Yukun Shi | Computer Science | Best Scholar Award

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Assoc. Prof. Dr. Yukun Shi | Computer Science | Best Scholar Award

Assoc. Prof. Dr. Yukun Shi, Beijing University of Chemical Technology, China

Dr. Yukun Shi is an accomplished researcher and Associate Professor at the Department of Information Science and Technology, Beijing University of Chemical Technology. He specializes in multi-agent systems, control system network attacks, and distributed estimation. Dr. Shi earned his Ph.D. in Control Science and Engineering from Beijing University of Chemical Technology in 2022. His academic journey includes a one-year research visit to the University of Victoria, Canada, in 2021. His contributions to the field are significant, particularly in advancing secure state estimation and consensus control. He has published extensively in top-tier journals, addressing challenges in network security and distributed control. With a strong background in system modeling and cybersecurity, Dr. Shi continues to drive innovations in multi-agent collaboration and resilience against malicious attacks. His research not only contributes to theoretical advancements but also has practical implications for industrial and technological applications worldwide.

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Suitability for the Research for Best Scholar Award – Yukun Shi

Dr. Yukun Shi, an Associate Professor at the Beijing University of Chemical Technology, has demonstrated remarkable academic and research excellence in the field of control science and engineering. His expertise spans critical areas such as multi-agent systems, control system network attacks, distributed estimation, and consensus control, making his contributions highly relevant to modern automation and cybersecurity challenges. His work is particularly notable in the area of secure state estimation, where he has investigated the robustness of networked control systems against malicious sensor attacks, an emerging concern in industrial and cyber-physical systems.

Dr. Shi’s research output includes several publications in prestigious IEEE journals, such as IEEE Transactions on Automation Science and Engineering and IEEE Transactions on Control of Network Systems, highlighting his ability to contribute cutting-edge advancements in his field. His scholarly work is well-cited, reflecting both its impact and recognition within the scientific community. Additionally, his international exposure, including a research visit at the University of Victoria, Canada, underscores his global perspective and collaborative research approach.

πŸŽ“ Education 

Dr. Yukun Shi pursued his Ph.D. in Control Science and Engineering at Beijing University of Chemical Technology, graduating in 2022. His doctoral research focused on secure state estimation in multi-agent systems under adversarial conditions, bridging control theory with cybersecurity. As part of his academic development, he undertook a one-year research visit to the University of Victoria, Canada, in 2021, where he collaborated on cutting-edge projects related to network security and control systems. His education provided him with a strong foundation in distributed control, estimation algorithms, and robust filtering techniques. Throughout his studies, Dr. Shi honed his expertise in tackling cyber threats to industrial control systems, laying the groundwork for his future research in resilient multi-agent networks. His academic journey is marked by rigorous training, innovative problem-solving, and contributions to the field of control and automation engineering.

πŸ’Ό Professional Experience

Dr. Yukun Shi currently serves as an Associate Professor at the Department of Information Science and Technology, Beijing University of Chemical Technology. With a research focus on multi-agent systems, network security, and distributed estimation, he has made significant contributions to securing cyber-physical systems. His professional journey includes leading research projects on sensor attacks, consensus control, and fault-tolerant filtering in distributed networks. Dr. Shi actively collaborates with international institutions to develop advanced methodologies for improving the resilience of control systems against malicious threats. His role extends beyond research, encompassing mentorship, curriculum development, and industry partnerships. He is a sought-after speaker at academic conferences and has peer-reviewed numerous articles in high-impact journals. His dedication to cybersecurity and control engineering has positioned him as a thought leader in the field, driving innovation and practical solutions to safeguard modern industrial and technological infrastructures.

πŸ… Awards and Recognition 

Dr. Yukun Shi has received multiple accolades for his pioneering work in control systems and cybersecurity. He has been recognized for his contributions to secure multi-agent systems and networked control security. His research papers have been published in high-impact journals, earning him best paper awards at leading automation and control conferences. Dr. Shi has also been a recipient of prestigious research grants that support his work in developing robust estimation algorithms against cyber threats. His outstanding contributions have been acknowledged by industry associations, positioning him as a key figure in distributed system security. His work has not only influenced academia but also guided practical implementations in industrial automation and cybersecurity frameworks. Additionally, Dr. Shi has served as a reviewer for top-tier journals, further highlighting his expertise and influence in the scientific community. His relentless pursuit of excellence continues to shape the future of secure control systems.

🌍 Research Skills On Computer Science

Dr. Yukun Shi possesses a robust research skill set centered around multi-agent systems, control system security, and distributed estimation. His expertise includes developing secure state estimation techniques to mitigate network attacks in cyber-physical systems. He specializes in designing fault-tolerant control algorithms that enhance the resilience of distributed networks. His research also encompasses consensus control strategies to improve synchronization in multi-agent environments. Dr. Shi is proficient in advanced filtering techniques, such as Kalman filtering and observer design, to ensure accurate system monitoring despite adversarial interference. He actively applies mathematical modeling and optimization methods to enhance decision-making in complex systems. His work in secure control frameworks has broad applications in autonomous systems, industrial automation, and networked infrastructures. With a keen focus on practical implementation, Dr. Shi’s research continues to bridge theoretical advancements with real-world security challenges, contributing to the evolution of resilient cyber-physical networks.

πŸ“– Publication Top Notes

  • Title: Optimal Output-Feedback Controller Design Using Adaptive Dynamic Programming: A Permanent Magnet Synchronous Motor Application
    • Authors: Zhongyang Wang, Huiru Ye, Youqing Wang, Yukun Shi, Li Liang
    • Citation: IEEE Transactions on Circuits and Systems II: Express Briefs
    • Year: 2025
  • Title: Distributed Filter Under Homologous Sensor Attack and Its Application in GPS Meaconing Attack
    • Authors: Yukun Shi, Wenjing He, Li Liang, Youqing Wang
    • Citation: IEEE Transactions on Automation Science and Engineering
    • Year: 2024
  • Title: Event-triggered distributed secure state estimation for homologous sensor attacks
    • Authors: Yukun Shi, Haixin Ma, Jianyong Tuo, Youqing Wang
    • Citation: ISA Transactions
    • Year: 2023
  • Title: Distributed Secure State Estimation of Multi-Agent Systems Under Homologous Sensor Attacks
    • Authors: Yukun Shi, Youqing Wang, Jianyong Tuo
    • Citation: IEEE/CAA Journal of Automatica Sinica
    • Year: 2023
  • Title: Online Secure State Estimation of Multiagent Systems Using Average Consensus
    • Authors: Yukun Shi, Youqing Wang
    • Citation: IEEE Transactions on Systems, Man, and Cybernetics: Systems
    • Year: 2022
  • Title: Asymptotically Stable Filter for MVU Estimation of States and Homologous Unknown Inputs in Heterogeneous Multiagent Systems
    • Authors: Yukun Shi, Changqing Liu, Youqing Wang
    • Citation: IEEE Transactions on Automation Science and Engineering
    • Year: 2022
  • Title: Secure State Estimation of Multiagent Systems With Homologous Attacks Using Average Consensus
    • Authors: Yukun Shi, Changqing Liu, Youqing Wang
    • Citation: IEEE Transactions on Control of Network Systems
    • Year: 2021

Jordi Rodeiro | Computer Science | Best Researcher Award

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Mr. Jordi Rodeiro | Computer Science | Best Researcher Award

 πŸ‘€ Mr. Jordi Rodeiro, Institut de Recerca Sant Joan de DΓ©u, Spain

Jordi Rodeiro Boliart is an accomplished International Computer Engineering and Sports Science graduate with a Master’s in Data Science and ongoing doctoral studies in Artificial Intelligence at La Salle Bonanova, Barcelona. Jordi is a dynamic professional blending a robust academic foundation with practical expertise. He is dedicated to leveraging data science and AI in health research, particularly autism prediction. With a deep passion for problem-solving and innovation, Jordi has conducted significant work in basketball analytics, biomedical data analysis, and medical imaging. His projects have included building Python tools, web applications, and dashboards that streamline decision-making. Jordi’s multilingual fluency in Catalan, Spanish, and English (C1) and his adaptability, critical thinking, and leadership skills underscore his commitment to excellence. As a mental health researcher, programming professor, and basketball coach, Jordi excels at interdisciplinary collaboration, fostering innovation, and making meaningful contributions to both academia and real-world applications.

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🌟  Summary of Suitability for the Award

Jordi Rodeiro Boliart demonstrates an exceptional combination of academic excellence, multidisciplinary expertise, and impactful research, making him a strong candidate for the Research for Best Researcher Award. His academic journey spans multiple disciplines, including International Computer Engineering, Sports Science, and Data Science, culminating in a PhD in Artificial Intelligence and Autism Prediction. His diverse background equips him with a unique perspective in integrating technology, data science, and health research to address complex societal challenges.

Jordi’s research outputs reflect significant contributions to both applied and theoretical domains. Notably, his final master’s thesis focused on analyzing basketball data to enhance coaching strategies, while his degree project in the biomedical field led to a published scientific paper.

πŸŽ“ Education

Jordi Rodeiro Boliart boasts an impressive academic journey beginning with a dual degree in International Computer Engineering (La Salle, UPC) and Sports Science (INEFC Barcelona, UB). He further honed his expertise with a Master’s in Data Science (La Salle Bonanova, Barcelona), culminating in award-winning academic recognition. Currently pursuing a Ph.D. in Artificial Intelligence with a focus on autism prediction, Jordi demonstrates a commitment to cutting-edge research. His educational highlights include a final master’s thesis analyzing basketball data to enhance coaching strategies and a degree project in metabolomics published in a peer-reviewed journal. Jordi has also contributed to projects in medical imaging, such as using x-rays for illness detection. His academic journey is enriched by attending technology seminars at globally renowned institutions like Harvard and MIT, along with specialized training in leadership and organizational behavior. Jordi’s blend of technical and interdisciplinary studies defines his innovative, research-oriented career trajectory.

πŸ’Ό   Professional Experience

Jordi Rodeiro Boliart has a versatile professional background spanning research, teaching, and leadership. As a mental health researcher at Parc Sanitari Sant Joan de DΓ©u, Jordi applies statistics and data science to critical health data, contributing to global assemblies and conferences. He serves as a university professor at La Salle Barcelona, teaching programming, mathematics, and IT software. As a data science intern at Sener, Jordi specialized in Power BI dashboards and analyzing corporate metrics. His engineering research internship included creating biomedical tools for metabolomic analysis, leading to a published paper. Jordi’s sports background complements his tech expertise, with roles as a basketball coach and coordinator, focusing on player development and team strategy. His earlier internships at Alfred Smart Systems and other engineering roles solidified his Python and gateway programming skills. Jordi’s diverse experiences exemplify his ability to integrate technology, data science, and education for impactful contributions.

πŸ…Awards and Recognitions

Jordi Rodeiro Boliart’s contributions have been widely recognized through various awards and honors. He received the prestigious Malaspina Award as part of the Empower consortium in 2023 and was a HackB finalist in the same year. Jordi was acknowledged with an academic excellence certificate for the best master’s record in Data Science (2023) and emerged as the LS Future Lab – Impact Challenge Hackathon winner in 2022. He represented his university as a National Model United Nations delegate in New York (2022) and participated in an international cooperation project in PerΓΊ. Jordi’s outstanding research on metabolomics earned him the opportunity to present at the Metabolomics 2022 conference. Beyond academia, Jordi is a certified Level II basketball coach, an FCBQ leadership trainee, and a master-certified Gannon Baker basketball coach. These accolades reflect his exceptional abilities in technical innovation, leadership, and interdisciplinary collaboration.

🌍  Research Skills On Computer Science

Jordi Rodeiro Boliart excels in applying advanced research methodologies to interdisciplinary challenges. His expertise includes data science, artificial intelligence, and object-oriented programming. Jordi has developed sophisticated tools for biomedical research, basketball analytics, and mental health studies. His doctoral research focuses on autism prediction through AI, combining statistical analysis and data visualization techniques. Jordi’s proficiency spans Python, MATLAB, MySQL, and Power BI, with skills in machine learning and medical image processing. He has designed Python programs to predict basketball outcomes, web apps for metabolomics, and diagnostic tools for x-rays. Jordi’s critical thinking, decision-making, and integrity define his research approach. His ability to present findings, such as at the Metabolomics 2022 conference, underscores his communication and analytical skills. Jordi’s research bridges academia and practical applications, demonstrating a commitment to addressing complex problems in health and technology.

πŸ“– Publication Top Notes

1. The longitudinal relationship among physical activity, loneliness, and mental health in middle-aged and older adults: Results from the Edad con Salud cohort
  • Authors: Jordi Rodeiro, Beatriz Olaya, Josep Maria Haro, Aina Gabarrell-Pascuet, JosΓ© Luis Ayuso-Mateos, Lea Francia, Cristina RodrΓ­guez-Prada, Blanca Dolz-del-Castellar, Joan DomΓ¨nech-Abella
  • Year: 2024
  • Citation: DOI: 10.1016/j.mhpa.2024.100667
2. The association of material deprivation with major depressive disorder and the role of loneliness and social support: A cross-sectional study
  • Authors: Joan DomΓ¨nech-Abella, Carles Muntaner, Jordi Rodeiro, Aina Gabarrell-Pascuet, Josep Maria Haro, JosΓ© Luis Ayuso-Mateos, Marta Miret, Beatriz Olaya
  • Year: 2024
  • Citation: DOI: 10.1016/j.jad.2024.09.071
3. Feasibility of an occupational e-mental health intervention for enhancing workplace mental health (EMPOWER RCT): Effectiveness and lessons learned (Preprint)
  • Authors: Carlota de Miquel, Christina M. Van der Feltz-Cornelis, Leona Hakkaart-van Roijen, Dorota Merecz-Kot, Marjo Sinokki, Jordi Rodeiro, Jennifer Sweetman, Kaja Staszewska, Ellen Vorstenbosch, Daniele Porricelli et al.
  • Year: 2024
  • Citation: DOI: 10.2196/preprints.66041
4. Trends of use of drugs with suggested shortages and their alternatives across 52 real-world data sources and 18 countries in Europe and North America
  • Authors: Marta Pineda-MoncusΓ­, Alexandros Rekkas, Álvaro MartΓ­nez PΓ©rez, Angela Leis, Carlos Lopez Gomez, Eric Fey, Erwin Bruninx, Filip MaljkoviΔ‡, Francisco SΓ‘nchez-SΓ‘ez, Jordi Rodeiro et al.
  • Year: 2024
  • Citation: DOI: 10.1101/2024.08.28.24312695
5. CloMet: A Novel Open-Source and Modular Software Platform That Connects Established Metabolomics Repositories and Data Analysis Resources
  • Authors: Jordi Rodeiro, Ester VidaΓ±a-Vila, Joan Navarro, Roger Mallol
  • Year: 2023

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Chang Gao | Engineering | Best Researcher Award

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Mrs. Chang Gao | Engineering | Best Researcher Award

πŸ‘€ Mrs. Chang Gao, Changsha University of Science and Technology, China

Chang Gao is an accomplished researcher and educator based in China, specializing in civil engineering and material sciences. With a strong academic foundation, he obtained his Bachelor’s degree in Civil Engineering from Hunan University and further advanced his expertise with a Ph.D. in Civil Engineering from the same institution. His innovative research spans high-performance concrete materials, eco-friendly construction methods, and machine learning applications in engineering. Currently, Chang serves as an Assistant Professor in the Intelligent Construction Department at Changsha University of Science and Technology while also pursuing postdoctoral research at Southeast University and Hunan University. His exceptional contributions to academia and industry have been recognized through prestigious awards, including the Third Prize of the Science and Technology Award by the China Circular Economy Association. Chang’s dedication to sustainable practices and cutting-edge research underscores his impact on the field of engineering.

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🌟 Summary of Suitability for the β€œResearch for Best Researcher Award”

Dr. Chang Gao’s impressive academic and professional accomplishments establish him as a strong candidate for the β€œResearch for Best Researcher Award.” His expertise lies in Civil Engineering, with a particular focus on innovative and eco-friendly concrete materials, shrinkage and creep behavior, and machine learning applications in construction materials. His contributions are evident through his impactful research, as highlighted in numerous peer-reviewed publications in reputable journals such as the Journal of Building Engineering, Construction and Building Materials, and the Journal of Materials Research and Technology.

Dr. Gao’s multidisciplinary approach, blending traditional civil engineering with advanced technologies like machine learning, sets him apart as a forward-thinking researcher. His work on recycled aggregate concrete and nanoparticles demonstrates a commitment to sustainable engineering solutions, addressing critical global challenges like resource efficiency and environmental impact.

πŸŽ“ Education

Chang Gao has a robust educational background in civil engineering, beginning with a Bachelor’s degree from Hunan University in 2014. Demonstrating exceptional academic performance, he pursued a Ph.D. in Civil Engineering at the same university, graduating in 2019. During his Ph.D. journey, Chang’s research focused on eco-friendly construction materials and the integration of machine learning in structural analysis. To broaden his expertise, he completed another doctoral program in Aeronautics and Astronautics Engineering at Purdue University in 2019, showcasing his interdisciplinary capabilities. This diverse academic experience not only honed his technical skills but also instilled a profound understanding of sustainable and advanced construction practices. With a passion for innovation and academic excellence, Chang has built a solid foundation to lead pioneering research and mentor the next generation of engineers.

πŸ’Ό  Professional Experience

Chang Gao’s professional journey reflects his dedication to advancing engineering practices. Since September 2022, he has served as an Assistant Professor in the Intelligent Construction Department of Civil Engineering at Changsha University of Science and Technology, where he actively contributes to academia through teaching and research. Simultaneously, Chang is a postdoctoral researcher at Southeast University, specializing in high-performance concrete materials, shrinkage and creep analysis, and the application of machine learning in construction engineering. Previously, he conducted postdoctoral research at Hunan University from December 2019 to September 2022, focusing on eco-friendly concrete and composite material improvements. Chang’s professional accomplishments are underpinned by his innovative approach, collaborative mindset, and dedication to sustainable construction solutions. His extensive experience bridges academia and industry, making him a prominent figure in civil engineering.

πŸ… Awards and Recognitions

Chang Gao’s exemplary contributions to engineering have earned him multiple accolades. He was honored with the Third Prize in the Science and Technology Award from the China Circular Economy Association, recognizing his innovative research in sustainable materials. Additionally, he received funding from the Youth Program of the National Natural Science Foundation of China (Grant No. 52308233, 2023) and the Youth Program of the Hunan Province Natural Science Foundation of China (Grant No. 2022JJ40062, 2022). These awards highlight Chang’s commitment to advancing eco-friendly construction practices and integrating cutting-edge technologies into civil engineering. His achievements underscore his leadership and innovation in the field, inspiring peers and students alike to pursue excellence in engineering research and sustainable development.

🌍  Research Skills On Engineering

Chang Gao possesses advanced research skills in civil engineering and materials science, with a focus on sustainable and high-performance construction materials. His expertise includes the development of eco-friendly concrete materials, composite improvements, and shrinkage and creep analysis. He is proficient in leveraging machine learning techniques to evaluate the mechanical properties and performance of recycled aggregate concrete, demonstrating his ability to integrate technology into engineering research. Chang’s work also explores nanotechnology applications in material modification, further enhancing the durability and efficiency of construction materials. His interdisciplinary approach combines practical problem-solving with theoretical rigor, enabling him to produce innovative solutions for modern engineering challenges. Chang’s research skills are complemented by his strong analytical capabilities and collaborative mindset, making him a leader in advancing sustainable construction practices.

πŸ“– Publication Top Notes

  • Simulation and numerical analysis of the seismic performance of the quick repaired seismic-damaged RC frame
    • Authors: Chang Gao, Liang Huang, Lei Wang, Qiang Sun, Yin Li
    • Journal: Soil Dynamics and Earthquake Engineering
    • Year: 2025
    • DOI: 10.1016/j.soildyn.2024.109083
  • Creep behavior evaluation of recycled aggregate concrete using machine learning technology
    • Authors: Chang Gao, Chuyu Luo, Bin Zhang, Zhangli Hu, Jinhui Tang, Lei Wang, Jiaping Liu
    • Journal: Journal of Building Engineering
    • Year: 2024
    • DOI: 10.1016/j.jobe.2024.111538
  • Axial compressive behavior of steel reinforced GGBS-RFBP-FA ternary composite geopolymer recycled fireclay brick aggregates concrete columns
    • Authors: Yin Li, Liang Huang, Chang Gao, Yiqun Qu, Xiaofeng Luo, Bodong Lv, Zhijun Chen
    • Journal: Structures
    • Year: 2024
    • DOI: 10.1016/j.istruc.2024.105913
  • Workability and mechanical properties of GGBS-RFBP-FA ternary composite geopolymer concrete with recycled aggregates containing recycled fireclay brick aggregates
    • Authors: Yin Li, Liang Huang, Chang Gao, Zhijie Mao, Mingzhu Qin
    • Journal: Construction and Building Materials
    • Year: 2023
    • DOI: 10.1016/j.conbuildmat.2023.131450
  • Jute Fiber-Reinforced Polymer Tube-Confined Sisal Fiber-Reinforced Recycled Aggregate Concrete Waste
    • Authors: Chang Gao, Qiu Ni Fu, Liang Huang, Libo Yan, Guangming Gu
    • Journal: Polymers
    • Year: 2022
    • DOI: 10.3390/polym14061260
  • Compressive performance of fiber reinforced polymer encased recycled concrete with nanoparticles
    • Authors: Chang Gao, Liang Huang, Libo Yan, Bohumil Kasal, Wengui Li, Ruoyu Jin, Yutong Wang, Yin Li, Peng Deng
    • Journal: Journal of Materials Research and Technology
    • Year: 2021
    • DOI: 10.1016/j.jmrt.2021.07.159
  • Flax FRP tube and steel spiral dual-confined recycled aggregate concrete: Experimental and analytical studies
    • Authors: Liang Huang, Jinmei Liang, Chang Gao, Libo Yan
    • Journal: Construction and Building Materials
    • Year: 2021
    • DOI: 10.1016/j.conbuildmat.2021.124023
  • Mechanical properties of recycled aggregate concrete modified by nano-particles
    • Authors: Chang Gao, Liang Huang, Libo Yan, Ruoyu Jin, Haoze Chen
    • Journal: Construction and Building Materials
    • Year: 2020
    • DOI: 10.1016/j.conbuildmat.2020.118030
  • Strength and ductility improvement of recycled aggregate concrete by polyester FRP-PVC tube confinement
    • Authors: Chang Gao, Liang Huang, Libo Yan, Ruoyu Jin, Bohumil Kasal
    • Journal: Composites Part B: Engineering
    • Year: 2019
    • DOI: 10.1016/j.compositesb.2018.10.102
  • Experimental and numerical studies of CFRP tube and steel spiral dual-confined concrete composite columns under axial impact loading
    • Authors: Liang Huang, Chang Gao, Libo Yan, Tao Yu, Bohumil Kasal
    • Journal: Composites Part B: Engineering
    • Year: 2018
    • DOI: 10.1016/j.compositesb.2018.07.008