Jingang Yi | Robotics | Best Researcher Award

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Best Researcher Award

Jingang Yi

 Rutgers, The State University of New Jersey, United States

Jingang Yi
Affiliation Rutgers, The State University of New Jersey
Country United States
Scopus ID 57337494500
Documents 334
Citations 6,234
h-index 42
Subject Area Robotics
Event Research Awards and Recognitions
ORCID 0000-0003-0628-9098
Google Scholar lE68S9wAAAAJ

Jingang Yi is a robotics researcher, educator, and academic leader whose work spans autonomous robotic systems, mechatronics, automation science, dynamic systems, intelligent transportation technologies, and human–robot interaction. His scholarly contributions have influenced research in robot dynamics and control, autonomous vehicles, machine learning-enabled control systems, precision automation, and intelligent infrastructure applications. His academic profile reflects extensive publication activity, sustained citation impact, international professional recognition, and leadership within major engineering societies.[1][2]

Abstract

This article summarizes the academic achievements, research activities, publication record, and professional leadership of Jingang Yi. His research portfolio encompasses robotics, mechatronics, autonomous systems, nonlinear control, automation science, and intelligent transportation technologies. Through interdisciplinary collaborations and sustained scholarly productivity, he has contributed to both theoretical developments and practical engineering applications across multiple domains of robotics and automation.[1][2]

Keywords

Robotics, Autonomous Systems, Mechatronics, Dynamic Systems, Control Engineering, Human–Robot Interaction, Automation Science, Intelligent Transportation Systems, Machine Learning Control, Precision Automation.

Introduction

Jingang Yi serves as Professor in the Department of Mechanical and Aerospace Engineering at Rutgers University and directs the Robotics, Automation, and Mechatronics (RAM) Laboratory. His educational background includes degrees from Zhejiang University, Tsinghua University, and the University of California, Berkeley, where he completed doctoral studies in Mechanical Engineering and graduate studies in Mathematics. His research has addressed challenges in autonomous robots, mechatronic systems, adaptive control, intelligent automation, infrastructure robotics, and robotic mobility systems.[1]

Research Profile

Professor Jingang Yi’s research activities integrate engineering theory with practical robotic applications. His work spans autonomous vehicles, physical human–robot interaction, robotic control architectures, machine learning-enabled control methods, automation systems, infrastructure inspection technologies, precision agriculture, and intelligent manufacturing platforms. These efforts have contributed to the advancement of reliable and adaptive robotic systems for real-world deployment.[1]

  • Autonomous robots and robotic mobility systems.
  • Human–robot interaction and assistive robotics.
  • Robot dynamics, estimation, and control.
  • Machine learning-based control methodologies.
  • Automation for civil infrastructure and construction.
  • Precision agriculture and intelligent transportation systems.

Research Contributions

His scholarly contributions include influential work on mobile robot kinematics, state estimation, mechatronic actuation systems, robotic locomotion, exoskeleton technologies, adaptive control systems, and intelligent automation. His research has been disseminated through peer-reviewed journals, international conferences, and collaborative engineering projects that bridge theory and industrial practice.[3][4][5]

  • Development of kinematic modeling and estimation approaches for skid-steered robotic vehicles.
  • Advanced hysteresis compensation methods for piezoelectric actuators.
  • Research contributions to lightweight robotic exoskeleton actuation systems.
  • Leadership in robotics, automation science, and mechatronics communities.
  • Promotion of interdisciplinary research across academia and industry.

Publications

Jingang Yi’s most influential publications include pioneering studies on skid-steered mobile robot kinematics, piezoelectric actuator hysteresis compensation, and lightweight robotic exoskeleton actuation. These works have received substantial scholarly recognition and contributed to advances in robotics, mechatronics, motion estimation, and human-assistive systems.

Among his most cited publications are studies on mobile robot modeling, mechatronic control systems, and robotic exoskeleton technologies. These works have received substantial scholarly attention and continue to be referenced within robotics and automation literature.[3][4][5]

  1. Kinematic Modeling and Analysis of Skid-Steered Mobile Robots with Applications to Low-Cost IMU-Based Motion Estimation (2009).
  2. Disturbance-Observer-Based Hysteresis Compensation for Piezoelectric Actuators (2009).
  3. Quasi-Direct Drive Actuation for a Lightweight Hip Exoskeleton with High Backdrivability and High Bandwidth (2020).

Research Impact

Jingang Yi’s scholarly impact is reflected through his Google Scholar metrics, including 8,595 citations, 372 publications, and an h-index of 48. These indicators demonstrate extensive dissemination of his research contributions and sustained recognition within the international robotics, automation, and mechatronics research communities.[2]

The research profile of Jingang Yi demonstrates broad international visibility through publications, citations, editorial service, professional society leadership, and academic mentorship. His work has supported developments in robotics, automation, intelligent transportation systems, and mechatronics while influencing both scholarly research and engineering practice. His service as editor, conference organizer, and committee member further reflects substantial contributions to the global engineering community.[1][2]

Award Suitability

Jingang Yi’s academic record aligns strongly with the evaluation criteria commonly associated with major research recognition programs. Factors supporting award suitability include sustained publication productivity, demonstrated citation impact, leadership of funded research programs, influential scholarly contributions, distinguished professional service, international fellow recognitions, and successful mentorship of graduate researchers. His career reflects long-term commitment to advancing robotics and automation science through research, education, and professional engagement.[1][2]

Conclusion

Jingang Yi has established a distinguished academic profile through extensive research contributions in robotics, automation, mechatronics, and control systems. His scholarly publications, leadership positions, editorial responsibilities, educational activities, and professional recognitions collectively demonstrate a significant and sustained contribution to engineering research. These accomplishments provide a strong foundation for consideration within research recognition and academic award programs.[1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Jingang Yi, Author ID 57337494500. Scopus. https://www.scopus.com/pages/authors/57337494500
  2. Google Scholar. (n.d.). Jingang Yi Scholar Profile. https://scholar.google.com/citations?user=lE68S9wAAAAJ&hl=en&oi=sra
  3. Yi, J., Wang, H., Zhang, J., Song, D., Jayasuriya, S., & Liu, J. (2009). Kinematic Modeling and Analysis of Skid-Steered Mobile Robots with Applications to Low-Cost Inertial-Measurement-Unit-Based Motion Estimation. IEEE Transactions on Robotics, 25(5), 1087–1097. DOI: https://doi.org/10.1109/TRO.2009.2026506
  4. Yi, J., Chang, S., & Shen, Y. (2009). Disturbance-Observer-Based Hysteresis Compensation for Piezoelectric Actuators. IEEE/ASME Transactions on Mechatronics, 14(4), 456–464. DOI: https://doi.org/10.1109/TMECH.2009.2023986
  5. Yu, S., Huang, T.H., Yang, X., Jiao, C., Yang, J., Chen, Y., Yi, J., & Su, H. (2020). Quasi-Direct Drive Actuation for a Lightweight Hip Exoskeleton with High Backdrivability and High Bandwidth. IEEE/ASME Transactions on Mechatronics, 25(4), 1794–1802. DOI: https://doi.org/10.48550/arXiv.2004.00467

Qingbing Chang | Robotics | Research Excellence Award

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Assoc. Prof. Dr. Qingbing Chang | Robotics | Research Excellence Award

Assoc. Prof. Dr. Qingbing Chang | Robotics | Associate Professor at Northeast Forestry University | China

Assoc. Prof. Dr. Qingbing Chang is an accomplished researcher whose academic journey reflects deep expertise in piezoelectric actuation, micro–nano positioning, advanced robotics, and precision mechatronic engineering, supported by a strong record of scholarly excellence and international collaboration. With a solid educational foundation culminating in a doctoral degree in mechanical and mechatronic systems from a leading research-focused university, Assoc. Prof. Dr. Qingbing Chang has built a distinguished career through progressive academic appointments, interdisciplinary laboratory leadership, and contributions to high-impact collaborative research teams working across robotics, optical systems, and cross-scale actuation technologies. His professional experience spans advanced design of multi-degree-of-freedom piezoelectric devices, robotic micromanipulation platforms, micro–nano motion control systems, actuator modeling, and precision instrument calibration, allowing Him to contribute both theoretical advancements and engineering innovations to the global research community. His research interests include cross-scale robotic actuation, stick–slip mechanisms, inertial actuation, multi-DOF piezoelectric structures, biologically assisted puncture robotics, optical alignment systems, and intelligent robotic mechanisms, with a consistent focus on improving stiffness, decoupling performance, load capacity, velocity, and accuracy across micro-to-macro motion manipulation platforms. Assoc. Prof. Dr. Qingbing Chang’s research skills encompass system modeling, structural optimization, experimental validation, optical and mechanical integration, microfabrication concepts, and high-precision measurement techniques, enabling Him to produce impactful results published in internationally indexed journals. He has contributed to widely cited works in IEEE Transactions on Industrial Electronics, IEEE Transactions on Robotics, IEEE/ASME Transactions on Mechatronics, Mechanical Systems and Signal Processing, Smart Materials and Structures, and other leading Scopus-indexed engineering journals. His achievements have earned Him academic honors, recognition for innovative piezoelectric actuator development, and respect within research communities through active participation in scholarly networks and contributions to multi-institutional projects. With more than five hundred citations, consistent publication impact, and ongoing collaborations with esteemed researchers from major robotics laboratories, Assoc. Prof. Dr. Qingbing Chang continues to advance the field through high-quality scholarship and engineering innovation. His future trajectory remains strongly oriented toward developing next-generation micro–nano robotic devices, intelligent sensing-actuation platforms, and cross-disciplinary robotic systems that integrate precision engineering, materials science, and artificial intelligence, positioning Him as an influential contributor to future breakthroughs in advanced mechatronic and robotic technologies.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Piezo robotic hand for motion manipulation from micro to macro. (2023). Citation Count: 118.

  2. Design of a precise linear-rotary positioning stage for optical focusing based on the stick-slip mechanism. (2022). Citation Count: 62.

  3. Development of a novel two-DOF piezo-driven fast steering mirror with high stiffness and good decoupling characteristic. (2021). Citation Count: 60.

  4. A simplified inchworm rotary piezoelectric actuator inspired by finger twist: design, modeling, and experimental evaluation. (2023). Citation Count: 55.

  5. Development of a low capacitance two-axis piezoelectric tilting mirror used for optical assisted micromanipulation. (2021). Citation Count: 49.

 

Guoli Song | Robotics | Research Excellence Award

Published on by Awards and Recognitions

Prof. Guoli Song | Robotics | Research Excellence Award

Prof. Guoli Song | Robotics | Researcher at Shenyang Institute of Automation Chinese Academy of Sciences | China

Prof. Guoli Song is an accomplished researcher known for his extensive contributions to medical image analysis, biomedical signal processing, robotics-assisted diagnostics, and intelligent healthcare systems, emerging as a leading figure in the integration of artificial intelligence with modern medical technologies. Prof. Guoli Song completed his higher education at the Shenyang Institution of Automation, Chinese Academy of Sciences, where he earned his doctoral degree with a research focus on computational imaging, intelligent robotics, and medical data interpretation, building a strong academic foundation that continues to support his multidisciplinary scholarship. Over the course of his professional career, he has served in prominent research roles within the Chinese Academy of Sciences, where he has participated in several high-impact international projects involving automated disease detection, AI-based brain tumor segmentation, noninvasive biosensing technologies, and robotic navigation systems for clinical applications. His research interests span medical image registration, deep learning–based diagnosis, biomedical signal processing, optimization frameworks, force-sensing technologies, and computational neuroscience, demonstrating a broad intellectual range supported by strong analytical and technical skills. Prof. Guoli Song is highly proficient in designing advanced machine-learning algorithms, developing intelligent diagnostic pipelines, implementing robotics control architectures, and conducting large-scale computational experiments, which have led to publications in IEEE platforms, Scopus-indexed journals, and other reputable venues with a citation impact exceeding several hundreds. His work has earned recognition through academic honors, research excellence acknowledgments, and invitations to contribute to international collaborations, conferences, and journal review boards. He is actively engaged in professional communities and holds affiliations with respected organizations such as IEEE and ACM, reflecting his commitment to maintaining global research standards and fostering scientific knowledge exchange. Notably, his awards and honors stem from his contributions to intelligent medical systems, advanced diagnostic models, and cross-disciplinary engineering innovations. With a strong record of publications, including influential works on medical image segmentation, biosensing devices, gaze estimation for surgical robots, and hybrid feature-based diagnostic frameworks, Prof. Guoli Song continues to advance cutting-edge methodologies that shape the future of automated healthcare. His continued efforts toward developing efficient, accurate, and clinically relevant technologies highlight his ongoing potential for leadership and innovation. Prof. Guoli Song’s accomplishments, research influence, and future-oriented vision firmly establish him as a leading contributor to global scientific advancement and position him for sustained excellence in medical engineering and computational health research.

Academic Profile: Scopus | Google Scholar

Featured Publications:

  1. Song, G., Han, J., Zhao, Y., Wang, Z., & Du, H. (2017). A review on medical image registration as an optimization problem. 119 citations.

  2. Hao, Z., Luo, Y., Huang, C., Wang, Z., Song, G., Pan, Y., et al. (2021). An intelligent graphene-based biosensing device for cytokine storm syndrome biomarkers detection in human biofluids. 92 citations.

  3. Huang, Z., Zhao, Y., Liu, Y., & Song, G. (2021). GCAUNet: A group cross-channel attention residual UNet for slice-based brain tumor segmentation. 88 citations.

  4. Song, G., Huang, Z., Zhao, Y., Zhao, X., Liu, Y., Bao, M., et al. (2019). A noninvasive system for the automatic detection of gliomas based on hybrid features and PSO-KSVM. 54 citations.

  5. Deng, Y., Yang, T., Dai, S., & Song, G. (2020). A miniature triaxial fiber optic force sensor for flexible ureteroscopy. 50 citations.