Zhizhen Chen | Computer Science | Best Researcher Award

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Dr. Zhizhen Chen | Computer Science | Best Researcher Award

Senior Lecturer, University of Greenwich, United Kingdom

🎓 Dr. Zhizhen Chen is a dedicated academic professional serving as a Senior Lecturer in Finance at the University of Greenwich since 2017. With a rich background in finance and economics, Dr. Chen brings extensive experience from both academia and industry. His research interests encompass financial markets, risk management, and financial engineering, contributing significantly to several top-tier finance journals. Dr. Chen is also an active peer reviewer and passionate educator, sharing his expertise through innovative courses like Fintech Banking and Financial Engineering and Machine Learning. 🌍📊

Publication Profile

Scopus

Strengths for the Award:

  1. Research Excellence: Dr. Chen has a strong publication record, with multiple articles published in high-impact journals such as “Journal of International Money and Finance” and “Research in International Business and Finance,” both rated 4* in SJR. This demonstrates his capability in producing high-quality research in the field of finance.
  2. Peer Review Activities: He has been a peer reviewer for several prestigious journals since 2016, which showcases his recognition in the academic community and his commitment to advancing knowledge in finance.
  3. Academic and Professional Credentials: Dr. Chen holds a PhD in Finance, is a Fellow of the Higher Education Academy, and has passed CFA Level 1. This combination of academic qualifications and professional certification adds to his credibility and expertise in the field.
  4. Diverse Teaching Portfolio: His teaching experience spans various finance and economics-related courses, demonstrating versatility and a solid understanding of different areas within the field.
  5. Industry Experience: Dr. Chen’s experience as an Investment Analyst and his work with financial institutions provide him with practical insights, enhancing his academic work’s relevance and applicability.
  6. Continuous Professional Development: His commitment to continuous learning and development is evident through his successful completion of the CFA Level 1 exam and his role in ongoing staff development activities.

Areas for Improvement:

  1. Broader Research Impact: While Dr. Chen has a strong record in finance-specific publications, expanding his research impact across other interdisciplinary areas, such as sustainable finance or fintech, could further enhance his profile.
  2. Leadership Roles in Research: Taking on more leadership roles in research projects or academic committees could strengthen his candidacy by demonstrating his influence beyond his individual contributions.
  3. Grants and Funding: Securing research grants or funding is a notable achievement in academia that is not highlighted in the current profile. Pursuing funding opportunities could bolster his research credentials further.

Education

🎓 Dr. Zhizhen Chen holds a PhD in Finance from the University of Glasgow (2018), demonstrating his strong foundation in financial research and education. He is also a Fellow of the Higher Education Academy (2017), a testament to his commitment to teaching excellence, and he earned an MSc in Economics from the University of Wuhan (2012). 📚✨

Experience

🌟 Dr. Chen’s career spans roles as a Senior Lecturer in Finance at the University of Greenwich since 2017, where he excels in teaching and research. His prior experience includes serving as a Research Assistant and Teaching Assistant at the University of Glasgow, and an Investment Analyst at ICBC Wuhan. This blend of academic and industry roles has equipped him with a unique perspective on finance education. 💼💹

Research Focus

🔍 Dr. Chen’s research is focused on financial markets, risk management, securitization, and financial engineering. He actively contributes as a peer reviewer for prestigious journals, including the Journal of International Financial Markets, Institutions & Money, and Finance Research Letters, ensuring rigorous academic standards in the field. 📑🔬

Awards and Honours

🏅 Dr. Chen was recognized as a Fellow of the Higher Education Academy in 2017, highlighting his dedication to teaching excellence. In addition, he passed the CFA Level 1 exam in 2020, demonstrating his commitment to continuous professional development in finance. 🎖️📈

Publication Top Notes

Lin, W., Yan, W., Chen, Z., Xiao, R. (2023). Research on product appearance patent spatial shape recognition for multi-image feature fusion. Multimedia Tools and Applications (SJR 3*).

Xiao, R., Li, G., Chen, Z. (2023). Research progress and prospect of evolutionary many-objective optimization. Control and Decision.

Chen, Z., Liu, H., Peng, J., Zhang, H., Zhou, M. (2022). Securitization and bank efficiency. In: Ferris, S.P., Kose, J., Makhija, A.K., (eds.) Empirical Research in Banking and Corporate Finance. Emerald Publishing Limited.

Conclusion:

Dr. Zhizhen Chen is a suitable candidate for the “Research for Best Researcher Award” due to his significant contributions to the field of finance through high-quality publications, peer-review activities, and professional development. While there is room for growth in interdisciplinary research and leadership roles, his current achievements and ongoing commitment to both academic and professional excellence make him a compelling contender for the award.

Shaghaf Kaukab | Technology | Young Scientist Award

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Dr. Shaghaf Kaukab | Technology | Young Scientist Award

scientist, ICAR-CIPHET, India

Shaghaf Kaukab is a dedicated Scientist at ICAR-Central Institute of Post-Harvest Engineering & Technology (ICAR-CIPHET), Ludhiana, specializing in Agricultural Structure and Process Engineering. With over 11 years of combined experience in scientific research and academic exploration within the food engineering and technology platform, Shaghaf has made significant contributions to the domain of extrusion processing, storage technology, drying techniques, and functional food product development. His work emphasizes the application of AI, machine learning, and deep learning techniques in agriculture, leading to innovative solutions that improve post-harvest management and food processing.

Publication Profile

Scopus

Strengths for the Award

  1. Research Contributions: Shaghaf Kaukab has made significant contributions to agricultural structure and process engineering, particularly in post-harvest technology. Her work on projects such as IoT-based monitoring systems and AI-enabled robotic harvesters demonstrates her innovative approach and alignment with modern agricultural challenges.
  2. Academic Excellence: With a Ph.D. in Post Harvest Technology and multiple prestigious academic awards, she has a strong academic background. Her high CGPA scores and ICAR merit medals underscore her academic diligence.
  3. Interdisciplinary Expertise: Shaghaf has expertise in various domains, including AI, machine learning, image processing, and food process engineering, making her research impactful and versatile.
  4. Publications and Impact: She has published extensively in refereed journals and contributed to book chapters, highlighting her active involvement in advancing her field of research. The inclusion of her work in high-impact journals reflects her research’s quality and relevance.
  5. Leadership and Collaboration: Shaghaf has demonstrated leadership by managing several projects, mentoring students, and coordinating training programs. Her collaborative efforts with organizations like CDAC and international exposure (e.g., Purdue University) enhance her profile.

Areas for Improvement

  1. Broader Outreach: While Shaghaf has conducted training and outreach activities, expanding these efforts to reach a more diverse audience, including more international platforms, could enhance her influence and recognition.
  2. Grant Acquisition: Although involved in several projects, focusing on securing more independent research grants could further validate her capabilities and drive her research agenda.
  3. Networking and Professional Development: Increased participation in international conferences, workshops, and collaborations outside of India could further her exposure and contribute to professional growth.

 

🎓 Education

Shaghaf Kaukab earned his Ph.D. in Post-Harvest Technology from the Indian Agricultural Research Institute (IARI), New Delhi, with a stellar CGPA of 9.1/10 in 2019. Prior to this, he completed his M.Tech. in Post-Harvest Engineering & Technology from IARI, New Delhi, with a CGPA of 8.97/10 in 2016. His academic journey has been marked by excellence, laying a strong foundation for his research and scientific endeavors.

💼 Experience

Currently, Shaghaf is a Scientist in Agricultural Structures & Process Engineering at ICAR-CIPHET, Ludhiana, where he has been instrumental in the development of technologies such as the stereo-depth based detection and localization module for apples. He has successfully led and contributed to several ongoing projects, including IoT-based modular systems for cold storage and AI-enabled robotic apple harvesters. His role extends to technical writing, project implementation, and collaboration with academic and industrial partners.

🔍 Research Focus

Shaghaf’s research interests lie in the application of new-age technologies like AI, machine learning, and deep learning in the post-harvest agriculture sector. He focuses on image processing techniques (such as Biospeckle, RGB, X-ray, Hyperspectral imaging) and the analysis of food properties (physical, thermal, mechanical, and micro-structural). His work in food process engineering aims to enhance the efficiency and quality of post-harvest processes.

🏆 Awards and Honors

Shaghaf Kaukab’s work has earned him recognition within the scientific community, including membership in prestigious organizations such as the Indian Society of Agricultural Engineers (ISAE) and the American Society of Agricultural and Biological Engineers (ASABE). He serves as a regular reviewer for scientific journals and has been an external examiner for graduate students at Dr. Rajendra Prasad Central Agricultural University, Bihar.

📚 Publication Top Notes

Shaghaf has published numerous articles in refereed journals and contributed to book chapters and training manuals. His notable works include:

Improving Real-time Apple Fruit Detection: Depth and Multi-modal Information Fusions with Non-targeted Background Removal – Published in Ecological Informatics.

Chickpea Temperature Profile Development and its Implication under Microwave Treatment – Published in Biological Forum – An International Journal.

Osmotic Dehydration of Aloe-vera Gel Discs – Published in Journal of AgriSearch.

Engineering Properties, Processing, and Value Addition of Tamarind: A Review – Published in IJBSM.

Study of Engineering Properties of Selected Vegetable Seeds – Published in Indian Journal of Agricultural Sciences.

 

Conclusion

Shaghaf Kaukab is a strong candidate for the Research for Young Scientist Award. Her innovative research, interdisciplinary expertise, and significant contributions to agricultural engineering, particularly in post-harvest technology, make her a standout. While expanding her outreach and securing more independent funding could strengthen her profile further, her accomplishments thus far demonstrate her potential as a leader in her field.

 

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

 

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

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Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.

 

Ke Wu | Computer Science | Best Dissertation Award

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Prof. Ke Wu | Computer Science | Best Dissertation Award

professor, China University of Geosciences (Wuhan), China

Dr. Ke Wu is a distinguished professor at the China University of Geosciences, specializing in hyperspectral remote sensing and its applications in geosciences 🌏. Born on October 2, 1981, in Hubei, China, Dr. Wu has established himself as a leading expert in his field, contributing significantly to research and education 📚. Fluent in both Chinese and English, he excels in both written and spoken communication, making him a valuable asset to the academic community.

Profile

ORCID

 

Education

Dr. Ke Wu holds a Ph.D. in Photogrammetry and Remote Sensing from Wuhan University (2008) 🎓, where he also completed his B.S. in Information Engineering (2002) 🏫. His advanced education has provided a strong foundation for his research and teaching career in remote sensing and geophysics.

Experience

Since January 2020, Dr. Ke Wu has been a professor at the China University of Geosciences 👨‍🏫. Prior to this, he served as an associate professor from 2011 to 2019 and as a postdoctoral researcher in geophysics from 2009 to 2011. His extensive experience in academia has enabled him to mentor many students and contribute to numerous research projects.

Research Interests

Dr. Ke Wu’s research interests focus on hyperspectral remote sensed image processing and its applications in geosciences 🔬. He has led several significant research projects funded by the National Natural Science Foundation of China and other prestigious organizations. His work aims to advance the understanding and practical applications of remote sensing technologies.

Awards

In recognition of his contributions to the field, Dr. Ke Wu and his team have received numerous awards 🏆. Notably, in 2022, they won the third prize in the National Hyperspectral Satellite Remote Sensing Image Intelligent Processing and Industry Application Competition of the “Obit Cup”. His group also secured the third prize in the South Division of the “Yuan Chuang Cup” Innovation and Creativity Competition in 2019 and the first prize of the Surveying and Mapping Science and Technology Progress Award of the China Society of Surveying, Mapping, and Geographic Information in 2017.

Publications

Junfei Zhong, Ke Wu, Ying Xu* (2024). “Deep Spatial Feedback Refined Network with Multi-Level Feature Fusion for Hyperspectral Image Sub-pixel Mapping,” IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2024.3419157 – Cited by: 3 articles

Ke Wu, Fan Yang, Huize Liu, Ying Xu* (2024). “Detection of coral reef bleaching by multitemporal Sentinel-2 data using the PU-bagging algorithm: A feasibility study at Lizard Island,” Remote Sens. DOI: 10.3390/rs16132473 – Cited by: 5 articles

Ke Wu, Yanting Zhan, Ying An, Suyi Li* (2024). “Multiscale Feature Search-Based Graph Convolutional Network for Hyperspectral Image Classification,” Remote Sens. DOI: 10.3390/rs16132328 – Cited by: 4 articles

Wenjie Tang, Ke Wu, Yuxiang Zhang, Yanting Zhan* (2023). “A Siamese Network Based on Multiple Attention and Multilayer Transformer for Change Detection,” IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2023.3325220 – Cited by: 6 articles

Yanting Zhan, Ke Wu, Yanni Dong* (2022). “Enhanced Spectral–Spatial Residual Attention Network for Hyperspectral Image Classification,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2022.3197934 – Cited by: 8 articles

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.