Yan-Jiang Zhao | Robotics and Automation | Excellence in Research Award

Published on by Research Awards

Prof. Yan-Jiang Zhao | Robotics and Automation | Excellence in Research Award 

Harbin University of Science and Technology | China

Prof. Yan-Jiang Zhao is a distinguished researcher and academic leader in the field of mechanical engineering and medical robotics, currently serving as Professor and Head of the Department of Engineering Graphics at Harbin University of Science and Technology, China. With extensive international research exposure, including postdoctoral training at Thomas Jefferson University, USA, he has established a strong interdisciplinary research program that bridges mechanical engineering, robotics, and medical applications. Prof. Zhao’s primary research interests encompass medical robotics, flexible and steerable needle insertion systems, multi-fingered dexterous robotic hands, composite filament winding technologies, and TRIZ-based mechanical system innovation. His work focuses on integrating mechanics-based modeling, multimodal sensing, and intelligent control strategies to improve precision, safety, and adaptability in robotic systems, particularly for minimally invasive medical procedures. His recent research efforts include variable-curvature flexible needle insertion, multimodal perception frameworks, and advanced control methods for medical robotic platforms. Throughout his academic career, Prof. Zhao has led or participated in more than 20 competitive research projects, including eight national-level grants such as the National Natural Science Foundation of China (NSFC) General and Young Scientist Funds, alongside multiple provincial and enterprise-funded projects. These projects have resulted in the development of functional robotic prototypes, innovative mechanical designs, and industry-ready technologies. In parallel, he has completed several consultancy and industry collaborations, contributing to composite material structural component development and industrial product design optimization. Prof. Zhao has an impressive scholarly output, having published over 40 peer-reviewed journal articles, with more than 30 indexed in SCI and EI databases. His research has appeared in leading international journals including Expert Systems with Applications, IEEE Robotics and Automation Letters, IEEE Access, Medical Engineering & Physics, Physics in Medicine & Biology, and the International Journal of Medical Robotics and Computer-Assisted Surgery. According to the Web of Science Core Collection, his indexed publications have received over 90 citations, with an h-index of 6 (2025).

Citation Metrics (Scopus)

1400
1000
600
200
0

Citations
200

Documents
31

h-index
8

Citations

h-index

i10-index

View Scopus Profile

Featured Publications

 

Tingting Yu | Robotics and Automation | Research Excellence Award | 14087

Published on by Research Awards

Assoc Prof Dr. Tingting Yu | Robotics and Automation | Research Excellence Award

South China University of Technology | China

Dr. Tingting Yu is an Associate Professor at the Shien-Ming Wu School of Intelligent Engineering, South China University of Technology (SCUT), Guangzhou, China, and an emerging leader in the field of micro- and nanorobotics. She received her B.Sc. degree in Computational Physical Chemistry and M.Sc. degree in Chemical Engineering and Physical Chemistry from the Technical University of Darmstadt, Germany, followed by a Ph.D. in Physical Chemistry jointly awarded by the University of Stuttgart and the Max Planck Institute for Intelligent Systems, Germany. Her interdisciplinary academic training has enabled her to bridge fundamental physical chemistry with advanced intelligent engineering and applied robotics. Dr. Yu’s research focuses on the design, fabrication, and intelligent control of material-driven micro- and nanorobotic systems, with strong applications in biomedicine and environmental remediation. Her work integrates novel propulsion mechanisms, hybrid light-magnetic actuation, self-assembly phenomena, and AI-based control strategies to develop functional microrobots capable of targeted drug delivery, microplastic removal, and biomimetic communication. She has made significant contributions to understanding motion control, swarm behavior, and feedback-guided fabrication in microscale systems. She has served as Principal Investigator or Co-Principal Investigator on several competitive national and provincial research grants, including projects funded by the National Natural Science Foundation of China (NSFC), MOSF Key Programs, Guangdong Regional Joint Funds, and Central University Young Scientist Group initiatives. In addition, Dr. Yu has led multiple industry-collaborative projects with major organizations such as the State Grid Corporation of China and Midea Group, demonstrating the translational impact of her research. Dr. Yu holds granted patents in advanced sensing systems and rapid prototyping DLP-based 3D printing technologies, reflecting her strong innovation capacity. Her research output includes high-impact publications in leading international journals such as Materials & Design, Nanoscale, Advanced Intelligent Systems, Small, ACS Applied Materials & Interfaces, ACS Nano, Advanced Science, and IEEE Robotics and Automation Letters. Several of her works have received journal highlights, front covers, and special recognitions, underscoring their scientific significance.

Citation Metrics (Scopus)

500
400
300
200
100
50
30
10
0

Citations
295

Documents
16

h-index
10

Citations

Documents

h-index

View Scopus Profile
      View Orcid Profile

Featured Publications

Chao Wang | Computer Science and Artificial Intelligence | Research Excellence Award

Published on by Research Awards

Mr. Chao Wang | Computer Science and Artificial Intelligence | Research Excellence Award

North China University of Technology | China

Dr. Chao Wang, an accomplished Associate Professor at the North China University of Technology, is a distinguished researcher whose work significantly advances the fields of vehicular networks, IoT security, and edge computing. Holding a Ph.D. in Computer Science, Dr. Wang has developed a strong academic portfolio grounded in deep technical expertise and innovative thinking. His research addresses some of the most pressing challenges in intelligent transportation systems, focusing on secure data communication, privacy-preserving mechanisms, and efficient resource allocation in highly dynamic vehicular environments. With 23 publications in SCI and Scopus-indexed journals and conferences, his work demonstrates a consistent trajectory of high-quality scientific output. His research impact is further reflected in 660 citations, an H-index of 10, and an i10-index of 10, according to Google Scholar as of December 3, 2025. These metrics underscore his growing global influence and the relevance of his contributions to next-generation intelligent mobility systems. Dr. Wang has successfully completed and continues to lead multiple national and provincial research projects, focusing on enhancing the reliability, safety, and intelligence of connected vehicle ecosystems. His innovations include blockchain-based frameworks for secure traffic data management, anomaly detection systems for vehicle-to-vehicle communication, and privacy-preserving architectures for IoT-enabled transportation infrastructures. With four patents published or under process, he demonstrates strong translational capability, often transforming theoretical models into practical, real-world solutions. His collaborations with researchers from Springer Nature, IEEE, and various international universities highlight his interdisciplinary approach and commitment to advancing global research partnerships. Although he has not yet undertaken industry consultancy projects, Dr. Wang’s research outputs inherently serve industrial needs, especially in smart transportation, urban planning, and secure IoT deployment. He is also an active professional member of IEEE, contributing to the broader scientific community through peer review, academic exchanges, and participation in scholarly networks. Beyond research, Dr. Wang is dedicated to academic mentorship, guiding students who have achieved recognition in national-level competitions, illustrating his commitment to nurturing the next generation of innovators. With strong expertise, a solid publication record, impactful innovations, and a dedication to advancing secure and intelligent transportation systems, Dr. Wang exemplifies the qualities celebrated by the Research Excellence Award. His achievements reflect not only academic rigor but also societal relevance, making him a highly deserving nominee for this international honor.

Profile: Orcid

Featured Publications

Li, J., Wang, C., Seo, D., Cheng, X., He, Y., Sun, L., Xiao, K., & Huo, Y. (2021). Deep learning-based service scheduling mechanism for GreenRSUs in the IoVs. Wireless Communications and Mobile Computing, 2021, Article 7018486. https://doi.org/10.1155/2021/7018486

Wang, C. (2020). Destination prediction-based scheduling algorithms for message delivery in IoVs. IEEE Access, 8, 1–15. https://doi.org/10.1109/ACCESS.2020.2966494

Wang, C. (2018). A blockchain-based privacy-preserving incentive mechanism in crowdsensing applications. IEEE Access, 6, 1–12. https://doi.org/10.1109/ACCESS.2018.2805837

Wang, C. (2015). A reliable broadcast protocol in vehicular ad hoc networks. International Journal of Distributed Sensor Networks, 11(8), Article 286241. https://doi.org/10.1155/2015/286241

Wang, C. (2015). Ads dissemination in vehicular ad hoc networks. In 2015 IEEE International Conference on Communications (ICC) (pp. 1–6). IEEE. https://doi.org/10.1109/ICC.2015.7248890

Wang, C. (2014). Schedule algorithms for file transmission in vehicular ad hoc networks. In Wireless Algorithms, Systems, and Applications (pp. 135–147). Springer. https://doi.org/10.1007/978-3-319-07782-6_12

Wang, C. (2014). S-disjunct code-based MAC protocol for reliable broadcast in vehicular ad hoc networks. In 2014 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI) (pp. 1–6). IEEE. https://doi.org/10.1109/IIKI.2014.66

Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Published on by Research Awards

Prof. Dr. Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology | India

Dr. K. Ramkumar is a distinguished academician, researcher, and innovator with over twenty-three years of rich teaching and research experience in the field of Engineering and Computer Science. He is presently serving as a Professor in the Department of Computer Science and Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. His illustrious academic journey is marked by consistent dedication to research, innovation, and academic excellence. He obtained his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, in 2018, specializing in Security and Privacy in Cloud Computing, a domain of critical importance in the digital era. To further enhance his expertise and broaden his research perspectives, he pursued a Post-Doctoral Fellowship (PDF) at the Federal University of Ceará, Fortaleza, Brazil, in 2023, focusing on Artificial Intelligence and Biomedical Data Analytics. Throughout his career, Dr. Ramkumar has held several prestigious leadership positions in academia, contributing extensively to institutional growth and quality enhancement. He has served as Professor and Head of the Department (CSE) at Rajalakshmi Institute of Technology, Chennai, and earlier as Professor and Associate Dean (Engineering & Technology) at SRM University, Delhi-NCR, Sonepat, Haryana, where he also chaired the Board of Studies. His earlier academic affiliations include SRM Institute of Science and Technology (Vadapalani Campus, Chennai), Kings Engineering College, and Indira Institute of Engineering and Technology, where he also functioned as Director of Placements. His industry exposure includes working with global technology companies such as Satyam Computer Services Ltd. and LogicaCMG Pvt. Ltd. (now CGI), where he held roles as Associate Consultant, IT Consultant, and Project Leader, leading large technical teams across onshore and offshore environments. Dr. Ramkumar’s research interests encompass a broad spectrum of emerging technologies including Cloud Computing Security, Artificial Intelligence, Machine Learning, IoT Frameworks, Blockchain Systems, and Biomedical Data Analytics. His prolific research output includes numerous publications in SCI, Scopus, and Web of Science-indexed journals, with several articles published in reputed platforms such as Elsevier, Springer, Taylor & Francis, and IEEE. His recent works focus on AI-based diabetic risk prediction, intelligent human activity recognition for assistive technologies, quantum image encryption, and deep learning applications for medical imaging. According to his Google Scholar profile, Dr. Ramkumar has achieved over 1,327 citations, with an h-index of 18 and an i10-index of 24, reflecting the global impact and scholarly recognition of his research contributions. His academic influence extends beyond publications, as he has co-supervised several Post-Doctoral Fellows at the Singapore Institute of Technology, demonstrating his commitment to mentoring and nurturing emerging researchers. Dr. Ramkumar has also published and been granted multiple patents across domains such as wireless sensor networks, mobile ad hoc networks, IoT-based monitoring systems, AI-driven diagnostic tools, and environmental pollution control mechanisms, reflecting his strong inclination toward innovation-driven applied research. Dr. K. Ramkumar stands as a dynamic academic leader whose contributions bridge academia, research, and industry, exemplifying excellence in technological innovation, knowledge dissemination, and professional leadership. His remarkable blend of teaching expertise, research achievements, and administrative acumen continues to inspire students, scholars, and peers across the global academic and scientific community.

Profiles: Scopus | Google Scholar

Featured Publications

Ramkumar, K. (2022). A comparative analysis of methods of endmember selection for use in subpixel classification: A convex hull approach. Computational Intelligence and Neuroscience, 2022, Article ID 3770871

Ramkumar, K., Ananthi, N., Brabin, D. R. D., Goswami, P., Baskar, M., & Bhatia, K. K. (2021). Efficient routing mechanism for neighbour selection using fuzzy logic in wireless sensor network. Computers & Electrical Engineering, 94, 107365.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy scalar(s). The European Physical Journal Plus, 139(2), 1–29.

Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy fermion(s). Nuclear Physics B, 1000, 116488.

Ramkumar, K., Medeiros, E. P., Dong, A., de Albuquerque, V. H. C., Hassan, M. R., & Hassan, M. M. (2024). A novel deep learning framework based Swin transformer for dermal cancer cell classification. Engineering Applications of Artificial Intelligence, 133, 108097.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to any mass-dimension for non-degenerate scalars and fermions including light–heavy mixing. The European Physical Journal Plus, 139(2), 169.

 

Longxing Liao | Mechanical Engineering | Best Researcher Award | 13160

Published on by Research Awards

Dr. Longxing Liao | Mechanical Engineering | Best Researcher Award

Dr. Longxing Liao, Jimei University, China

Dr. Longxing Liao is an accomplished researcher and academic affiliated with Jimei University, China. With expertise in marine engineering and renewable energy systems, Dr. Liao focuses on innovative solutions for sustainable development in coastal and maritime environments. He has contributed to cutting-edge research in renewable energy integration, resource optimization, and advanced marine technology applications. Dr. Liao’s work aims to promote environmental sustainability and economic growth through the development of efficient energy systems and technologies, solidifying his reputation as a forward-thinking leader in his field.

Profile

Scopus

Early Academic Pursuits 🎓

Dr. Longxing Liao embarked on his academic journey with a strong passion for engineering and innovation. He obtained his Doctor of Philosophy degree, laying the groundwork for a career focused on advancing knowledge and technological progress. Early in his studies, Dr. Liao developed an interest in high-performance manufacturing processes and chemical mechanical polishing, which would later become his primary areas of research. This foundational phase of his academic career equipped him with the technical expertise and critical thinking skills necessary to excel in the competitive field of mechanical and marine engineering.

Professional Endeavors 🔧

Currently, Dr. Liao serves as a lecturer and postgraduate supervisor at the School of Marine Equipment and Mechanical Engineering at Jimei University, China. In this capacity, he has been instrumental in shaping the next generation of engineers and researchers. He is not only an educator but also a hands-on researcher who has managed several high-impact projects. Dr. Liao has successfully secured funding for research initiatives from prestigious organizations, including:

  • The National Natural Science Foundation of China
  • Provincial and Municipal Natural Science Foundations
  • The Provincial Education Department

These projects have allowed Dr. Liao to explore innovative approaches to mechanical engineering challenges, emphasizing sustainability and efficiency.

Contributions and Research Focus 🛠️

Dr. Liao’s research primarily focuses on chemical mechanical polishing and high-performance manufacturing. His work in these areas has led to the publication of over 20 SCI-indexed papers in top-tier international journals, such as Applied Surface Science and the Journal of Manufacturing Processes. These publications are widely recognized for their innovative methodologies and impactful findings, contributing significantly to the body of knowledge in manufacturing and surface science.

Additionally, Dr. Liao holds an impressive portfolio of over 20 invention patents, with many ranked in the top two positions. His patented innovations demonstrate practical applications of his research, particularly in optimizing manufacturing processes and advancing material sciences.

Accolades and Recognition 🏆

Dr. Liao’s contributions have not gone unnoticed. Among his many accolades are:

  • Second Prize of the Liaoning Provincial Patent Award in 2022 (ranked 2/6).
  • First Prize of the China Industry-University-Research Institute Collaboration Innovation Achievement Award (ranked 9/10).

Dr. Liao’s commitment to fostering talent is evident in his guidance of undergraduate teams to achieve notable success:

  • Two National Third Prizes in the China Undergraduate Mechanical Engineering Innovation and Creativity Competition.
  • One National Second Prize in the National College Students’ Social Practice and Science Contest on Energy Saving, Emission Reduction, and Environmental Protection.

Furthermore, he was personally honored with the First Prize in the 2024 Young Teachers’ Award, highlighting his dual excellence as an educator and researcher.

Publication Top Notes📝

A novel process of chemical-mechanical fluid-solid coupling polishing with high-quality and high-efficiency for turbine blisk

Author: Luo, S., Liao, L., Wang, Y.

Journal: Manufacturing Processes

Year: 2024

Structural design and hydrostatic analysis of an intelligent glass cleaning robot

Author: Wang, B., Liao, L., Zhou, M., Lin, Q., Chen, L.

Journal: The International Society for Optical Engineering, 

Year: 2024

Study on the mechanism of chemical mechanical polishing on high-quality surface of single crystal diamond

Author: Liao, L., Luo, S., Chang, X., Li, S., Shutin, D.

Journal: Manufacturing Processes

Year: 2023

Geometric design and dynamic characteristics of a novel abnormal cycloidal gear reducer

Author: Mo, J., Gong, X., Luo, S., … Chang, X., Liao, L.

Journal: Advances in Mechanical Engineering

Year: 2023,

Study on hydrodynamic lubrication and friction reduction performance of spur gear with groove texture
Author: Chang, X., Renqing, D., Liao, L., … Huang, Y., Luo, S.

Journal: Tribology International

Year:  2023

 

Carlo Alessi | Robotics and Automation | Best Researcher Award

Published on by Research Awards

Mr. Carlo Alessi | Robotics and Automation | Best Researcher Award

Ph.D. Candidate at The Bio Robotics Institute, Sant’Anna School of Advanced Studies, Italy.

Carlo Alessi is a Ph.D. candidate specializing in BioRobotics at Scuola Superiore Sant’Anna in Pisa, Italy. His research focuses on reinforcement learning for soft robot control, supported by a prestigious three-year grant under the EU project PROBOSCIS. Carlo’s academic journey includes M.Sc. and B.Sc. degrees in Computer Science from the University of Pisa, where he explored artificial intelligence and robotics through international study grants and research internships. He has contributed to notable publications and actively participates in leading conferences, showcasing his expertise in machine learning frameworks and robotics technologies. Carlo’s future endeavors include a post-doctoral position at the Italian Institute of Technology, Genova, where he will continue advancing robotic manipulation using tactile sensors in projects like ergoCub and FAIR. His interdisciplinary approach and commitment to innovation position him as a promising leader in the field of robotics and AI.

Professional Profiles:

Education 🎓

Carlo Alessi holds a Bachelor of Science degree in Computer Science with honors from the University of Pisa, Italy, complemented by an Erasmus+ Study grant at the University of Bristol. His research during this period centered on convolutional neural networks for species detection in natural images. He proceeded to earn a Master of Science in Computer Science (Artificial Intelligence) at the same institution, achieving distinction. His master’s thesis focused on modulating motor commands using FORCE-trained Spiking Neural Networks, with additional studies at the University of Barcelona and Polytechnic University of Catalonia through another Erasmus+ grant. Currently a Ph.D. candidate in BioRobotics at The BioRobotics Institute, Scuola Superiore Sant’Anna Pisa, Carlo’s research is funded by a three-year grant under the EU project PROBOSCIS, exploring Reinforcement Learning for Soft Robot Control. He actively tutors M.Sc. students and participates in leading conferences like the IEEE-RAS International Conference on Soft Robotics and Mediterranean Machine Learning Summer School.

Professional Experience

Carlo Alessi’s professional journey is marked by significant roles in cutting-edge robotics research. As a Research Assistant at The BioRobotics Institute, Scuola Superiore Sant’Anna Pisa, Italy, he developed educational tools for soft robotics control using machine learning. His Ph.D. Research Internship at Bristol Robotics Laboratory, UK, focused on reinforcement learning for soft robot control, supported by an Erasmus+ Traineeship grant. Moving forward, Carlo is poised to join the Italian Institute of Technology, Genova, Italy, as an (Incoming) Post-Doctoral Researcher in the HumanoiD Sensing and Perception Group under Dr. Lorenzo Natale. Here, he will advance his expertise in machine learning for robot manipulation using tactile sensors, contributing to projects like ergoCub and FAIR. Carlo’s career highlights his dedication to robotics and artificial intelligence, coupled with a commitment to pushing the boundaries of research in bio-robotics. His contributions in academia and industry underscore his role as a leader in the field, driving innovation and technological advancement.

Research Interest

Carlo Alessi’s research interests revolve around the intersection of robotics, artificial intelligence, and machine learning, particularly in the domain of soft robotics. His doctoral research focuses on reinforcement learning techniques for enhancing the control and adaptability of soft robotic systems. Carlo is keenly interested in applying these methodologies to improve robot manipulation and sensory perception, with a specific emphasis on tactile sensors and their integration into robotic platforms. He is also intrigued by the broader implications of his research in advancing human-robot interaction and exploring new paradigms in robotic control strategies. Carlo’s work aims to contribute significantly to the development of intelligent robotic systems capable of autonomous learning and adaptation in dynamic environments. His interdisciplinary approach combines theoretical insights with practical applications, aiming to address real-world challenges in robotics and pave the way for future innovations in bio-robotics and beyond.

Award and Honors

Carlo Alessi has earned several prestigious accolades and honors throughout his academic and professional journey. He secured a significant Ph.D. research grant to advance his studies in BioRobotics at The BioRobotics Institute, Scuola Superiore Sant’Anna Pisa, Italy, where his focus lies in reinforcement learning for enhancing soft robot control capabilities. His academic pursuits were further enriched by Erasmus+ Study Grants, facilitating enriching experiences at the University of Bristol, UK, and the University of Barcelona & Polytechnic University of Catalonia, Spain, where he explored cutting-edge applications in computer science and artificial intelligence. Carlo’s commitment to research excellence is underscored by impactful internships at institutions like Bristol Robotics Laboratory, UK, and Technical University of Munich, Germany, where he contributed to pioneering research in robotics and AI. He actively engages in the global academic community through participation in esteemed conferences such as the IEEE-RAS International Conference on Soft Robotics and the Mediterranean Machine Learning Summer School, where he shares insights and collaborates on advancing technological frontiers in his field. These honors highlight Carlo’s dedication to pushing the boundaries of robotics research and his significant contributions to the academic community.

Research Skills

Carlo Alessi possesses a strong foundation in robotics and artificial intelligence research, emphasizing expertise in reinforcement learning and machine learning frameworks such as Stable-baselines, OpenAI Gym, and PyTorch. His practical skills extend to ROS, Gazebo simulation, Arduino, and Lego Mindstorms, facilitating the development and integration of robotic systems. Proficient in C, C++, Python, and Java, Carlo applies these languages alongside Matlab, Bash scripting, and SQL for algorithm development and data analysis. He excels in experimental design, execution, and statistical analysis, pivotal for deriving insights in his research. Carlo’s ability to communicate findings effectively through publications and presentations at international conferences underscores his dedication to advancing the field, making significant contributions to robotics and AI research.

Publications

  1. Learning a Controller for Soft Robotic Arms and Testing its Generalization to New Observations, Dynamics, and Tasks
    • Authors: Alessi, C., Hauser, H., Lucantonio, A., Falotico, E.
    • Conference: 2023 IEEE International Conference on Soft Robotics, RoboSoft 2023
    • Year: 2023
    • Citations: 2
  2. Ablation Study of a Dynamic Model for a 3D-Printed Pneumatic Soft Robotic Arm
    • Authors: Alessi, C., Falotico, E., Lucantonio, A.
    • Journal: IEEE Access, 2023, 11, pp. 37840–37853
    • Year: 2023
    • Citations: 7