applied mechanical design. His undergraduate studies were carried out at Islamic Azad University in Najafabad, providing him with the essential grounding in mechanical and production engineering. He also broadened his international research exposure through a visiting research position at the Friedrich Wilhelm Bessel Institut in Germany. This combination of domestic and international education has allowed him to integrate theoretical knowledge with practical innovation, preparing him to tackle complex industrial and biomedical engineering challenges. His academic journey reflects a continuous pursuit of applied, impactful research.

Experience

Dr. Hojjati has built a distinguished career in both academia and industry, serving as a lecturer in mechanical engineering at Islamic Azad University, Mobarakeh Branch, for over two decades. His teaching portfolio includes advanced hydraulics, robotics, industrial measurements, machining, and materials strength, equipping future engineers with cutting-edge knowledge. Beyond teaching, he has taken leadership roles such as group manager of the mechanical engineering department and head of the Advanced Engineering Research Center, where he spearheaded innovative industrial research projects. His applied expertise extends to significant industrial collaborations, including the design, development, and installation of specialized machinery for large-scale steel industries. He has also implemented research-based prototypes such as robotic orthoses, pneumatic muscle-driven devices, and CNC-based robotic systems. This combination of academic leadership, practical industrial implementation, and applied research highlights his commitment to bridging the gap between education, industry, and innovation. His experience exemplifies a balance of teaching, research, and industrial application.

Research Focus

Dr. Hojjati’s research primarily centers on the integration of mechanical engineering with assistive and rehabilitation technologies. His work emphasizes the design and development of orthotic systems, exoskeletons, and assistive devices aimed at improving mobility for individuals with spinal cord injuries and lower-limb disabilities. He has investigated mechanical and motor-driven systems for sit-to-stand transitions, gait improvement, and locomotion rehabilitation, with several prototypes demonstrating practical benefits in healthcare applications. His studies also extend to robotics, hydraulics, and pneumatics, with innovative applications of fluidic muscles and electromechanical drives in rehabilitation devices. In addition to biomedical engineering, he has explored industrial automation, machining performance, and intelligent monitoring systems for robotics. His extensive publication record in international journals, along with ongoing research into exoskeleton technologies, reflects his commitment to applied, impactful innovations. Overall, his research focus merges industrial engineering expertise with biomedical solutions, showcasing his dedication to developing technologies that improve human life and industrial practices.

Award and Honor

Dr. Hojjati has been recognized for his pioneering contributions to industrial and applied research with distinctions that reflect both academic and practical excellence. He was honored as a Pioneer Investigator by Islamic Azad University, highlighting his leadership in advancing engineering education and research. His inventive spirit is demonstrated by his patented Surface Quick Modeling Machine, certified by the General Bureau of Industrial Possessions and Corporations Records, marking a significant contribution to industrial innovation. Alongside this, his published works in highly regarded international journals and conference presentations have further solidified his standing as a recognized researcher in mechanical and biomedical engineering fields. His authored and translated books on pneumatics, robotics, mechatronics, and industrial systems showcase his commitment to knowledge dissemination and professional development. These awards and honors underscore his role as a respected academic and industrial innovator, reflecting a career dedicated to advancing engineering solutions with real-world impact.

Publications Top Notes

  • Title: Mechanical design and simulation of a saddle-assistive device for sit-to-stand transfer in healthy subjects
    Authors: A Hojjati Najafabadi, S Amini, F Farahmand
    Year: 2017
    Citations: 8

  • Title: The effect of saddle-assistive device on improving the gait parameters of patients with the lower limbs weakness: a pilot study
    Authors: A Hojjati Najafabadi, S Amini, F Farahmand
    Year: 2020
    Citations: 2

  • Title: Machining performance on AISI 304 steel in the milling machine with mechanical and hydraulic spindle
    Authors: M Shirazi, A Hojjati Najafabadi, S Amini
    Year: 2024
    Citations: 1

  • Title: Using a saddle-assistive device equipped with mechanical orthosis for walking of the person with incomplete spinal cord injury
    Authors: A Hojjati Najafabadi, S Amini, F Farahmand
    Year: 2021
    Citations: 1

  • Title: Improving sit-to-stand transition by the saddle-assistive device in the spinal cord injury: A case study
    Authors: A Hojjati Najafabadi, S Amini, F Farahmand
    Year: 2021
    Citations: 1

  • Title: Novel design and comprehensive mechanical analysis of a cost-effective manual patient lifting system with worm gear mechanism
    Authors: A Hojjati Najafabadi, M Ahmadi Bani
    Year: 2025

  • Title: Innovative Enhancements in Surface Quality and Hardness of Aluminium Alloy 2024 through an Optimized Burnishing Process
    Authors: AH Najafabadi
    Year: 2024

  • Title: Development of the Burnishing Process: Moving Towards Increasing the Quality and Surface Hardness of Aluminum alloy 2024
    Authors: AH Najafabadi
    Year: 2023

  • Title: Comparison of anterior and posterior wheeled walkers based on body weight support in improving gait function a subjects with spinal cord injury: A case study
    Authors: AH Najafabadi, MA Bani, V Pourmoghadam
    Year: 2022

  • Title: Design of patient lifting device based on the use of a worm gears mechanism in the protection of the caregiver
    Authors: AH Najafabadi
    Year: 2022

  • Title: Rapid welding of aluminum for marking on hot steel
    Authors: HB Soroush Baladi, Akbar Hojjati Najafabadi, Mohammad Reza Khanzadeh
    Year: 2022

Conclusion

Dr. Akbar Hojjati Najafabadi’s publication record reflects a strong and consistent focus on applied industrial and biomedical engineering research. His contributions span from early work in assistive device design to recent advancements in machining processes, patient lifting systems, and rehabilitation technologies. The research demonstrates both technical depth and practical application, particularly in developing innovative solutions for spinal cord injury rehabilitation and industrial manufacturing improvements. While some of his works have already gained citations and recognition in reputable journals, others represent emerging areas with potential for broader impact. The combination of interdisciplinary research, industrial collaboration, and continuous innovation positions him as a significant contributor to industrial research. His work not only advances scientific knowledge but also provides tangible benefits to healthcare and industry, reinforcing his suitability for recognition such as the Best Industrial Research Award.

Xiaoxu Liu | Engineering | Best Researcher Award

Dr. Xiaoxu Liu | Engineering | Best Researcher Award

Associate Professor at Shenzhen Technology University, China

Dr. Xiaoxu Liu is an accomplished Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. He holds a Ph.D. in Electrical Engineering from the University of Northumbria and specializes in robust fault diagnosis, fault-tolerant control, stochastic systems, and multi-agent systems. Dr. Liu has published extensively in top-tier journals such as IEEE Transactions on Industrial Electronics and Automatica, and has served as Associate Editor for IEEE Transactions on Industrial Informatics. He has led multiple nationally funded research projects, securing over 3 million RMB in grants. His work integrates control theory with data-driven methods, addressing challenges in cyber-physical systems. Recognized as a Shenzhen Overseas High-level Talent, he has received numerous awards for research excellence and student mentorship. With international research experience and significant editorial contributions, Dr. Liu is a prominent figure in intelligent systems and control, demonstrating both academic leadership and impactful research contributions.

Professional Profile 

Scopus Profile

Education

Dr. Xiaoxu Liu possesses a strong and progressive academic background in engineering and applied mathematics. He earned his Ph.D. in Electrical Engineering from the University of Northumbria in the UK (2014–2018), where he specialized in fault-tolerant control systems and robust estimation. Prior to this, he completed a Master’s degree in Operations Research and Cybernetics at Northeastern University (2012–2014), and a Bachelor’s degree in Information and Computing Science at the same university (2008–2012). His educational path reflects a solid foundation in both theoretical and applied aspects of control systems, cybernetics, and intelligent systems. This combination of mathematical rigor and engineering application has laid the groundwork for his interdisciplinary research approach. His international academic journey has also helped him build a global perspective and a collaborative mindset, both of which have been instrumental in his subsequent professional and research achievements.

Professional Experience

Dr. Xiaoxu Liu has built an impressive academic and research career marked by rapid progression and leadership. Since December 2021, he has served as an Associate Professor at the Sino-German College of Intelligent Manufacturing, Shenzhen Technology University. Before that, he was an Assistant Professor at the same institution from 2018 to 2021. He also held research and teaching positions internationally, including as a Research Associate at the Faculty of Mathematics, City University of Hong Kong, and as a Lecturer at the University of Northumbria. Throughout these roles, Dr. Liu has led cutting-edge research projects, mentored students, and contributed to institutional development. He has acted as the principal investigator for numerous funded research programs, reflecting his capacity to lead independently and strategically. His experience demonstrates not only academic proficiency but also a sustained commitment to advancing intelligent systems research and fostering interdisciplinary collaboration in both teaching and applied engineering contexts.

Research Interest

Dr. Xiaoxu Liu’s research spans several high-impact areas within intelligent systems and control engineering. His primary interests include robust fault diagnosis, fault-tolerant control, stochastic nonlinear systems, and multi-agent systems. He also ocuses on cyber-physical systems and data-driven control, areas highly relevant to Industry 4.0 and autonomous system applications. Dr. Liu’s work often combines theoretical rigor with practical relevance, leveraging modern tools like deep reinforcement learning and Takagi-Sugeno fuzzy models to address real-world challenges such as actuator faults in UAVs or wind turbine resilience. His interdisciplinary approach blends classical control theory with artificial intelligence, enhancing system adaptability and reliability. His research outputs—published in top-tier journals like IEEE Transactions on Industrial Electronics—demonstrate not only novelty but also applicability to emerging technologies. Dr. Liu’s ability to connect robust theory with practical implementations positions him as a thought leader in intelligent manufacturing and autonomous system control.

ward and Honor

Dr. Xiaoxu Liu has received multiple awards that recognize his research excellence, academic leadership, and contributions to engineering education. He was honored as a Shenzhen Overseas High-level Talent in 2019, highlighting his strategic value to China’s academic and technological development. He has earned several Best Paper and Best Presentation Awards from prestigious conferences and journals, such as the IEEE Industrial Electronics Society and Processes. Dr. Liu also received the IEEE IES Student Paper Travel Award and various recognitions for his mentorship of student teams who achieved national-level prizes in robotics and circuit design competitions. These accolades underscore both the quality and impact of his scholarly work and his dedication to student development. His involvement as an Associate Editor for IEEE Transactions on Industrial Informatics and reviewer for top IEEE journals further validates his status as a trusted expert in his field. These honors collectively reflect his rising prominence in the global research community.

Conclusion

In summary, Dr. Xiaoxu Liu stands out as a highly capable and accomplished researcher in the field of intelligent control systems. With a solid educational foundation, diverse professional experience across top institutions, and a research portfolio that blends theoretical innovation with real-world application, he exemplifies academic excellence. His focus on robust fault diagnosis, resilient control systems, and data-driven approaches addresses some of the most pressing challenges in cyber-physical systems and smart manufacturing. Recognized nationally and internationally through numerous awards, editorial roles, and funded projects, Dr. Liu has established himself as a leader in his domain. He continues to advance the field through impactful publications, student mentorship, and collaborative projects. His trajectory reflects not only technical expertise but also a broader commitment to scientific progress and educational excellence. As such, Dr. Liu is highly deserving of recognition through accolades such as the Best Researcher Award.

Publications Top Notes

  • Title: Joint Observer Based Fault Tolerant Control for Discrete-Time Takagi-Sugeno Fuzzy Systems With Immeasurable Premise Variables

    • Authors: Xiaoxu Liu, Risheng Li, Zhiwei Gao, Bowen Li, Tan Zhang

    • Year: 2025

  • Title: Multiagent Formation Control and Dynamic Obstacle Avoidance Based on Deep Reinforcement Learning

    • Authors: Zike Yuan, Chenhao Yao, Xiaoxu Liu, Zhiwei Gao, Wenwei Zhang

    • Year: 2025

  • Title: Fault Estimation for Cyber–Physical Systems with Intermittent Measurement Transmissions via a Hybrid Observer Approach

    • Authors: Jingjing Yan, Chao Deng, Weiwei Che, Xiaoxu Liu

    • Year: 2024

    • Citations: 5

  • Title: Reinforcement Learning-Based Fault-Tolerant Control for Quadrotor UAVs Under Actuator Fault

    • Authors: Xiaoxu Liu, Zike Yuan, Zhiwei Gao, Wenwei Zhang

    • Year: 2024

    • Citations: 12

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 

Google Scholar
Scopus Profile
ORCID Profile

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

Štefan Ondočko | Engineering | Best Researcher Award

Assist. Prof. Dr. Štefan Ondočko | Engineering | Best Researcher Award

Assistant professors, Technical University of Košice, Slovakia

Profile

Scopus

Ing. Štefan Ondočko, PhD, is an Assistant Professor at the Technical University of Košice, specializing in mechanical engineering with a focus on production systems and robotics. His extensive experience spans both academia and industry, contributing to the advancement of robotic technologies.

Education 🎓

Štefan earned his degree in Mechanical Engineering from the Technical University of Košice (1996–2004), specializing in Instrumentation, Control, and Automation Technology. He later completed his PhD in Mechanical Engineering, focusing on Production Technology, in 2023.

Experience 💼

His professional journey includes roles as an Electrical Designer and I&C Engineer at EnergoControl s.r.o and SMZ Jelšava a.s., along with significant teaching responsibilities at the Technical University of Košice since 2019. Štefan currently focuses on applied research and development in robotic and production technologies.

Research Interests 🔬

Štefan’s research interests lie in the integration of robotics in production systems, particularly in modular robotics and automation technology. He actively engages in grant projects that advance educational tools and methodologies in these fields.

Awards 🏆

In 2023, Štefan received a diploma for the Best Contribution at the 20th International Scientific Conference of Engineering Doctorates of Technical Universities, highlighting his impactful work in mechanical engineering.

Publications Top Notes 📚

  1. Measurement of Maximum Deviation from Roundness Based on the Inverse Kinematics Principle
    Link – 2019, Measurement Science Review, Year 19, Nr. 6.
  2. Inverse Kinematics Data Adaptation to Non-Standard Modular Robotic Arm Consisting of Unique Rotational Modules
    Link – 2021, Applied Sciences, Year 11, Nr. 3.
  3. Comparison of Selected Numerical Methods for the Calculation of Inverse Kinematics of Nonstandard Modular Robotic Arm Consisting of Unique Rotational Modules
    Link – 2021, MM Science Journal, June.
  4. Mapping Robot Singularities Through the Monte Carlo Method
    Link – 2022, Applied Sciences, Year 12, Nr. 16.
  5. Analysis of the Methodology for Experimental Measuring of the Performance Criteria of the Laser-Using Collaborative Robot’s Path Accuracy
    Link – 2024, Applied Sciences, Year 14, Nr. 4.