Dr. Xiaojuan Pang | Technologies | Best Researcher Award

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Dr. Xiaojuan Pang | Technologies | Best Researcher Award

lecturer, China University of Mining and Technology, China

Dr. Xiaojuan Pang is a dynamic Chinese computational chemist and academic serving as a Lecturer at the China University of Mining & Technology (CUMT) since 2019. With deep expertise in photochemistry, nonadiabatic dynamics, and photocatalytic hydrogen production, she bridges theoretical innovation and practical application. Her international research exposure includes a pivotal joint doctoral training at the Technical University of Munich under Prof. Wolfgang Domcke, positioning her as a global voice in computational reaction mechanism studies. 🌍

Publication Profile

ORCID

🎓 Education Background

Dr. Pang earned her Bachelor’s degree in Physics from Xinzhou Teachers University in 2013 🎓. She continued her academic journey with a Doctorate in Physics from Xi’an Jiaotong University (2013–2019), where she explored ultrafast photochemical mechanisms. Her international academic footprint includes a prestigious year (2017–2018) at the Technical University of Munich. She is currently undertaking a postdoctoral fellowship (since 2025) in a two-station program, co-hosted by CUMT and Zhejiang Changshan Textile Co., Ltd., further sharpening her cross-disciplinary skills in mining and material science. 📘🧪

👩‍🏫 Professional Experience

Dr. Pang began her academic career as a Lecturer in the Department of Physics at CUMT in 2019. She plays a vital role in teaching, curriculum reform, and scientific mentorship. Her involvement spans several cutting-edge research projects, including multiple national and provincial grants where she serves as Principal Investigator. She also collaborates with industrial partners to apply her research in real-world contexts, especially in energy materials and ultrafast dynamics. 🏫🧑‍🔬

🏅 Awards and Honors

Dr. Pang has garnered numerous accolades for her academic and teaching excellence. Highlights include the Outstanding Young Core Faculty Award (2024), Jiangsu “Double-Innovation Doctor” Talent Award (2020), and multiple teaching competition prizes. She has also been recognized as an Outstanding Communist Party Member, Outstanding Head Teacher, and earned three consecutive years of top annual performance ratings from 2020 to 2023. 🏆🎖️

🔍 Research Focus

Her core research explores the reaction mechanisms in photocatalytic water splitting, photoisomerization of molecular motors, and ultrafast nonadiabatic photochemical processes. Dr. Pang utilizes a powerful combination of computational tools—like Gaussian, Turbomole, and MNDO—to simulate and analyze excited-state dynamics. Her work significantly contributes to the development of efficient solar-to-hydrogen energy conversion technologies and light-driven molecular machines. 💡⚛️

🧩 Conclusion

With an impressive blend of academic rigor, international exposure, innovative research, and award-winning teaching, Dr. Xiaojuan Pang stands as a rising star in computational chemistry and photophysics. Her ongoing work at the intersection of theory and application is paving the way for advances in sustainable energy and smart molecular systems. 🚀

📚 Top Publications

Nonadiabatic Surface Hopping Dynamics of Photo-catalytic Water Splitting Process with Heptazine–(H2O)4 Chromophore
🔹Cited by: [Articles on MDPI and Google Scholar]

Study on the Photoinduced Isomerization Mechanism of Hydrazone Derivatives Molecular Switch
🔹Cited by: [Relevant studies in ACS database]

Effect of Load-Resisting Force on Photoisomerization Mechanism of a Single Second Generation Light-Driven Molecular Rotary Motor
🔹Cited by: [AIP citations and Scholar references]

Ultrafast Nonadiabatic Photoisomerization Dynamics Study of Molecular Motor Based on Indanylidene Frameworks
🔹Cited by: [CrossRef, ScienceDirect]

Photoinduced Electron-Driven Proton Transfer from Water to N-Heterocyclic Chromophore
🔹Cited by: 40+ citations (Google Scholar, Scopus)

Watching the Dark State in Ultrafast Nonadiabatic Photoisomerization of Light-Driven Motor
🔹Cited by: 70+ citations (ResearchGate, Google Scholar)

Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

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Prof. Dr. YiSheng Huang | Computer Science | Best Researcher Award

Professor, National Ilan University/EE, Taiwan

Dr. Yi-Sheng Huang is a distinguished Professor at National Ilan University, Taiwan, with a remarkable career in Electrical and Electronic Engineering. Holding a Ph.D. from National Taiwan University of Science and Technology (NTUST), he has significantly contributed to Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). Recognized among the World’s Top 2% Scientists (1960–2023), his expertise spans both theoretical advancements and real-world applications, shaping the future of smart mobility and automation. With leadership roles in academia and international collaborations, Dr. Huang continues to drive impactful research and innovation in the field of intelligent systems. 🚀

Publication Profile

📚 Academic Background

Dr. Yi-Sheng Huang earned his Ph.D. in Electrical Engineering from NTUST in 2001, laying the foundation for his expertise in dynamic systems and intelligent transportation. His commitment to academic excellence led him to various leadership positions, including Chairman of the Department of Electrical Engineering at National Ilan University (2015–2019) and Dean of the Office of Research and Development (2023–2024). He also enriched his global academic experience as a Visiting Professor at the New Jersey Institute of Technology (2008, 2014), fostering cross-border collaborations in intelligent automation. 🎓

🏢 Professional Experience

With over two decades of academic and research contributions, Dr. Huang has completed 30 major research projects and collaborated with industry leaders such as CECI Engineering Consultants, INC., Taiwan. His consultancy work spans 6 completed and 7 ongoing industry projects, demonstrating his ability to bridge theoretical research with practical applications. He is an esteemed member of the IEEE SMC Society and IEEE ITS Society, further solidifying his influence in cutting-edge technological advancements. His extensive publication record includes 114 journal papers indexed in Scopus and SCI, reflecting his commitment to advancing the field of intelligent systems. ⚡

🏆 Awards and Honors

Dr. Huang’s research excellence has earned him a place among the World’s Top 2% Scientists (1960–2023), highlighting his profound impact on electrical engineering and intelligent systems. His work has significantly influenced transportation optimization, making urban mobility smarter and more efficient. As a leading researcher, he continues to push the boundaries of Discrete Event Dynamic Systems and Petri Nets applications, setting new standards in system modeling and control. His contributions have been acknowledged globally, reinforcing his reputation as a pioneering scientist in his field. 🏅

🔬 Research Focus

Dr. Huang’s research revolves around Discrete Event Dynamic Systems, Petri Nets, and Intelligent Transportation Systems (ITS). His work has led to advanced methodologies in traffic flow management, congestion control, and system optimization, improving urban transport networks. By integrating theoretical models with real-world applications, he has contributed to automated decision-making frameworks, enhancing efficiency and sustainability in transportation. His research is instrumental in shaping smart cities and next-generation mobility solutions, fostering safer and more efficient transport ecosystems worldwide. 🚦

🔍 Conclusion

Dr. Yi-Sheng Huang stands at the forefront of intelligent transportation research, driving significant innovations in automation and dynamic systems. His global academic presence, extensive research contributions, and impactful industry collaborations establish him as a leading figure in electrical engineering and intelligent mobility solutions. With a legacy of over 114 publications, numerous research projects, and an enduring influence in academia, Dr. Huang continues to shape the future of intelligent transportation and automated systems. 🌍🚀

📝 Top Publications

A Petri net-based model for real-time traffic control in urban networks.

Optimization of discrete event systems using hybrid Petri nets.

Modeling and performance analysis of ITS using dynamic Petri nets.

Smart transportation planning with discrete event system simulation.

Enhancing automated transport systems using intelligent Petri nets.

 

Hsing-Chung Chen | Blockchain Technology | Best Researcher Award

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Prof. Dr. Hsing-Chung Chen | Blockchain Technology | Best Researcher Award

Distinguished Professor, Asia University, Taiwan

Prof. Hsing-Chung Chen is a Distinguished Full Professor at the Department of Computer Science and Information Engineering, Asia University, Taiwan. He holds a Ph.D. in Electronic Engineering from National Chung Cheng University, Taiwan (2007). A Senior Member of IEEE, he is recognized for his outstanding contributions to Information Security, Blockchain Technology, Internet of Things, Artificial Intelligence, and Cryptography. He has served in numerous academic and leadership roles, including Director of the Information Security Research Center at Asia University. Prof. Chen has been recognized on the “World Ranking of Top 2% Scientists” by Stanford University for four consecutive years (2021-2024). Additionally, he has been awarded the Best Paper and Best Post Publication awards and has published 80 journal papers, 6 patents (including 2 US Patents), and over 130 conference papers.

Publication Profile

ORCID

Education 🎓

Prof. Hsing-Chung Chen received his Ph.D. in Electronic Engineering from National Chung Cheng University, Taiwan, in 2007, laying the foundation for his extensive career in information security, blockchain, and related fields.

Experience 🧑‍🏫

Prof. Chen began his academic career as an Assistant Professor at Asia University, Taiwan, in 2008, advancing to Associate Professor and Full Professor until he was named Distinguished Full Professor in 2019. He has held various leadership positions, including Chairman of the Department of Computer Science and Information Engineering at Asia University and Research Consultant at China Medical University Hospital. He has been a key figure in organizing major conferences and workshops and serving on editorial boards for prestigious international journals.

Research Interests 🔍

His research interests are wide-ranging and include Information and Communication Security, Software Supply Chain, Blockchain Technology, Internet of Things (IoT), Mobile Networks, Medical Signal Image Processing, AI & Soft Computing, and Applied Cryptography.

Awards 🏆

Prof. Chen has received numerous prestigious awards, including the Best Paper Awards at BWCCA 2016, MobiSec 2017, and BWCCA 2018, as well as the Best Journal Paper Award from AACT. He has also been honored with multiple recognitions, such as the ACM ICFET 2020 Best Paper Presentation Award and the TANET 2018 Best Post Publication Award.

Publications 📚

“A Blockchain-Based IoT Security Architecture for Digital Healthcare”
Published in IEEE Access (2023)
Link to Publication
Cited by: 50+

“Secure Mobile and Wireless Network Protocols”
Published in Journal of Internet Services and Information Security (2022)
Link to Publication
Cited by: 30+

“AI-Driven Cryptographic Techniques for Smart Healthcare Systems”
Published in IEEE Transactions on Industrial Informatics (2021)
Link to Publication
Cited by: 75+

“Data Security in IoT Networks: A Blockchain Approach”
Published in International Journal of Engineering and Industries (2020)
Link to Publication
Cited by: 45+

“Mobile and Wireless Network Security: Challenges and Solutions”
Published in Journal of Advanced Transportation (2019)
Link to Publication
Cited by: 60+

 

Isabel de la Torre | Computer Science | Women Researcher Award

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Prof Dr. Isabel de la Torre | Computer Science | Women Researcher Award

Catedrática, Universidad de Valladolid, Spain

Isabel de la Torre Díez, born in 1979 in Zamora, Spain, is a renowned Full Professor at the University of Valladolid. She received her M.S. and Ph.D. degrees in Telecommunication Engineering from the same university in 2003 and 2010, respectively. Isabel’s expertise lies in telemedicine, e-health, m-health, and related fields. She has authored over 250 papers and played a significant role in numerous research projects. Isabel leads the GTe Research Group and is a key figure in the field of telemedicine and e-health. 🌐👩‍🏫

Publication Profile

 

Strengths for the Award

  1. Significant Research Contributions: Isabel de la Torre Díez has published over 250 papers in SCI journals, peer-reviewed conferences, and books. This extensive publication record highlights her impactful research in telemedicine, e-health, and related fields.
  2. Leadership and Innovation: She leads the GTe Research Group at the University of Valladolid and has been involved in creating and coordinating innovative software. Her leadership in advancing telemedicine and e-health applications demonstrates her commitment to improving healthcare through technology.
  3. Research Impact and Recognition: She has been involved in over 100 international conference program committees and has participated in numerous funded research projects. Her involvement as a reviewer for well-known SCI journals further underscores her expertise and influence in her field.
  4. Research and Teaching Excellence: With two research sexenios, she has demonstrated consistent research excellence. Her role in guiding doctoral theses and her contributions to high-impact journals and conferences reflect her high standing in the academic community.
  5. International Collaboration: Her postdoctoral research experiences in Portugal, Spain, and France highlight her international collaboration and mobility, enhancing her global research network and exposure.

Areas for Improvement

  1. Broader Recognition: While her research is extensive, further highlighting any awards or recognitions she has received could strengthen her application. Emphasizing awards or honors related to her research could enhance her candidacy.
  2. Diversity of Research Interests: While her focus is on telemedicine and e-health, demonstrating how her research contributes to a broader range of applications or interdisciplinary areas might strengthen her profile.
  3. Detailed Impact Metrics: Providing specific metrics, such as citation counts, h-index, and impact factors of the journals where she has published, could offer a clearer picture of her research impact.

Conclusion

Isabel de la Torre Díez is a highly qualified candidate for the Research for Women Researcher Award. Her extensive research contributions, leadership in innovative projects, and active participation in international research communities position her as a leading figure in her field. Enhancing her application with additional recognitions and detailed impact metrics could further bolster her candidacy. Overall, her achievements and ongoing contributions to the field of telemedicine and e-health make her a strong contender for the award.

Education 🎓

Isabel de la Torre Díez earned her M.S. and Ph.D. degrees in Telecommunication Engineering from the University of Valladolid, Spain, in 2003 and 2010, respectively. Her education laid a strong foundation for her prolific career in telemedicine and e-health. 🏫📜

Experience 👩‍💼

Isabel de la Torre Díez is a Full Professor in the Department of Signal Theory and Communications and Telematics Engineering at the University of Valladolid. She has authored over 250 papers and coauthored 16 registered innovative software. Isabel has been involved in more than 100 international conference program committees and has participated in 44 funded research projects. She is also a reviewer for renowned journals like the International Journal of Medical Informatics. 🏫📚

Research Focus 🔬

Isabel’s research focuses on the development and evaluation of telemedicine applications, e-health, m-health, EHRs (Electronic Health Records), machine and deep learning, privacy and security, biosensors, QoS (Quality of Service), and QoE (Quality of Experience) in the health field. She has significantly contributed to these areas, particularly in telepsychiatry, teleophthalmology, and telecardiology. 🧠💻

Awards and Honors 🏆

Isabel de la Torre Díez has received numerous accolades throughout her career. She has two research sexenios and coordinates the GTe Research Group and the GIR “Society of Information” group. She has also been recognized for her contributions as a reviewer for prestigious journals and her leadership in various research projects and collaborations. 🌟🏅

Publications 📄

  1. Novel model to authenticate role-based medical users for blockchain-based IoMT devices
    PLOS ONE
    2024-07-10
    DOI: 10.1371/journal.pone.0304774
  2. A Digital Mental Health Approach for Supporting Suicide Prevention: A Qualitative Study
    International Journal of Mental Health and Addiction
    2024-06-21
    DOI: 10.1007/s11469-024-01347-4
  3. A deep learning approach for Named Entity Recognition in Urdu language
    PLoS ONE
    2024
    DOI: 10.1371/journal.pone.0300725
    Cited by 1 article
  4. A Detectability Analysis of Retinitis Pigmentosa Using Novel SE-ResNet Based Deep Learning Model and Color Fundus Images
    IEEE Access
    2024
    DOI: 10.1109/ACCESS.2024.3367977
    Cited by 1 article

 

HaiTian Chen | Computer Science | Best Researcher Award

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Ms. HaiTian Chen | Computer Science | Best Researcher Award

College of Science, North China University of Science and Technology, China

Chen HaiTian is a dedicated researcher in the field of Cyberspace Security from China. Born in December 1998, Chen has made significant strides in federated learning, privacy preservation, and cybersecurity. His contributions span multiple peer-reviewed journals and patents, showcasing his commitment to advancing technology and safeguarding digital spaces.

Profile

ORCID

 

Education

Chen HaiTian holds a major in Cyberspace Security, demonstrating his expertise and focus in this critical area of study. His academic background has equipped him with the skills and knowledge necessary to tackle complex cybersecurity challenges and contribute to innovative solutions in the field. 🎓

Research Interests

Chen HaiTian’s research interests focus on federated learning, privacy preservation, and cybersecurity. He is particularly interested in developing robust aggregation techniques to defend against poisoning attacks in federated learning and exploring personalized fair split learning for resource-constrained Internet of Things (IoT). 🔍

Awards

Chen HaiTian has received recognition for his contributions to software development, including the Huali Academy Backstage Management System V1.0 and the DC Early Warning System V1.0. His work has been registered with computer software registration numbers, showcasing his achievements in developing innovative solutions for network management and security. 🏆

Publications

Chen, H.; Chen, X.; Peng, L. (2023). FLRAM: Robust Aggregation Technique for Defense Against Byzantine Poisoning Attacks in Federated Learning. Electronics. Cited by Electronics.

Chen, H.; Chen, X.; Peng, L. (2024). Personalized Fair Split Learning for Resource-Constrained Internet of Things. Sensors, 24, 88. Cited by Sensors.

Chen, H., Chen, X., Ma R., et al. (2024). A federated learning privacy preserving approach for remote sensing data. Computer Applications. Cited by Computer Applications.

Chen, H., Chen, X. (2023). A Robust Aggregation Technique for Poisoning Attack Defense in Federated Learning. Cited by Journal.

Xu C., Zhang S., Chen H., et al. (2024). A federated learning approach based on adaptive differential privacy and customer selection optimization. Computer Applications. Cited by Computer Applications.

Peng L., Zhang S., Chen H., et al. (2023). Clustered federated learning based on improved CFSFDP algorithm. Journal of North China University of Science and Technology (Natural Science Edition). Cited by NCUST.

Qiang Li | Computer Science | Best Researcher Award

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Mr. Qiang Li | Computer Science | Best Researcher Award

Lecturer, Qingdao University, China

Dr. Li Qiang is an experienced lecturer in computer science with a PhD in Engineering. He specializes in high-performance computing and has a strong background in both teaching and research. Committed to fostering academic excellence and technological innovation, Dr. Li has been a dedicated educator and researcher at Qingdao University since 2015.

Profile

ORCID

 

Education 🎓

PhD in Engineering: University of the Chinese Academy of Sciences, Computer Network Information Center (2010-2014), Advisor: Lu Zhonghua. Master’s in Information Science and Engineering: Shandong University of Science and Technology (2007-2010), Advisor: Zhao Maoxian. Bachelor’s in Education: Qingdao University (2003-2007).

Experience 👨‍🏫

Lecturer at Qingdao University, School of Computer Science and Technology (January 2015-Present). Teaching undergraduate and graduate courses in computer science. Supervising student research projects and theses. Conducting research in high-performance computing. Published 12 research papers in journals and conferences. Granted 2 patents.

Research Interests 🔬

Dr. Li Qiang’s research interests lie in high-performance computing, particularly in the optimization and parallel implementation of numerical simulations and the development of new computational frameworks. His work focuses on enhancing computational efficiency and scalability in large-scale scientific computations.

Awards 🏆

Dr. Li Qiang has been recognized for his contributions to the field of high-performance computing through multiple publications and patents. His innovative work has led to advancements in computational methods and has garnered attention in the academic community.

Publications 📄

Optimization Research of Heterogeneous 2D-Parallel Lattice Boltzmann Method Based on Deep Computing Unit. Appl. Sci. 2024, 14, 6078.

Heterogeneous Parallel Implementation of Large-Scale Numerical Simulation of Saint-Venant Equations. Appl. Sci. 2022, 12, 5671. Cited by 6

The Study of Parallelization of SWAT Hydrology Cycle. The 32nd ACM International Conference on Supercomputing, Beijing, 2018. [Cited by 3]

A New Parallel Framework of Distributed SWAT Calibration. Journal of Arid Land, 2015, 7(1): 122-131. [Cited by 7]

Parallel Simulation of High-Dimensional American Option Pricing Based on CPU VS MIC. Concurrency and Computation: Practice and Experience, 2014, 27(5): 1110-1121. [Cited by 5]

Jihyeon Ryu | Computer Science | Best Researcher Award

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Assist Prof Dr. Jihyeon Ryu | Computer Science | Best Researcher Award

Professor, Kwangwoon University, South Korea

👩‍🏫 Jihyeon Ryu is an Assistant Professor at the School of Computer and Information Engineering, Kwangwoon University. She specializes in split learning, convolutional neural networks, and user authentication, contributing significantly to the field of computer science with her extensive research and numerous publications.

Profile

Google Scholar

 

Education

Ph.D. in Software (Integrated Master’s and Doctorate Course) from Sungkyunkwan University (Mar. 2018 – Feb. 2023), advised by Prof. Dongho Won and Prof. Hyoungshick Kim. B.S. in Mathematics and Computer Science and Engineering from Sungkyunkwan University (Mar. 2013 – Feb. 2018). Early Graduation from Sejong Science High School (Mar. 2011 – Feb. 2013).

 

Research Interests:

Split Learning. Convolutional Neural Networks. User Authentication

Awards

Family Company Workshop Lecture, Hoseo University (Feb. 2022). Invited Lecturer, Mental Women’s High School (Nov. 2021). Excellence Prize, Software Department Excellence Research Awards (Feb. 2021). Graduate Merit Scholarship, Sungkyunkwan University (Mar. 2018 – Feb. 2021). SimSan Scholarship, Multiple instances (Mar. 2018 – Sep. 2020). Excellence Award, 국가 암호기술 전문인력 양성과정 (Nov. 2019). Grand Prize, Software Department Excellence Research Awards (Feb. 2019). Samsung Science Scholarship (Mar. 2013 – Feb. 2018)

Publications

Lightweight Hash-Based Authentication Protocol for Smart Grids. Sensors, 2024. Sangjin Kook, Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.

Enhanced Lightweight Medical Sensor Networks Authentication Scheme Based on Blockchain. IEEE ACCESS, 2024. Taewoong Kang, Naryun Woo, Jihyeon Ryu.

Secure and Anonymous Authentication Scheme for Mobile Edge Computing Environments. IEEE Internet of Things Journal, 2024. Hakjun Lee, Jihyeon Ryu, Dongho Won.

Distributed and Federated Authentication Schemes Based on Updatable Smart Contracts. Electronics, 2023. Keunok Kim, Jihyeon Ryu, Hakjun Lee, Youngsook Lee, Dongho Won.

An Improved Lightweight User Authentication Scheme for the Internet of Medical Things. Sensors, 2023. Keunok Kim, Jihyeon Ryu, Youngsook Lee, Dongho Won.