Manjiang Xing | Digital economy | Best Researcher Award

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Prof. Manjiang Xing | Digital economy | Best Researcher Award

Qilu Institute of Technology | China

Publication Profile

Scopus

INTRODUCTION 👨‍🏫

Xing Manjiang is a distinguished academic and researcher, holding a Ph.D. and serving as a senior engineer and professor at Qilu Institute of Technology in China. He specializes in fields like Digital Economy, Digital Trade, Smart Cities, Artificial Intelligence, and E-commerce, among others. Xing is a key figure in multidisciplinary research, where his work fuses various technologies and business sectors, demonstrating leadership in both academia and the industry. His contributions span across publishing multiple research papers and securing several patents.

EARLY ACADEMIC PURSUITS 🎓

Xing Manjiang’s academic journey began with a Bachelor’s degree in Thermal and Power Engineering from North China University of Science and Technology in 2004. He later pursued a Master’s degree in Project Management at North China Electric Power University, completing it in 2019. Continuing his commitment to academia, he earned a Ph.D. in International Management (Global Business) from Kyonggi University in 2024. These academic milestones laid the foundation for his diverse contributions in both research and teaching.

PROFESSIONAL ENDEAVORS 💼

Throughout his career, Xing has held significant roles both in academia and industry. He is currently serving as a Professor at Qilu University of Technology, where he is involved in research and teaching undergraduate courses such as International Economic Cooperation and Introduction to Big Data. In addition to his academic duties, he worked as a Part-time Technical Director & Financial Director at Mingchuang Kehuan (Beijing) Technology Co. from 2021 to 2024. His industry experience includes positions as a Senior Engineer and Technician in several power generation companies, where he gained expertise in equipment management and infrastructure management.

CONTRIBUTIONS AND RESEARCH FOCUS 💡

Xing’s research primarily focuses on Digital Economy, Smart Cities, Artificial Intelligence, E-commerce, Regional Economy, and Social Efficiency. He has explored the integration of big data and AI with business strategies, such as in cross-border e-commerce and industry innovation. Xing’s ability to bridge technology with business makes his research especially impactful. He’s led several key projects, such as the Sichuan Provincial Science and Technology Department’s Key R&D Project and the China Association of Business Economics 2024 Planning Project, among others.

IMPACT AND INFLUENCE 🌍

Xing’s academic work has made a considerable impact in the fields of digital transformation and economic growth strategies. Through his research, he has contributed to enhancing urban economic efficiency by exploring the potential of smart city development. His insights into digital economy integration and smart energy have been acknowledged in major international journals, helping to advance policies and strategies related to technology and regional economic development. His participation in global trade, economic cooperation, and AI integration has solidified his influence in both academia and industry.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Xing has published numerous influential papers in well-respected journals. Notable among them is his SSCI paper in the International Review of Financial Analysis, titled “Digital Economy, Dual Innovation Capability, and Enterprise Labor Productivity”. His papers are widely cited in top journals, and he has authored and co-authored numerous works that deal with economic productivity, smart city models, and innovative technologies. His patents and edited monographs further attest to his significant academic footprint. He has also authored and edited several important papers, contributing to the broader scientific community’s understanding of digital economies and sustainable development.

HONORS & AWARDS 🏅

Xing Manjiang has earned various professional honors throughout his career. He is a Senior Member of the Chinese Society of Technology Economics and serves on expert committees such as the China Association of Trade in Services and the Shandong Green and Low-Carbon Expert Committee. His leadership in innovation and technical advancements in smart energy and green development has earned him recognition from both industry and academia.

LEGACY AND FUTURE CONTRIBUTIONS 🚀

Xing’s legacy is built on his pioneering work in integrating digital economy and smart cities with sustainability. As he continues to contribute to the academic field, he aims to further explore the potential of AI and big data in driving economic transformation. His ongoing projects will continue to shape the way we view technological solutions in business and urban development, ensuring his influence endures in the coming decades.

FINAL NOTE ✨

With a remarkable career marked by deep academic achievements, innovative contributions, and impactful leadership in multiple sectors, Xing Manjiang has solidified his position as a leading academic and researcher in the fields of digital transformation and international trade. His work continues to shape modern understanding and application of artificial intelligence, big data, and smart technologies, paving the way for future breakthroughs that will undoubtedly benefit both academia and industry.

Top Notes Publications 📚

Manjiang Xing, Chi Gong, Gyu-Hyen Moon, Xiaohong Ge

    • Title: Digital economy, dual innovation capability and enterprise labor productivity

    • Journal: International Review of Financial Analysis

    • Year: 2025

    • DOI: 10.1016/j.irfa.2025.104005

Manjiang Xing et al.

  • Title: Optimal Scheme Selection Model of Distributed Photovoltaic Consumption in Smart City Based on Gaussian Mixture Model

  • Journal: Journal of Nanoelectronics and Optoelectronics

  • Year: 2024

  • DOI: 10.1166/jno.2024.3575

Manjiang Xing et al.

    • Title: Enhancing urban economic efficiency through smart city development: A focus on sustainable transportation

    • Journal: Computers and Electrical Engineering

    • Year: 2024

    • DOI: 10.1016/j.compeleceng.2023.109058

Xing, Manjiang

    • Title: Power Information System Database Cache Model Based on Deep Machine Learning

    • Journal: Intelligent Automation & Soft Computing

    • Year: 2023

    • DOI: 10.32604/iasc.2023.034750

Manjiang Xing et al.

    • Title: Research on Smart City Competitiveness Model Based on the Integration of Digital Economy and Smart Energy

    • Journal: 무역통상학회지 (Korea Citation Index)

    • Year: 2022

    • DOI: 10.29331/JKRAIC.2022.12.22.6.277

Sherin Zafar | Machine Learning  | Women Researcher Award

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Dr. Sherin Zafar | Machine Learning  | Women Researcher Award

Jamia Hamdard | India

PUBLICATION PROFILE

Scopus

🌟 DR. SHERIN ZAFAR: ACADEMIC AND RESEARCH PIONEER 

👩‍🏫 INTRODUCTION

Dr. Sherin Zafar is an accomplished Assistant Professor in the Department of Computer Science and Engineering at the School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi. Joining the institution in 2015, she has made remarkable contributions to teaching, research, and faculty development. With expertise in network security, machine learning, and health informatics, Dr. Zafar continues to inspire both students and colleagues alike.

🎓 EARLY ACADEMIC PURSUITS

Dr. Zafar’s academic journey began with a Bachelor’s degree in Computer Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal, followed by a Master’s degree in the same field. Her passion for optimizing network protocols led her to complete her Ph.D. at Manav Rachna International Institute of Research and Studies (MRIIRS) in 2015, where she focused on creating secure protocols for Mobile Ad-Hoc Networks (MANETs) through biometric authentication.

💼 PROFESSIONAL ENDEAVORS

Since joining Jamia Hamdard, Dr. Zafar has been dedicated to academic growth and research excellence. Her professional endeavors span the fields of artificial intelligence (AI), health informatics, and wireless networks. A regular participant in faculty development programs (FDP), workshops, and international conferences, Dr. Zafar stays at the forefront of technological advancements, demonstrating her commitment to personal and professional growth.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Zafar’s research interests are centered around applying AI and computational techniques to real-world problems, especially in health and security. Her work in e-health, including maternal health improvement through AI-based systems, and the development of secure network protocols, highlights her commitment to impactful research. She has also explored the application of machine learning in smart city technologies and water quality monitoring.

🌍 IMPACT AND INFLUENCE

Dr. Zafar has made a significant impact in the academic community through her publications and collaborative research. Her work in healthcare AI, optimization techniques, and network security has been widely recognized and cited by scholars and professionals worldwide. Her contributions have advanced both theoretical and practical aspects of computer science and engineering.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

Dr. Zafar’s academic footprint includes high-quality research papers published in top-tier journals and international conference proceedings. Her studies, including works on AI in healthcare and photo captioning for visually impaired individuals, have been published in journals like Heliyon, Proceedings on Engineering Sciences, and Multimedia Tools and Applications. These works have been indexed in Scopus and Web of Science, contributing to the ongoing academic dialogue.

🏆 HONORS & AWARDS

Throughout her career, Dr. Zafar has received several honors in recognition of her contributions to teaching and research. These accolades showcase her dedication to enhancing the educational landscape and driving innovations in technology and healthcare.

🛠️ LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Zafar continues her work at Jamia Hamdard, her legacy is one of inspiring innovation and fostering academic excellence. With a focus on AI, machine learning, and secure communications, her future research is poised to make lasting contributions to the fields of computer science and healthcare, inspiring future generations of researchers and professionals.

📜 FINAL NOTE

Dr. Sherin Zafar’s career is a testament to her passion for research and teaching. Through her groundbreaking research in AI, network security, and healthcare, Dr. Zafar has earned a well-deserved reputation as a leader in her field. As she continues her academic journey, her influence will undoubtedly shape the future of computer science and engineering, leaving a lasting legacy for years to come.

📚 TOP NOTES PUBLICATIONS 

Internet of things assisted deep learning enabled driver drowsiness monitoring and alert system using CNN-LSTM framework

Authors: S.P. Soman, Sibu Philip G., Senthil Kumar G., S.B. Nuthalapati, Suri Babu S., Zafar Sherin, K.M. Abubeker K.M.
Journal: Engineering Research Express
Year: 2024

Holistic Analysis and Development of a Pregnancy Risk Detection Framework: Unveiling Predictive Insights Beyond Random Forest

Authors: N. Irfan Neha, S. Zafar Sherin, I. Hussain Imran
Journal: SN Computer Science
Year: 2024

Correction to: A transformer based real-time photo captioning framework for visually impaired people with visual attention

Authors: A.K.M. Kunju Abubeker Kiliyanal Muhammed, S. Baskar S., S. Zafar Sherin, S. Rinesh S., A. Shafeena Karim A.
Journal: Multimedia Tools and Applications
Year: 2024

A transformer based real-time photo captioning framework for visually impaired people with visual attention

Authors: K.M. Abubeker K.M., S. Baskar S., S. Zafar Sherin, S. Rinesh S., A. Shafeena Karim A.
Journal: Multimedia Tools and Applications
Year: 2024

 Enhancing Heart Health Prediction with Natural Remedies Through Integration of Hybrid Deep Learning Models

Authors: L.M.S. Akoosh Lamiaa Mohammed Salem, F. Siddiqui Farheen, S. Zafar Sherin, S. Naaz Sameena, M.A. Afshar Alam
Journal: Journal of Natural Remedies
Year: 2024

Synergistic Precision: Integrating Artificial Intelligence and Bioactive Natural Products for Advanced Prediction of Maternal Mental Health During Pregnancy

Authors: N. Irfan Neha, S. Zafar Sherin, I. Hussain Imran
Journal: Journal of Natural Remedies
Year: 2024

Chunyu Liu | Neuroscience Data Analysis | Women Researcher Award

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Dr. Chunyu Liu | Neuroscience Data Analysis | Women Researcher Award

North China Electric Power University | China

PUBLICATION PROFILE

Google Scholar

Dr. Chunyu Liu⚡🌍

INTRODUCTION 🧠💡

Dr. Chunyu Liu is a Lecturer at North China Electric Power University, specializing in machine learning, neural decoding, and visual attention. Her research delves into the integration of AI and brain science, focusing on neural signals like MEG and fMRI to gain insights into cognitive functions and develop new AI theories. Her work bridges the gap between artificial intelligence and neuroscience, contributing to both fields in groundbreaking ways. 🌟

EARLY ACADEMIC PURSUITS 🎓📚

Dr. Liu’s academic journey began with a B.S. degree in Mathematics and Applied Mathematics from Henan Normal University. She went on to earn an M.S. degree in Applied Mathematics from Northwest A&F University, and a Ph.D. in Computer Application Technology from Beijing Normal University. These formative years built the foundation for her expertise in the intersection of computer science and cognitive science. 🔬

PROFESSIONAL ENDEAVORS 💼🔍

After completing postdoctoral training at Peking University, Dr. Liu embarked on her career as a lecturer at North China Electric Power University. In this role, she has led multiple research projects, mentored students, and contributed to the advancement of neural decoding and cognitive computing. Her professional endeavors focus on integrating theoretical AI methods with practical neuroscience. 🚀

CONTRIBUTIONS AND RESEARCH FOCUS ON Neuroscience Data Analysis 🧑‍🔬🔎

Dr. Liu’s research is primarily concerned with the neural mechanisms underlying object recognition, emotion, and visual attention. By combining AI theories with psychological experimental paradigms, she works with multi-modal neural signals like MEG and fMRI to better understand cognitive functions. Her work provides critical insights into how the brain processes information and leads to the development of advanced AI systems. 🤖🧠

IMPACT AND INFLUENCE 🌍📈

Dr. Liu has made substantial contributions to the fields of cognitive computing and neural decoding. Her innovative research models decode stimuli and cognitive states from brain activity, advancing our understanding of the human brain. Her influence extends globally, as her work is not only used to better understand cognition but also informs the development of intelligent AI systems. 🌐✨

ACADEMIC CITATIONS AND PUBLICATIONS 📑📊

With over 10 academic papers, including six SCI-indexed publications as the first author, Dr. Liu’s work has earned wide recognition. Noteworthy papers include “S-TBN: A New Neural Decoding Model to Identify Stimulus Categories from Brain Activity Patterns” in IEEE Transactions on Neural Systems and Rehabilitation Engineering and “Decoding Six Basic Emotions from Brain Functional Connectivity Patterns” in Science China Life Sciences. Her research continues to shape future studies in the fields of cognitive computing and AI. 📝🏆

HONORS & AWARDS 🏅🏆

Dr. Liu has received numerous prestigious awards and recognition for her pioneering work in cognitive computing and brain science. These accolades reflect the high regard for her contributions to neural decoding and her influence on both the neuroscience and AI communities. 🎖️

LEGACY AND FUTURE CONTRIBUTIONS HIGHLIGHT 🏛️🌱

Dr. Liu’s future research promises to continue pushing the boundaries of both cognitive science and artificial intelligence. By developing more sophisticated neural decoding models, she aims to further our understanding of the brain’s cognitive processes while advancing the development of AI systems that can more effectively interact with and understand human cognition. Her legacy will be one of innovation, discovery, and progress. 🌟

FINAL NOTE 🔮💭

As Dr. Liu continues her research, she is poised to make lasting contributions to both artificial intelligence and neuroscience. Her work will further bridge the gap between these fields, and her innovations will have a profound impact on how we understand human cognition and develop intelligent systems. Her legacy is one of groundbreaking interdisciplinary research. 🔮

 TOP NOTES PUBLICATIONS 📚

Decoding six basic emotions from brain functional connectivity patterns
    • Authors: C Liu, Y Wang, X Sun, Y Wang, F Fang
    • Journal: Science China Life Sciences
    • Year: 2023
Decoding disparity categories in 3-dimensional images from fMRI data using functional connectivity patterns
    • Authors: C Liu, Y Li, S Song, J Zhang
    • Journal: Cognitive Neurodynamics
    • Year: 2020
Categorizing objects from MEG signals using EEGNet
    • Authors: R Shi, Y Zhao, Z Cao, C Liu, Y Kang, J Zhang
    • Journal: Cognitive Neurodynamics
    • Year: 2021
Rapidly decoding image categories from MEG data using a multivariate short-time FC pattern analysis approach
    • Authors: C Liu, Y Kang, L Zhang, J Zhang
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Year: 2020
Image categorization from functional magnetic resonance imaging using functional connectivity
    • Authors: C Liu, S Song, X Guo, Z Zhu, J Zhang
    • Journal: Journal of Neuroscience Methods
    • Year: 2018
s-TBN: A new neural decoding model to identify stimulus categories from brain activity patterns
    • Authors: C Liu, B Cao, J Zhang
    • Journal: IEEE Transactions on Neural Systems and Rehabilitation Engineering
    • Year: 2024

Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

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Dr. Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

Korea University Anam Hospital AI Center | South Korea

Publication Profile

Scopus

Google Scholar

INTRODUCTION 🧑‍🎓

Dr. Kwang-Sig Lee is a distinguished academician, research leader, and innovator specializing in the integration of medical and social informatics. Currently serving as Vice Center Chief at the AI Center of Korea University Anam Hospital, Dr. Lee’s groundbreaking research combines artificial intelligence with diverse datasets, such as genetic, image, numeric, and text data. His expertise in AI-driven systems has led to revolutionary work in healthcare, focusing on predictive AI models and multimodal machine learning. His work has earned significant recognition, influencing both academic circles and real-world medical applications.

EARLY ACADEMIC PURSUITS 🎓

Dr. Lee’s academic journey began at Kon Kuk University in Seoul, South Korea, where he earned a Bachelor’s degree in Economics and Physics (1994-1999), with a GPA of 3.52/4.00. He furthered his studies at Iowa State University (1999-2004), earning dual Master’s degrees in Economics and Sociology, graduating with a GPA of 3.69/4.00. Dr. Lee’s pursuit of advanced studies led him to Johns Hopkins University, where he obtained his Ph.D./MSE in Sociology and Applied Mathematics with a focus on health systems, securing a GPA of 3.63/4.00.

PROFESSIONAL ENDEAVORS 💼

Dr. Lee’s professional career spans across multiple prestigious institutions. At present, he holds the role of Vice Center Chief at Korea University’s AI Center in the Medical School. His previous roles include serving as a Research Associate Professor at the same institution, and Senior Research Fellow positions at various research agencies, including Acorn, Enliple, Agilesoda, and National Health Insurance Service. Dr. Lee has also worked as an Assistant Professor at Yonsei University and Sungkyunkwan University, contributing his expertise in preventive medicine and biostatistics.

CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE 🧬

Dr. Lee’s contributions to the field of medical and social informatics are vast and impactful. His research primarily focuses on the application of artificial intelligence (AI) in healthcare, especially through the use of machine learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. His work explores the integration of genetic, image, numeric, and text data, thereby providing a more holistic approach to solving complex health-related challenges. Dr. Lee is known for his expertise in “Wide & Deep Learning,” a method that synthesizes multiple AI approaches to offer more powerful insights and predictive models.

IMPACT AND INFLUENCE 🌍

Dr. Lee’s innovative research has earned significant recognition both in academic and industrial circles. His work has been published in over 45 SCIE-indexed journals with a combined impact factor of 168. His Field-Weighted Citation Impact is 1.76, surpassing the average citation impact of KAIST in 2021. His expertise is frequently sought in both teaching and consultation, with Dr. Lee being an influential member of various academic committees. His ability to mentor graduate students and lead multidisciplinary research projects has significantly shaped the landscape of AI and healthcare.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Lee’s extensive publication record spans notable journals such as Cancers, European Radiology, International Journal of Surgery, and Journal of Medical Systems. His contributions have greatly impacted the scientific community, with a robust body of work related to medical AI, health informatics, and predictive modeling. In addition to his research articles, Dr. Lee has served as a guest editor for journals like Frontiers in Bioscience and Applied Sciences, as well as a reviewer for top-tier publications such as Nature Communications and Journal of Big Data.

HONORS & AWARDS 🏆

Throughout his academic career, Dr. Lee has been the recipient of numerous accolades, including full financial support during his tenure at Johns Hopkins University and Iowa State University. Additionally, he has been awarded for his academic excellence during his undergraduate studies at Kon-Kuk University. Dr. Lee’s consistent recognition for research excellence is evident from his impactful publications and active participation in the academic community, including his involvement in major research projects funded by government agencies.

FINAL NOTE ✨

Dr. Kwang-Sig Lee’s career is a testament to his dedication to advancing AI in medicine and social sciences. His expertise in combining machine learning with healthcare applications has paved the way for new innovations in predictive medicine, offering vital contributions to global healthcare systems. As he continues to lead research projects at the AI Center at Korea University, Dr. Lee’s legacy will be defined by his commitment to improving public health through cutting-edge technology and interdisciplinary research.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Lee’s future endeavors are poised to have a lasting impact on the fields of AI and healthcare. As the Vice Center Chief at one of the top medical schools, his work is expected to advance predictive healthcare models, fostering the development of more personalized and efficient healthcare solutions. With his expertise in “Wide & Deep Learning,” Dr. Lee is likely to continue influencing both the academic community and industry, shaping the future of AI-driven healthcare innovations.

TOP NOTES PUBLICATIONS 📚

Article: Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old
  • Authors: K. Lee, Kwang-sig; B. Ham, Byung-joo
    Journal: Psychiatry Investigation
    Year: 2024
Article: A Machine Learning-Based Decision Support System for the Prognostication of Neurological Outcomes in Successfully Resuscitated Out-of-Hospital Cardiac Arrest Patients
  • Authors: S. Lee, Sijin; K. Lee, Kwang-sig; S. Park, Sang-hyun; S. Lee, Sung-woo; S. Kim, Sujin
    Journal: Journal of Clinical Medicine
    Year: 2024
Article: Clinical and Dental Predictors of Preterm Birth Using Machine Learning Methods: The MOHEPI Study
  • Authors: J. Park, Jung-soo; K. Lee, Kwang-sig; J. Heo, Ju-sun; K. Ahn, Ki-hoon
    Journal: Scientific Reports
    Year: 2024
Article: Explainable Artificial Intelligence on Safe Balance and Its Major Determinants in Stroke Patients
  • Authors: S. Lee, Sekwang; E. Lee, Eunyoung; K. Lee, Kwang-sig; S.B. Pyun, Sung Bom
    Journal: Scientific Reports
    Year: 2024

Qinxu Ding | Machine Learning and AI Applications | Best Researcher Award

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Dr. Qinxu Ding | Machine Learning and AI Applications | Best Researcher Award

Dr. Qinxu Ding at Singapore University of Social Sciences, Singapore

PROFILES👨‍🎓

EARLY ACADEMIC PURSUITS 📚

This accomplished individual began their academic journey with a B.S. in Information and Numerical Science from Nankai University, Tianjin, China, graduating in July 2015 with an impressive GPA of 89/100. Their undergraduate studies laid a strong foundation in Mathematical Statistics, Probability Theory, and Data Mining, which paved the way for further academic exploration. They pursued a Ph.D. in Computational Mathematics at Nanyang Technological University, completing their thesis on Numerical Treatment of Certain Fractional and Non-fractional Differential Equations in April 2020.

PROFESSIONAL ENDEAVORS 💼

Currently, this individual serves as a Lecturer and DBA Supervisor in the Finance Programme at the Business School of the Singapore University of Social Sciences (SUSS) since July 2021. Their teaching portfolio includes various fintech courses such as Machine Learning and AI for FinTech, Blockchain Technology, and Risk Management for Finance and Technology. Prior to this role, they were a Research Fellow at the Alibaba-NTU Singapore Joint Research Institute, focusing on Explainable Artificial Intelligence.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Their research interests lie at the intersection of applied machine learning, computational mathematics, and blockchain technology in fintech. They have made significant contributions through publications in top-tier AI conferences, including ICLR, NeurIPS, AAAI, and CIKM, as well as prestigious journals in computational mathematics and fintech.

IMPACT AND INFLUENCE 🌟

The individual has played a pivotal role in enhancing the understanding of machine learning models and their applicability in real-world financial scenarios. Their work on adversarial attacks in deep neural networks and the development of explainable AI frameworks has positioned them as a thought leader in the field, influencing both academic and industrial practices.

ACADEMIC CITES 📖

Their groundbreaking research has been recognized in multiple high-impact venues, highlighting their innovative approaches to complex problems in fintech. Notable publications include works on adversarial defenses, counterfactual explanations, and recommendation systems, reflecting a robust commitment to advancing knowledge in AI and fintech.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

As a Chartered Fintech Professional and a member of various academic committees, this individual continues to contribute to the fintech community. Their involvement in organizing the Global Web3 Eco Innovation Summit 2022 illustrates their dedication to fostering innovation and collaboration in the fintech space. Looking ahead, they aim to further bridge the gap between academia and industry, shaping the future of fintech through research and education.

TOP NOTED PUBLICATIONS 📖

Stable neural ode with lyapunov-stable equilibrium points for defending against adversarial attacks
    • Authors: Q. Kang, Y. Song, Q. Ding, W. P. Tay
    • Journal: Advances in Neural Information Processing Systems
    • Year: 2021
Non-polynomial Spline Method for Time-fractional Nonlinear Schrödinger Equation
    • Authors: Q. Ding, P. J. Y. Wong
    • Journal: 15th International Conference on Control, Automation, Robotics and …
    • Year: 2018
A hybrid bandit framework for diversified recommendation
    • Authors: Q. Ding, Y. Liu, C. Miao, F. Cheng, H. Tang
    • Journal: Proceedings of the AAAI Conference on Artificial Intelligence
    • Year: 2021
Quintic non-polynomial spline for time-fractional nonlinear Schrödinger equation
    • Authors: Q. Ding, P. J. Y. Wong
    • Journal: Advances in Difference Equations
    • Year: 2020
A survey on decentralized autonomous organizations (DAOs) and their governance
    • Authors: Q. Ding, D. Liebau, Z. Wang, W. Xu
    • Journal: World Scientific Annual Review of Fintech
    • Year: 2023
The skyline of counterfactual explanations for machine learning decision models
    • Authors: Y. Wang, Q. Ding, K. Wang, Y. Liu, X. Wu, J. Wang, Y. Liu, C. Miao
    • Journal: Proceedings of the 30th ACM International Conference on Information …
    • Year: 2021

Gebeyehu Belay Gebremeskel | Machine Learning | Editorial Board Member

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Assoc Prof Dr. Gebeyehu Belay Gebremeskel | Machine Learning | Editorial Board Member

Assoc Prof Dr. Gebeyehu Belay Gebremeskel  at  Bahir Dar University, Ethiopia

👨‍🎓 Profiles

🌟 Early Academic Pursuits

Dr. Gebeyehu Belay Gebremeskel’s academic journey began at Alemaya University in Dire Dawa, Ethiopia, where he earned his Bachelor of Science in Computer Science in July 1991. His quest for advanced knowledge led him to London South Bank University in England, where he completed a Master of Science in Advanced Information Technology in January 2001. Under the guidance of Professor Ddembe Williams, he delved into System Dynamics Modeling and Decision Science. Dr. Gebremeskel’s pursuit of deeper expertise continued with a Ph.D. from Chongqing University in China, culminating in June 2013. His dissertation, supervised by Professor Zhongshi He, focused on the integration of Data Mining Algorithms and Multi-Agent Systems with Business Intelligence.

💼 Professional Endeavors

Dr. Gebeyehu’s professional career is distinguished by his impactful roles at Bahir Dar University’s Institute of Technology. As an Associate Professor, he has been instrumental in program accreditation, international conference organization, and curriculum development. His expertise has been further honed through a postdoctoral fellowship at Chongqing University’s College of Automation, focusing on machine learning, big data analytics, and intelligent systems. His commitment to excellence is reflected in his contributions to academic and research training, including programs in GIS, web design, and networking.

🔬 Contributions and Research Focus

Dr. Gebeyehu’s research spans several cutting-edge areas within computer science and engineering. His work in Big Data Analytics emphasizes optimization and precision in performance. In Artificial Intelligence and Machine Learning, he explores neural networks, genetic algorithms, and support vector machines, contributing to advancements in intelligent systems and fault diagnosis. His research in Data Mining includes pattern recognition, outlier detection, and intelligent data systems. Additionally, his focus on Intelligent Systems and Agent Technology involves developing algorithms for multi-agent systems and enhancing system intelligence.

🏆 Accolades and Recognition

Dr. Gebeyehu has received significant recognition for his contributions to academia and research. His roles as conference co-chair and technical program chair for international events like ICAST 2018, 2019, and 2020 highlight his leadership and influence in the field. His research publications in renowned journals, such as the International Journal of Data Science and Analytics, further underscore his impact. His work on big data analytics and neural network models has been widely acknowledged and respected within the academic community.

🌍 Impact and Influence

Dr. Gebeyehu’s influence extends across both academic and practical domains. His research has advanced knowledge in intelligent transportation systems and smart environments. His curriculum development and program accreditation efforts at Bahir Dar University have elevated the quality of education and research opportunities. By mentoring postgraduate students and leading international workshops, Dr. Gebeyehu has significantly impacted the field of computer science and engineering, shaping the future of many students and researchers.

🌟 Legacy and Future Contributions

Dr. Gebeyehu Belay Gebremeskel’s legacy is marked by his pioneering research, extensive teaching experience, and leadership in academia. His contributions to machine learning, big data analytics, and intelligent systems have set a high standard in the field. As he continues to explore new research avenues and educational initiatives, Dr. Gebeyehu is poised to make further advancements and impact future generations of researchers and practitioners. His dedication ensures that his influence will be felt long into the future.

📖 Publications

Architecture and optimization of data mining modeling for visualization of knowledge extraction: Patient safety care

Hend ALnajjar | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Hend ALnajjar, Artificial Intelligence, Best Researcher Award

Assoc Prof Dr. Hend ALnajjar at king Saud bin Abdulaziz for health science, Saudi Arabia

Professional Profile

Scopus Profile
Orcid  Profile
Research Gate Profile
Google Scholar Profile

🌟Summary

Dr. Hend Abdu Alnajjar is an accomplished Associate Professor in Pediatric Nursing at the College of Nursing–Jeddah, King Saud bin Abdulaziz University for Health Sciences. With a robust educational background including a Ph.D. in Nursing from Manchester University and extensive experience in nursing education, she specializes in maternal and child health, healthcare quality, and academic leadership.

🎓Education

  • Doctor of Philosophy in Nursing, Manchester University, UK (November 2012)
  • MSc in Advanced Nursing Studies, Manchester University, UK (November 2008)
  • Master of Medical Education, College of Medicine, King Saud bin Abdulaziz University for Health Sciences (2017-2019)
  • Bachelor of Science in Nursing, King Abdulaziz University, Jeddah, KSA (September 2000)

💼 Professional Experience

Dr. Hend Abdu Alnajjar brings a wealth of expertise as an Associate Professor in Pediatric Nursing at the College of Nursing–Jeddah, King Saud bin Abdulaziz University for Health Sciences. With a distinguished career spanning leadership roles such as Dean of the College of Nursing – Jeddah and Associate Dean of Academic & Student Affairs, she has significantly contributed to advancing nursing education and healthcare quality in Saudi Arabia. Dr. Alnajjar’s leadership extends to extensive involvement in accreditation processes, curriculum development, and quality assurance initiatives, enhancing educational standards across multiple institutions. Her commitment to maternal and child health is underscored by her clinical background in neonatal intensive care units, further enriching her academic and practical contributions to the nursing profession.

🔬 Research Interests

Dr. Hend Abdu Alnajjar’s research interests are focused on pivotal areas within nursing and healthcare. Her primary scholarly pursuits revolve around maternal and child health, where she explores innovative approaches to improve healthcare outcomes for mothers and children. Additionally, her research encompasses nursing education, aiming to enhance teaching methodologies and curriculum frameworks to foster competent nursing professionals. Dr. Alnajjar is also passionate about healthcare quality, investigating strategies to optimize patient care delivery and safety within clinical settings. Her academic leadership in these domains reflects a commitment to advancing nursing practice and education both locally and globally.

📖 Publication Top Noted

Article title: Digital proficiency: assessing knowledge, attitudes, and skills in digital transformation, health literacy, and artificial intelligence among university nursing students

    • Authors: Ebtsam Aly Abou Hashish, Hend Alnajjar
    • Journal: BMC Medical Education
    • Volume: 24
    • Pages: 508
    • Year: 2024

Article title: Perception of the accreditation of the National Commission for Academic Accreditation and assessment at different health colleges in Jeddah, Saudi Arabia

    • Authors:Ali S Al-Shareef, Mansour A AlQurashi, Azza Al Jabarti, Hend Alnajjar, Ahmad A Alanazi, Mohamed Almoamary, Bader Shirah, Khalid Alqarni
    • Journal: Cureus
    • Volume: 15
    • Year: 2023

Article title: Managerial power bases and its relationship to influence tactics and conflict management styles: Bedside nurses’ perspective

    • Authors: Ebtsam Abou Hashish, Hend Alnajjar, Arwa Al Saddon
    • Journal: Worldviews on Evidence‐Based Nursing
    • Volume: 20
    • Issue: 5
    • Year: 2023

Article title: Exploring the relationship between leadership and conflict management styles among nursing students

    • Authors: Hend Alnajjar, Ebtsam Abou Hashish
    • Journal: Nursing management
    • Volume: 29
    • Issue: 3
    • Year: 2022

Article title: Academic ethical awareness and moral sensitivity of undergraduate nursing students: assessment and influencing factors

    • Authors: Hend Abdu Alnajjar, PhD, Ebtsam Aly Abou Hashish, PhD
    • Journal: SAGE open nursing
    • Volume: 7
    • Year: 2021