Jiabo Ding | Simulation | Best Researcher Award

Published on by Technology Scientists

Best Researcher Award

Jiabo Ding — Chinese Academy of Agricultural Sciences, China

Jiabo Ding
Affiliation Chinese Academy of Agricultural Sciences
Country China
Scopus ID 12804951700
Documents 133
Citations 1,086
h-index 17
Subject Area Simulation
Event Technology Scientists Awards
ORCID 0000-0002-8515-9031

Jiabo Ding is a researcher affiliated with the Chinese Academy of Agricultural Sciences whose documented scholarly work includes studies spanning animal health, infection biology, molecular profiling, and genetic manipulation. His publication record includes research employing proteomic, transcriptomic, and genetic approaches, providing an interdisciplinary basis for evaluating research activity in simulation and related computationally informed scientific domains.[1][2][3]

Abstract

Jiabo Ding, affiliated with the Chinese Academy of Agricultural Sciences, has a documented research profile encompassing animal biosafety, infectious diseases, molecular biology, proteomics, transcriptomics, and genetic manipulation. His recent publications demonstrate participation in multidisciplinary studies using contemporary experimental and analytical approaches. Research addressing feline calicivirus biomarkers, Brucella-associated immune dysregulation, and genetic manipulation of Eimeria illustrates engagement with data-intensive biological investigation. These contributions provide evidence of sustained scholarly activity and collaborative research across veterinary and biomedical science. The available publication record and reported bibliometric indicators provide a basis for recognition under a researcher-focused award framework within Technology Scientists Awards.[1][2][3]

Keywords

Jiabo Ding; Best Researcher Award; Chinese Academy of Agricultural Sciences; Simulation; animal biosafety; veterinary science; infectious disease research; proteomics; transcriptomics; genetic manipulation; Eimeria; Brucella abortus; feline calicivirus; biomedical research.

Introduction

Research in contemporary veterinary and biomedical science increasingly integrates experimental biology with computational analysis, molecular profiling, and systems-level interpretation. Jiabo Ding’s documented publications reflect this multidisciplinary environment, addressing infectious disease mechanisms, biomarkers, immune responses, and genetic technologies. These studies demonstrate collaborative engagement with complex biological questions and modern research methodologies.[1][2][3]

Research Profile

Jiabo Ding’s research profile is associated with the Chinese Academy of Agricultural Sciences and encompasses animal biosafety, veterinary infectious diseases, molecular diagnostics, and parasite biology. His recent scholarly contributions include proteomic analysis of feline calicivirus infection, single-cell transcriptomic investigation of Brucella infection, and review of genetic manipulation approaches for Eimeria, demonstrating broad biological research engagement.[1][2][3]

Research Contributions

The documented contributions associated with Jiabo Ding include participation in studies that identify molecular biomarkers, characterize infection-associated immune responses, and assess emerging genetic manipulation technologies. These works employ complementary methodologies, including serum proteomics, single-cell RNA sequencing, flow cytometry, and genetic engineering. Collectively, they contribute evidence toward improved understanding of animal pathogens and disease mechanisms.[1][2][3]

Publications

Selected publications involving Jiabo Ding demonstrate activity across molecular veterinary research and infectious disease biology. The 2026 study on feline calicivirus reported proteomic identification of candidate biomarkers, while research on Brucella abortus applied single-cell transcriptomics to characterize immune dysregulation. A 2025 iScience review examined genetic manipulation advances in the non-model protozoan Eimeria.[1][2][3]

Research Impact

The research record indicates impact through contributions to understanding pathogen biology, host responses, biomarker discovery, and genetic manipulation. The cited studies address practical scientific challenges in veterinary health and infectious disease research. Their use of molecular and single-cell methodologies supports deeper characterization of biological processes and may inform future diagnostic, therapeutic, preventive, or experimental strategies.[1][2][3]

Award Suitability

The available scholarly record supports consideration of Jiabo Ding for a Best Researcher Award based on documented publication activity, multidisciplinary research participation, and contributions to contemporary veterinary and biomedical investigation. His reported profile includes 133 documents, 1,086 citations, and an h-index of 17, while selected publications demonstrate sustained involvement in collaborative, methodologically diverse research.[1][2][3]

Conclusion

Jiabo Ding’s documented research demonstrates sustained engagement with important questions in veterinary science, infectious disease biology, molecular profiling, and genetic technologies. His participation in studies involving proteomics, single-cell transcriptomics, and Eimeria genetic manipulation illustrates methodological breadth. Together with the reported bibliometric indicators, these contributions provide a substantive scholarly basis for researcher recognition.[1][2][3]

References

  1. Xu, C., Liu, H., Gu, H., Wu, D., Tang, X., Liang, L., Hou, S., Ding, J., & Liang, R. (2026). Serum proteomic profiling identifies ACSL4 and S100A2 as novel biomarkers in feline calicivirus infection. International Journal of Molecular Sciences, 27(2), 1047.
    https://pubmed.ncbi.nlm.nih.gov/41596690/
  2. Zhang, G., Shen, Q., Ye, J., Feng, Y., Boireau, P., Fan, X., Lv, L., Li, Y., Xu, X., Cha, H., Shen, C., Zhang, Y., Peng, X., Jiang, H., & Ding, J. (2026). Single-cell transcriptome profiling reveals the immune dysregulation characteristics of mice infected with Brucella abortus. The Journal of Infectious Diseases, 233(1), e55–e66.
    https://pubmed.ncbi.nlm.nih.gov/41074555/
  3. Li, Y., Suo, J., Liang, R., Liang, L., Liu, X., Ding, J., Suo, X., & Tang, X. (2025). Genetic manipulation for the non-model protozoan Eimeria: Advancements, challenges, and future perspective. iScience, 28(3), 112060.
    https://www.sciencedirect.com/science/article/pii/S2589004225003207

Xiao Liang | Multi-Agent Control | Outstanding Scientist Award

Published on by Technology Scientists

Prof. Xiao Liang | Multi-Agent Control | Outstanding Scientist Award

Associate Dean | Shenyang Aerospace University | China

Xiao Liang is a Professor at Shenyang Aerospace University and Associate Director of the Key Laboratory of Liaoning Province. He earned his B.S. in Automation from Northeastern University, followed by an M.S. in Control Theory and Control Engineering. He received his Ph.D. in Navigation, Guidance, and Control from Beihang University. With over 30 academic papers published in leading journals and five authorized patents, Liang has significantly advanced unmanned aerial and ground vehicle (UAV/UGV) research. His international engagement includes academic exchanges at Swansea University, UK. He has led numerous prestigious projects funded by the National Natural Science Foundation of China, the Aeronautical Science Foundation, and provincial foundations. His research integrates intelligent decision-making, mission planning, and heterogeneous multi-agent collaboration. Liang’s work bridges theory and practice, addressing challenges in robotics, aerospace, and autonomous systems.

Professional Profiles

ORCID | Scopus

Education 

Xiao Liang’s academic journey demonstrates consistent excellence and commitment to automation and control engineering. He completed his undergraduate studies in Automation at Northeastern University, where he distinguished himself by being recommended for postgraduate study without entrance examinations. He pursued a Master’s degree in Control Theory and Control Engineering, which he earned. His doctoral studies at Beihang University culminated in a Ph.D. in Navigation, Guidance, and Control, specializing in autonomous systems and flight control technologies. This educational trajectory provided Liang with a robust foundation in aircraft design, control theory, and computational modeling. His exposure to both theoretical and applied dimensions of control engineering has enabled him to integrate multidisciplinary perspectives into his research. An academic exchange visit to Swansea University further enriched his international outlook. His education laid the groundwork for his leadership in UAV/UGV cooperative systems and intelligent autonomous decision-making.

Experience 

Xiao Liang is a Professor at Shenyang Aerospace University’s School of Automation, where he supervises master’s students and directs cutting-edge research. He also serves as Associate Director of the Key Laboratory of Liaoning Province. His research leadership includes hosting major projects funded by the National Natural Science Foundation of China, the Aeronautical Science Foundation of China, and multiple provincial agencies. Liang’s projects span UAV/UGV path planning, dynamic tracking, collaborative sensing, and obstacle avoidance, with applications in rescue missions and aerospace systems. He has published widely in journals such as Intelligent Service Robotics, Robotics and Autonomous Systems, and Aerospace Science and Technology. Beyond academia, his work includes five authorized patents on UAV control systems and path planning methods, underscoring his role in translating research into technological innovations. Liang’s international experience, including research exchange at Swansea University, has further shaped his multidisciplinary approach to intelligent decision-making and multi-agent collaboration.

Research Focus 

Xiao Liang’s research lies at the intersection of control theory, artificial intelligence, and aerospace systems. His primary focus is the design and optimization of heterogeneous multi-agent systems, particularly UAV/UGV collaboration in dynamic and complex environments. His contributions span navigation, guidance, and control (GNC), pursuit-evasion strategies, multi-agent decision-making, and robust target-tracking algorithms. Liang has introduced innovative approaches such as visual SLAM in dynamic environments, semantic octree mapping, and adaptive path planning methods under uncertain conditions. His work also explores mission planning under adversarial and rescue scenarios, emphasizing robustness and fault tolerance. Liang integrates hardware-software design into UAV/UGV systems, ensuring practical applicability. His pioneering contributions extend beyond aerospace into areas such as smart shopping systems for unmanned supermarkets, reflecting the adaptability of his methods. With a balance of theoretical advancement and applied innovation, his research continues to push the boundaries of intelligent multi-agent control and autonomous robotics.

Awards and Honors 

Xiao Liang has been recognized with multiple prestigious awards for his scientific and technological contributions. He received the Science and Technology Award from the Chinese Society of Astronautics, highlighting his impact in aerospace innovation. His mentorship and leadership have also led student teams to achieve top recognition: Second Prize in the 16th “Challenge Cup” National Undergraduate Academic Science and Technology Works, and First Prize in both the 13th and 14th China Graduate Electronic Design Competitions. He was selected for the Liaoning BaiQianWan Talents Program and recognized among the High-level Talents of Shenyang in the same year. His earlier contributions earned the Progress in Science and Technology Award from both Liaoning Province and Shenyang City. Collectively, these honors reflect Liang’s sustained excellence, leadership, and innovation in aerospace engineering, intelligent systems, and multi-agent control research, positioning him as a leading scientist of his generation.

Publication Top Notes

Title: Design and Development of Full Self-Service Smart Shopping System for Unmanned Supermarket
Year: 2025

Title: STSLAM: Robust Visual SLAM in Dynamic Scenes via Image Segmentation and Instance Tracking
Year: 2025

Title: Real-Time Semantic Octree Mapping under Aerial-Ground Cooperative System
Year: 2025

Title: Collaborative Pursuit-Evasion Game of Multi-UAVs Based on Apollonius Circle in the Environment with Obstacle
Year: 2023

Title: Design and Development of Ground Station for UAV/UGV Heterogeneous Collaborative System
Year: 2021

Title: Fault-Tolerant Control for the Multi-Quadrotors Cooperative Transportation under Suspension Failures
Year: 2021

Title: Target Tactical Intention Recognition in Multiaircraft Cooperative Air Combat
Year: 2021

Title: Collaborative Pursuit-Evasion Strategy of UAV/UGV Heterogeneous System in Complex Three-Dimensional Polygonal Environment
Year: 2020

Title: Moving Target Tracking Method for Unmanned Aerial Vehicle/Unmanned Ground Vehicle Heterogeneous System Based on AprilTags
Year: 2020

Title: Moving Target Tracking of UAV/UGV Heterogeneous System Based on Quick Response Code
Year: 2019

Title: Real-Time Moving Target Tracking Algorithm of UAV/UGV Heterogeneous Collaborative System in Complex Background
Year: 2019

Title: A Geometrical Path Planning Method for Unmanned Aerial Vehicle in 2D/3D Complex Environment
Year: 2018

Conclusion

Xiao Liang demonstrates a strong combination of scholarly excellence, technological innovation, and leadership in the field of unmanned systems and intelligent robotics. His contributions to UAV/UGV heterogeneous collaboration, robust control, and path planning strategies position him as a highly competitive candidate for the Research for Outstanding Scientist Award. With further efforts toward global collaboration and broader application of his research outcomes, his profile will continue to strengthen and align well with the award’s standards of excellence.