Yansheng Wu | Computer Science | Best Researcher Award

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Dr. Yansheng Wu | Computer Science | Best Researcher Award

Associate Professor, Nanjing University of Posts and Telecommunications, China

Dr. Yansheng Wu is a distinguished researcher and Associate Professor at the School of Computer Science, Nanjing University of Posts and Telecommunications, China. With a strong background in Pure Mathematics, his expertise lies in Finite Fields, Cryptography, and Coding Theory. He has made significant contributions to algebraic coding theory and applications of algebra in cryptographic systems. Dr. Wu has held esteemed positions as a Postdoctoral Research Fellow at Ewha Womans University and a Visiting Scholar at the Hong Kong University of Science and Technology. His scholarly work is widely recognized, with numerous publications in prestigious journals such as IEEE Transactions on Information Theory and Finite Fields and Their Applications. In addition to his research, he actively contributes as a reviewer for multiple high-impact journals, making him a key figure in the field of applied mathematics and cryptography. 📚✨

Publication Profile

🎓 Education

Dr. Yansheng Wu holds a Ph.D. in Pure Mathematics from Nanjing University of Aeronautics and Astronautics (2019), where he focused on algebra and number theory applications in coding theory. He earned his MSc in Pure Mathematics from Guangxi Teachers Education University (2016), working on matrix rings and finite group rings. His academic journey began with a BSc in Mathematics and Applied Mathematics from Anhui Normal University (2013), where he explored number partitions. His rigorous training in algebra, number theory, and their cryptographic applications has shaped his prolific research career. 🎓🔢

💼 Experience

Dr. Wu’s professional journey includes serving as an Associate Professor at Nanjing University of Posts and Telecommunications since 2020. Prior to that, he completed a postdoctoral fellowship at Ewha Womans University, South Korea, where he collaborated on advanced research in finite fields. His academic engagements also include a visiting scholar position at the Hong Kong University of Science and Technology in 2023-2024, enhancing international collaborations in cryptography and coding theory. He has participated in prestigious research forums, including the East Asian Core Doctoral Forum at The University of Tokyo. 🌍📊

🏆 Awards and Honors

Dr. Wu has secured multiple prestigious research grants, including the National Natural Science Foundation of China (2022-2024) and the Talent Introduction Fund at Nanjing University of Posts and Telecommunications (2021-2023). His research excellence is also recognized through editorial board memberships at leading journals like AIMS Mathematics and numerous reviewing roles for top-tier mathematical and cryptographic journals, including IEEE Transactions on Information Theory and Finite Fields and Their Applications. 🏅🔬

🔬 Research Focus

Dr. Wu’s research interests span Finite Fields, Coding Theory, Cryptography, and Algebraic Structures. His work explores the design and analysis of linear codes, algebraic cryptosystems, and combinatorial structures over finite fields. He has extensively studied the properties of MDS codes, Reed-Solomon codes, and quaternary codes, contributing novel constructions with optimal parameters. His interdisciplinary approach integrates number theory with applied cryptography, making his research pivotal in modern data security and error correction. 🔢🛡️

🔚 Conclusion

Dr. Yansheng Wu is a leading figure in the field of mathematics, cryptography, and coding theory. His contributions to algebraic coding, finite fields, and cryptographic structures have significantly impacted secure communications and data integrity. Through his research, editorial roles, and academic collaborations, he continues to shape the future of cryptographic mathematics, making lasting contributions to theoretical and applied aspects of the discipline. 🚀🔢

📚 Publications

Two classes of twisted generalized Reed-Solomon codes with two twists. Finite Fields and Their Applications, 104, 102595. [Cited by: TBD] 🔗 Link

When Does the Extended Code of an MDS Code Remain MDS? IEEE Transactions on Information Theory, 71(1), 263-272. [Cited by: TBD] 🔗 Link

Two classes of narrow-sense BCH codes and their duals. IEEE Transactions on Information Theory, 70(1), 131-144. [Cited by: TBD] 🔗 Link

Linear Complementary Dual Codes Constructed from Reinforcement Learning. Journal of System Science and Complexity. [Cited by: TBD] 🔗 Link

Two families of linear codes with desirable properties from some functions over finite fields. IEEE Transactions on Information Theory, 70(11), 8320-8342. [Cited by: TBD] 🔗 Link

Optimal few-weight codes and their subfield codes. Journal of Algebra and Its Applications, 23(4), 2450248. [Cited by: TBD] 🔗 Link

Two Infinite Families of Quaternary Codes. IEEE Transactions on Information Theory, 70(12), 8723-8733. [Cited by: TBD] 🔗 Link

Quaternary codes and their binary images. IEEE Transactions on Information Theory, 70(7), 4759-4768. [Cited by: TBD] 🔗 Link

 

Leyi Zhao | Computer Science | Best Researcher Award

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Dr. Leyi Zhao | Computer Science | Best Researcher Award

Doctor, Beijing University of Chinese Medicine, China

Dr. Leyi Zhao is a dedicated clinical doctoral researcher in Integrative Medicine at the prestigious Beijing University of Chinese Medicine. With a keen interest in digestive tract diseases, Dr. Zhao specializes in studying precancerous lesions, tumors, and the intricate relationship between the immune environment and disease progression. Passionate about blending traditional medicine with modern computational techniques, Dr. Zhao integrates computer language and data analysis to establish innovative prognostic models, enhancing clinical applications. With multiple completed and ongoing research projects, Dr. Zhao’s contributions to the field of immunotherapy and colorectal cancer prognosis are highly impactful.

Publication Profile

ORCID

🎓 Education

Dr. Zhao is currently pursuing a doctorate in Integrative Medicine at Beijing University of Chinese Medicine, a renowned institution for traditional and modern medical research. This academic journey has equipped Dr. Zhao with a strong foundation in both traditional Chinese medical practices and cutting-edge clinical research methodologies.

💼 Experience

With extensive research experience, Dr. Zhao has led and contributed to multiple research projects focusing on colorectal cancer, immune microenvironments, and predictive modeling in oncology. Through a blend of experimental studies and computational approaches, Dr. Zhao has contributed significantly to understanding the impact of tertiary lymphoid structures (TLS) on tumor prognosis and immune response. In addition to academic research, Dr. Zhao has been involved in consultancy and industry-based projects, furthering the practical application of scientific findings.

🏆 Awards and Honors

Dr. Zhao’s research excellence has been recognized through publications in high-impact journals indexed in SCI and Scopus. The innovative work in colorectal cancer prognosis and immunotherapy has garnered citations and recognition within the scientific community. As an active contributor to the field, Dr. Zhao has been nominated for the prestigious Best Researcher Award at the Cryogenicist Global Awards.

🔬 Research Focus

Dr. Zhao’s primary research focus lies in immunotherapy for tumors, particularly in colorectal cancer. The groundbreaking research involves developing a TLS-based prognostic model that explores immune cell interactions within tumors. This model holds potential for predicting patient prognosis and treatment responsiveness, offering valuable insights into personalized medicine. Furthermore, Dr. Zhao’s interdisciplinary approach integrates network pharmacology, computational modeling, and traditional Chinese medicine, enhancing the precision and effectiveness of cancer treatments.

🔗 Publications

The Impact of Tertiary Lymphoid Structures on Tumor Prognosis and the Immune Microenvironment in Colorectal Cancer. Biomedicines, 2025; 13(3):539
🔗 DOI: 10.3390/biomedicines13030539

 Limonin ameliorates indomethacin-induced intestinal damage and ulcers through Nrf2/ARE pathway. Immun Inflamm Dis, 2023; 11(2):e787
🔗 DOI: 10.1002/iid3.787

Chinese patent herbal medicine (Shufeng Jiedu capsule) for acute upper respiratory tract infections: A systematic review and meta-analysis. Integr Med Res, 2021; 10(3):100726
🔗 DOI: 10.1016/j.imr.2021.100726

Deciphering the Mechanism of Siwu Decoction Inhibiting Liver Metastasis by Integrating Network Pharmacology and In Vivo Experimental Validation. Integr Cancer Ther, 2024; 23:15347354241236205
🔗 DOI: 10.1177/15347354241236205

🔚 Conclusion

Dr. Leyi Zhao’s research contributions are shaping the future of colorectal cancer treatment and immune microenvironment analysis. With a strong foundation in integrative medicine and a passion for computational research, Dr. Zhao continues to push the boundaries of medical science, making a profound impact on oncology and personalized medicine. As a nominee for the Best Researcher Award, Dr. Zhao’s work exemplifies innovation, dedication, and a commitment to improving patient outcomes worldwide. 🌍

Mr. André Guimarães | Computer Science | Best Researcher Award

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Mr. André Guimarães | Computer Science | Best Researcher Award

Researcher, University of Beira Interior, Portugal

Andre Guimarães is a dedicated researcher and educator in the fields of Engineering Sciences, Industrial Engineering, and Management. With a strong academic background, he has contributed significantly to various research projects related to Industry 4.0 and digital transformation. He currently holds research positions at the University of Beira Interior and the Polytechnic Institute of Viseu, Portugal. Alongside his academic work, Andre has accumulated practical experience in industrial environments, particularly in production management and technical consulting, where he focuses on quality management, lean methodologies, and engineering innovations. He is also a passionate educator, teaching engineering and management-related courses at the higher education level. 📚🔬

Publication Profile

ORCID

Education:

Andre’s educational journey includes a Master’s degree in Mechanical Engineering and Industrial Management from the Polytechnic Institute of Viseu. He is currently pursuing a PhD in Industrial Engineering and Management at the University of Beira Interior. Additionally, Andre holds several postgraduate qualifications, including a specialization in Industry 4.0 and Digital Transformation from the Polytechnic Institute of Porto. His training also includes certifications in quality management, Six Sigma, lean manufacturing, and other engineering disciplines. 🎓📖

Experience:

Andre’s professional career spans both academia and industry. He has worked as a researcher at the University of Beira Interior and the Polytechnic Institute of Viseu, contributing to cutting-edge research in mechanical and industrial engineering. Additionally, Andre has extensive industrial experience, having served as the Production Manager at IPROM – Products Industry Metallics Ltd, where he oversaw production processes and managed technical operations. As a consultant and facilitator at the Welding and Quality Institute, Andre applies his expertise in quality management systems and continuous improvement. 🏭⚙️

Awards and Honors:

Andre Guimarães has been recognized for his contributions to both research and industry. He is a full member of the Order of Engineers in Portugal and a fellow at FCT Research. His work has been acknowledged through various academic and industry accolades, cementing his reputation as a skilled professional and educator in his field. 🏅🌟

Research Focus:

Andre’s research interests are deeply rooted in Industry 4.0 technologies, digital transformation, lean management, and quality systems in industrial engineering. His research aims to bridge the gap between theoretical frameworks and practical applications in engineering, with a focus on improving production efficiency, implementing digital technologies, and optimizing management processes in industrial environments. His recent projects explore advanced methodologies in electromechatronics and systems research. 🔍📊

Conclusion:

With a rich academic background and a wealth of practical experience, Andre Guimarães stands at the intersection of research and industry, contributing to the evolution of engineering practices. His work, driven by a passion for innovation and education, continues to shape the future of industrial engineering and management in Portugal and beyond. Andre’s ongoing commitment to advancing the field through both research and practical applications makes him a valuable asset to the academic and industrial communities. 🚀🌍

Publications:

The influence of consumer, manager, and investor sentiment on US stock market returnsInvestment Management and Financial Innovations

Effects of Lean Tools and Industry 4.0 technology on productivity: An empirical studyJournal of Industrial Information Integration

Método Delphi modificado para abordar a transformação digital na gestão de ativosRevista de Ativos de Engenharia

Lean philosophy and Value Engineering methodologies. Their relations and synergy using Bert a natural language processing modelCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Modificação do Método Delphi para Aplicação num Questionário sobre a Transformação Digital na Gestão de AtivosCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Overview of the use of data assets in the context of Portuguese companies: Comparison between SMEs and large companiesCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Comparative analysis of welding processes using different thermoplasticsInternational Journal of Integrated Engineering

Amutha S | Computer Science | Best Researcher Award

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Dr. Amutha S | Computer Science | Best Researcher Award

Professor, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, India

👩‍🏫 Dr. S. Amutha is a Professor at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai. With over two decades of teaching and research experience, she has made notable contributions to cybersecurity, wireless networks, and AI-based innovations in healthcare and agriculture. Her dedication to academic excellence and impactful research has earned her numerous accolades and professional recognition.

Publication Profile

Strengths for the Award:

  1. Extensive Research Contributions: Dr. S. Amutha has published 17 research papers in SCI and Scopus-indexed journals, highlighting her impact on key areas such as network security and wireless ad-hoc networks. Her work focuses on high-impact fields like cybersecurity, deep learning, and blockchain technologies, making her contributions highly relevant in today’s technological landscape.
  2. Interdisciplinary Research: Dr. Amutha’s research spans multiple domains, including healthcare (medical image analysis, ECG signal detection) and agriculture (crop health monitoring). Her integration of AI, data science, and real-world applications strengthens her profile as a leading interdisciplinary researcher.
  3. Innovative Approach: Dr. Amutha has worked on cutting-edge topics, such as federated learning and CNN autoencoders, for solving problems in text classification and medical diagnostics. Her research also focuses on cybersecurity applications using deep learning models to detect Trojan attacks and improve phishing detection, demonstrating her innovative problem-solving capabilities.
  4. Research Output: With 9 patents under process, 27 international publications, book chapters, and strong editorial appointments, Dr. Amutha shows a prolific research output. She has also led consultancy projects, demonstrating an ability to bridge academia with industry.

Areas for Improvement:

  1. Research Citations: With a citation index of 29, there is room to increase the academic visibility of her work. Engaging more with collaborative research networks, open-access platforms, and conferences can boost her citation count.
  2. International Collaborations: While Dr. Amutha has significant research collaborations, broadening international partnerships could further elevate her research’s global impact, increasing her recognition in global academic circles.

Education

🎓 Dr. Amutha completed her B.E. in Computer Science and Engineering from Madurai Kamaraj University in 1999. She pursued an M.E. in Computer Science and Engineering at Anna University, Chennai, securing First Class with Distinction. Later, she earned her Ph.D. in Secure Routing in Wireless Adhoc Networks from Anna University.

Experience

💼 Dr. Amutha has served as an Associate Professor at PSR Engineering College, Tamil Nadu, from 2003 to 2023, before transitioning to her current role as Professor. She has guided numerous undergraduate and postgraduate students and has been actively involved in organizing workshops and faculty development programs. Her extensive experience includes delivering expert talks in machine learning and data science.

Research Focus

🔍 Dr. Amutha’s research spans network security, wireless ad hoc networks, and the application of AI in cybersecurity. Her interdisciplinary work includes deep learning models for detecting cyber threats, and AI innovations in healthcare, such as ECG signal detection and medical image analysis. She has also contributed to advancements in smart agriculture through federated learning applications.

Awards and Honours

🏆 Dr. Amutha has been recognized for her research and innovation, earning awards in both academia and industry collaborations. She is a life member of prestigious professional organizations such as ISTE and IEANG, and has consistently contributed to workshops and conferences as a speaker and organizer.

Publications (Top Notes)

📚 Dr. Amutha has published 27 research papers in reputed international journals and presented 15 papers in international conferences. She has also contributed to book chapters, demonstrating her scholarly impact across various domains.

  1. Amutha, S., “Secure Routing in Wireless Adhoc Networks,” International Journal of Advanced Research in Computer Science and Software Engineering, 2022. Cited by 29 articles – Focuses on routing security challenges in wireless networks.
  2. Amutha, S., “AI for Cybersecurity: Deep Learning Approaches,” Journal of Network Security, 2021. Cited by 15 articles – Explores the use of AI in detecting cyber threats.

Conclusion:

Dr. S. Amutha’s strengths in cutting-edge research, practical applications, and interdisciplinary innovation make her a strong contender for the Best Researcher Award. She demonstrates a balance of academic excellence, industry relevance, and forward-thinking research in fields that are critical to technological and societal progress. While expanding international collaboration and citations could enhance her profile, her current contributions merit recognition for her impactful and diverse research endeavors.

mourad JABRANE | Computer Science | Best Researcher Award

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Prof Dr. mourad JABRANE | Computer Science | Best Researcher Award

software enginee, sultan moulay slimane university, Morocco

JABRANE Mourad is a state-certified software engineer and a third-year Ph.D. candidate at the National School of Applied Sciences, Sultan Moulay Slimane University. With a passion for designing scalable and efficient systems, Mourad excels in data mining, machine learning, and distributed computing. As an adjunct professor, he effectively conveys complex concepts, making him a valuable contributor to both academia and industry.

Publication Profile

Strengths for the Award:

  1. Solid Academic Background: Jabrane Mourad holds a state-certified software engineering degree and is currently a Ph.D. candidate specializing in Big Data, showcasing a strong academic foundation in cutting-edge technologies.
  2. Research Contributions: His research work focuses on significant areas like entity resolution in Big Data, machine learning, and distributed computing. His publications in reputable journals, such as the Journal of Intelligent Information Systems and Information Systems, highlight his contributions to the field.
  3. Diverse Skill Set: Mourad has extensive expertise in programming languages (Java, Python, JavaScript, etc.), frameworks (Spring, Angular), and software engineering tools (Docker, Jenkins, Kubernetes), making him a well-rounded researcher with practical skills applicable to various domains.
  4. Teaching Experience: As an adjunct professor, Mourad has taught a wide range of subjects including data integration, advanced Java Enterprise Edition, and distributed systems. His teaching experience demonstrates his ability to communicate complex concepts clearly, which is a valuable trait in academia.
  5. International Recognition: The publication of his work in international journals and his participation in global research projects suggest that his research has gained international recognition, making him a strong candidate for the award.

Areas for Improvement:

  1. Broader Impact: While Mourad’s research contributions are significant, further efforts to collaborate on interdisciplinary projects or engage in community outreach could broaden the impact of his work.
  2. Innovation and Patents: Although he has a strong publication record, obtaining patents or developing innovative software solutions could further strengthen his candidacy for a best researcher award.
  3. Networking and Collaborations: Expanding his network and collaborating with more researchers across different institutions could help him gain more visibility and access to diverse research opportunities.

Education

Ph.D. Candidate (2021 – Present): National School of Applied Sciences, Sultan Moulay Slimane University.
Thesis title: Entity Resolution in Big Data. State Software Engineer (2018 – 2021): National School of Applied Sciences, Sultan Moulay Slimane University. MP Higher School Preparatory Classes (2016 – 2018): Centre Ibn Abdoun.
Track title: Mathematics, Physics, and Engineering Sciences.

Experience 💼

JABRANE Mourad has accumulated significant experience as an adjunct professor at the National School of Applied Sciences, where he has taught a variety of subjects including Data Integration, Data Quality, Advanced JEE, Distributed Systems, Python Programming, MATLAB, and C Programming. His roles extend to both regular courses and continuing education programs, demonstrating his versatility and commitment to teaching.

Research Focus 🔬

Mourad’s research is centered around big data, with specific interests in data mining, machine learning, and distributed computing. His Ph.D. work focuses on Entity Resolution in Big Data, where he is exploring innovative approaches to improve accuracy and efficiency in large-scale data matching.

Awards and Honors 🏅

Though the detailed awards and honors list is not provided, Mourad’s academic and professional journey is marked by his selection as a Ph.D. candidate and his appointment as an adjunct professor at a prestigious institution.

Publications 📚

Mourad has contributed extensively to the field of big data and machine learning. Below are some of his notable publications:

  1. “Erabqs: Entity resolution based on active machine learning and balancing query strategy” – Published in Journal of Intelligent Information Systems, March 2024. Cited by 3 articles.
  2. “Enhancing entity resolution with a hybrid active machine learning framework: Strategies for optimal learning in sparse datasets” – Published in Information Systems, November 2024. Cited by 7 articles.
  3. “Enhancing semantic web entity matching process using transformer neural networks and pre-trained language models” – Published in Computing and Informatics, 2024. Cited by 5 articles.
  4. “Sentiment analysis dataset in Moroccan dialect: Bridging the gap between Arabic and Latin scripted dialect” – Published in Language Resources and Evaluation, July 2024. Cited by 4 articles.

 

Conclusion:

Jabrane Mourad presents a strong case for the Best Researcher Award due to his solid academic background, notable research contributions in Big Data and machine learning, and diverse technical skills. His role as an adjunct professor and his extensive teaching experience further emphasize his ability to convey knowledge and contribute to the academic community. To enhance his candidacy, Mourad could focus on increasing the broader impact of his research through interdisciplinary collaborations and innovation. Overall, Mourad is a well-rounded candidate with the potential to make substantial contributions to the field, making him a suitable contender for the award.

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

 

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

GAN XU | Computer Science | Best Researcher Award

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Mr. GAN XU | Computer Science | Best Researcher Award

PhD. candidate, capital university of economics and business, China

Xu Gan is a Doctoral student at Capital University of Economics and Business, Beijing, specializing in Rural Finance, Financial Theory and Policy, and Supply Chain Finance. With a solid academic background and practical experience, Xu has contributed significantly to research in financial services and blockchain technology. 🏛️📚

Profile

Scopus

 

Education

Xu Gan completed a Master of Finance from Capital University of Economics and Business in Beijing (2018-2021) and a Bachelor of Biotechnology from Beijing Union University (2006-2010). Xu also has an extensive academic background in these fields, providing a strong foundation for research and analysis. 🎓📈

Experience

Xu has actively participated in several high-profile research projects, including the National Social Science Foundation of China’s research on rural financial services and the China Mobile Communication Federation’s blockchain technology applications in finance. Xu was responsible for designing research sub-topics and writing research reports. 📊🔬

Research Interests

Xu Gan’s research interests include Rural Finance, Financial Theory and Policy, and Supply Chain Finance. Xu is focused on improving rural financial services and exploring innovative financial technologies such as blockchain. 🌾💡

Awards

Xu has been recognized for academic excellence with several honors: Beijing Outstanding Graduates (2020), Outstanding Graduate of Beijing Union University (2020), and several awards for excellent papers at various financial and rural finance forums. 🏅📜

Publications

Yang, GZ., Xu, G., Zhang, Y., et al. Financial density of village banks and income growth of rural residents. Economic Issues, 2021, 504(08): 89-94.

Zhang, F., Xu, G., Zhang, XY, Cheng, X. Knowledge mapping analysis of seven decades of rural finance research in China. Rural Finance Research, 2020(01): 10-20.

Zhang, F., Xu, G., Cheng, X. A review of blockchain applications in the financial sector. Technology for Development, 2019, 15(08): 865-871.

Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

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Dr. Hafiza Sadia Nawaz | Computer Science | Women Researcher Award

Shenzhen University, China

🎓 Dr. H. Sadia Nawaz is a distinguished researcher and academic in Computer Vision, with a Ph.D. from Ocean University of China. Her work focuses on Temporal Activity Detection using Natural Language. With a background in both teaching and research, she has contributed significantly to the field of computer vision and continues to pursue a career as a postdoctoral researcher. Her extensive knowledge and dedication to the subject make her a valuable asset to any research group.

Profile

Scopus

 

Education

📚 Dr. H. Sadia Nawaz holds a Ph.D. in Computer Science from Ocean University of China, specializing in Temporal Moment Localization using Natural Language. She also completed her Master’s in Information Science and Technology at the University of Sargodha and an MS in Computer Science and Technology with a focus on Cyber Security at the University of Lahore. Her academic background provides a strong foundation for her research and teaching roles.

Experience

💼 Dr. Nawaz has a robust teaching background, having served as a Programming Teaching Assistant at Heriot-Watt University and Ocean University of China, and as a Computer Science Lecturer at Superior University of Lahore and the University of Sargodha. Her roles in academia have honed her skills in teaching, mentoring, and research, contributing to her expertise in computer vision and machine learning.

Research Interests

🔍 Dr. Nawaz’s research interests include Activity Localization in Videos via Language, Temporal Moment Detection, and Natural Language Processing. She is particularly focused on moment detection in complex scenarios and the integration of machine learning methods with computer vision techniques to enhance video understanding and activity localization.

Awards

🏅 Dr. H. Sadia Nawaz has been recognized for her research contributions in the field of computer vision, particularly for her work on Temporal Moment Localization using Natural Language. Her research has been published in high-impact journals, reflecting her expertise and commitment to advancing the field.

Publications

Temporal Moment Localization via Natural Language by Utilizing Video Question Answers as a Special Variant and Bypassing NLP for Corpora

IVTEN – Integration of Visual-Textual Entities for Temporal Activity Localization via Language in Video

Revelation of Novel Paradigm in Temporal Moment Localization by Using Natural Language in Video

Multi-level Edges and Context Arranger Architecture Using Referencing Expressions for Temporal Moment Localization via Natural Language

A Frame-Based Feature Model for Violence Detection from Surveillance Cameras Using ConvLSTM Network

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.