Giuliana Ramella | Artificial Intelligence | Best Researcher Award

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Dr. Giuliana. Ramella | Artificial Intelligence | Best Researcher Award

National Research Council, Italy

Professional Profile 👨‍🎓

Scopus Profile

Orcid Profile

Research Gate Profile

Early Academic Pursuits 🎓

Dr. Giuliana Ramella embarked on her academic journey with a strong foundation in Physics, specializing in Cybernetics, from the University of Naples “Federico II”, Italy, where she obtained her Laurea degree in 1990. Her early career was distinguished by a fellowship granted by the Italian National Research Council (CNR) at the Institute of Cybernetics “E. Caianiello”, which marked the beginning of her deep engagement with interdisciplinary research. Her academic background was further enriched by participation in several international and national schools, covering topics from biophysics to machine vision, which laid the groundwork for her future research endeavors.

Professional Endeavors 🧑‍🔬

Dr. Ramella’s professional career at the CNR has spanned decades, beginning in 1991 with a fellowship at the Institute of Cybernetics, now known as the Institute of Applied Sciences and Intelligent Systems (CNR-ISASI). Over the years, she transitioned into permanent research roles, contributing significantly to numerous research projects. Her professional milestones include being a visiting researcher at LIAMA (Sino-French Laboratory) in Beijing, China, and overseeing major research initiatives such as those focused on image processing and the conservation of cultural heritage.

Contributions and Research Focus 🔬

Dr. Ramella’s research spans multiple fields, including image processing, artificial intelligence, neurosciences, and cultural heritage conservation. Notable contributions include leadership in projects such as CNR-IAC-CNR DIT.AD021.077 (focused on color image processing) and the Campania Imaging Infrastructure for Research in Oncology. Her work blends theoretical and practical applications, particularly in the intersection of machine learning and image analysis, demonstrating her commitment to advancing computational methods in complex scientific domains.

Impact and Influence 🌍

Dr. Ramella has made a significant impact both in Italy and internationally, particularly in the fields of biophysics, neurosciences, and cultural heritage preservation. She has led several high-profile projects, influencing the development of automated systems for monitoring and diagnosing cultural heritage, as well as data analysis systems for oncology research. Her leadership in educational coordination has also contributed to the professional development of individuals in specialized fields, including image and data management.

Academic Citations and Scholarly Recognition 📚

Throughout her career, Dr. Ramella has built a robust academic reputation, frequently cited for her work in machine learning frameworks like Pytorch, TensorFlow, and Keras, as well as her contributions to computer vision. Her involvement in international workshops and conferences further underscores her standing as a thought leader in the scientific community. Additionally, her research has had a profound effect on the fields of visual perception and neuroscience, solidifying her as a key figure in these interdisciplinary areas.

Technical Skills and Expertise 💻

Dr. Ramella is highly skilled in a range of programming languages, including Matlab, C/C++, and Python, which are essential tools for her work in data analysis and machine learning. She has a strong command over popular machine learning frameworks like Pytorch, TensorFlow, and Keras, which she applies to advanced research in image processing, signal analysis, and high-dimensional data modeling. Her technical expertise is fundamental to her contributions to automated systems in the analysis of cultural artifacts and medical imaging.

Teaching Experience 🍎

In addition to her research, Dr. Ramella has played an essential role in educational coordination. She co-led specialist courses for unemployed individuals and workers in mobility, aimed at developing technical skills for sectors like image management and building heritage monitoring. Her role in shaping the professional development of students in the fields of image analysis and information technology has left a lasting impact on both the academic and professional communities.

Legacy and Future Contributions 🔮

Looking ahead, Dr. Ramella’s legacy is poised to continue making waves in the fields of artificial intelligence and machine learning, especially in the areas of healthcare, cultural heritage conservation, and data-driven methodologies. Her ongoing involvement in projects like the Agritech research program, funded by the European Union through Next Generation EU, speaks to her future aspirations to contribute to cutting-edge research and technological advancements. Dr. Ramella’s future work promises to leave an indelible mark on interdisciplinary fields, continuing her legacy of innovation and impact across global scientific communities.

 

Top Noted Publications 📖

An Open Image Resizing Framework for Remote Sensing Applications and Beyond

Authors: Occorsio, D., Ramella, G., Themistoclakis, W.
Journal: Remote Sensing
Year: 2023

Image Scaling by de la Vallée-Poussin Filtered Interpolation

Authors: Occorsio, D., Ramella, G., Themistoclakis, W.
Journal: Journal of Mathematical Imaging and Vision
Year: 2023

Filtered Polynomial Interpolation for Scaling 3D Images

Authors: Occorsio, D., Ramella, G., Themistoclakis, W.
Journal: Electronic Transactions on Numerical Analysis
Year: 2023

 Lagrange–Chebyshev Interpolation for Image Resizing

Authors: Occorsio, D., Ramella, G., Themistoclakis, W.
Journal: Mathematics and Computers in Simulation
Year: 2022

Saliency-based Segmentation of Dermoscopic Images Using Colour Information

Author: Ramella, G.
Journal: Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization
Year: 2022

Yun Xing | Computer Vision | Best Researcher Award

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Mr. Yun Xing | Computer Vision | Best Researcher Award

Mr. Yun Xing at The First Affiliated Hospital of Xi’an Jiaotong University, China

👨‍🎓Professional Profile

🎓 Education and Academic Background

I am currently a second-year Ph.D. student at VI-Lab, Nanyang Technological University (NTU), under the supervision of Prof. Shijian Lu. I received my B.S. degree in Biomedical Engineering and Instrument Science from Zhejiang University in 2021, where I worked under the guidance of Prof. Hong Zhou. Prior to my Ph.D., I completed my Master’s in Artificial Intelligence at NTU (2021–2022). My research interests primarily focus on vision-language pre-training and foundation model adaptation.

🔬 Research Interests

My research revolves around cutting-edge topics in vision-language pre-training and the adaptation of foundation models. I am particularly interested in methods that enable models to transfer knowledge effectively across different domains, such as few-shot learning, cross-domain adaptation, and improving model robustness in complex vision-language tasks.

🏆 Achievements and News

In recent years, I have been fortunate to have several papers accepted at top-tier conferences. These include NeurIPS 2024, ECCV 2024, CVPR 2024, and NeurIPS 2023, marking significant milestones in my academic journey. Notably, my work on object hallucination mitigation and segmentation adaptation has received considerable attention in the community.

🏅 Awards and Honors

Throughout my academic journey, I have received various recognitions for my contributions to research. These include the Outstanding Graduate Award from Zhejiang University in 2021, as well as the Academic Excellence Award (2018, 2019) and Academic Progress Award (2019) from the same institution.

💻 Service and Teaching

As an active member of the academic community, I contribute as a conference reviewer for prominent venues such as CVPR, ICML, ECCV, and NeurIPS 2024, where I was honored to be selected as one of the Top Reviewers at NeurIPS. Additionally, I am involved in teaching and mentoring at NTU. In Spring 2024, I will be assisting with the SC1015: Introduction to Data Science and Artificial Intelligence course.

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

 

Shymon Islam | Natural Language Processing | Best Researcher Award

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Mr. Md. Shymon Islam,Natural Language Processing,  Best Researcher Award

 Shymon Islam at North Western University, Khulna Bangladesh

Professional Profile:

Google Scholar Profile
Research Gate

Summary:

Mr. Md. Shymon Islam is a dedicated professional with a Master of Science in Engineering in Computer Science and Engineering (CSE) from Khulna University, Bangladesh. With a keen interest in education and research, he aspires to contribute significantly to the advancement of Computer Science and Engineering. His expertise lies in Machine Learning, Data Mining, Image Processing, and Artificial Intelligence.

👩‍🎓Education:

Mr. Md. Shymon Islam holds a Master of Science in Engineering in Computer Science and Engineering (CSE) from Khulna University, Bangladesh, achieved with a remarkable CGPA of 4.00, earning the distinction. He previously obtained his Bachelor of Science in Engineering in CSE from the same institution, graduating with a notable CGPA of 3.90, also with distinction. His academic journey reflects his dedication to excellence and his passion for advancing in the field of Computer Science and Engineering.

Professional Experience:

With three years of experience as both a research scholar and faculty member at Khulna University, Md. Shymon Islam has demonstrated his dedication to academia and research. His role has involved not only teaching but also actively contributing to the body of knowledge in Computer Science and Engineering. He has published multiple research papers in prestigious journals and conferences, focusing on areas such as sentiment analysis, optimization algorithms, and document classification. His tenure showcases his commitment to advancing the field through rigorous academic inquiry and practical application.

Research Interest :

Mr. Md. Shymon Islam’s research interests lie at the intersection of cutting-edge technologies in Computer Science and Engineering. He is particularly passionate about exploring areas such as Machine Learning, Data Mining, Image Processing, and Artificial Intelligence. With a keen interest in both theoretical advancements and practical applications, he seeks to contribute innovative solutions to real-world problems across these domains. His interdisciplinary approach and curiosity drive his quest for knowledge and discovery in the ever-evolving landscape of technology.

Publication Top Noted: