Youmna Iskandarani | Machine Learning | Best Researcher Award

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Ms. Youmna Iskandarani l Machine Learning | Best Researcher Award

American University of Beirut, Lebanon

Author Profile

Orcid

EARLY ACADEMIC PURSUITS 🎓

Youmna Iskandarani’s academic journey laid a robust foundation for her career in food science and technology. She earned her Bachelor’s degree in Dietetics and Clinical Nutrition Services from Lebanese International University, followed by a Bachelor of Applied Science in Food Science and Technology. Building on this knowledge, she pursued a Master of Science in Food Science and Technology, which further refined her expertise in food processing, safety, and research. During her studies, she also explored economics, expanding her understanding of the broader socio-economic factors influencing food systems.

PROFESSIONAL ENDEAVORS 💼

Youmna’s professional trajectory spans over a decade and includes a wealth of experience in community development, food technology, and business development. As the founder of Ossah Taybeh, a food heritage initiative, she has demonstrated her leadership in promoting sustainable food practices. Additionally, her role as a business development consultant and food expert for various organizations, including the World Food Programme (WFP) and UNDP, highlights her expertise in improving the socio-economic conditions of small and medium enterprises (SMEs) in Lebanon. Youmna has also worked with institutions like the American University of Beirut, where she contributed to food safety training, product development, and innovative food solutions. Her consulting work for international organizations and governments underscores her technical expertise in food processing, quality control, and business strategy.

CONTRIBUTIONS AND RESEARCH FOCUS  On  Machine Learning🔬

Throughout her career, Youmna has been at the forefront of several groundbreaking projects in food science and technology. She has published significant research, including studies on ADHD and nutrition, the production procedures of labneh anbaris (a traditional Lebanese yogurt), and food security. Her research in food safety, quality control, and food product development, especially in the dairy sector, has made substantial contributions to understanding the physicochemical properties of traditional food products. Additionally, her work in food safety, particularly related to cross-contamination prevention and dairy production processes, has helped improve the standards of food processing in Lebanon and beyond.

IMPACT AND INFLUENCE 🌍

Youmna’s impact extends far beyond her professional roles; she has become a key figure in advancing food safety and quality practices in Lebanon. As a consultant and trainer, she has helped develop and implement strategies that enhance the livelihoods of farmers and small business owners in rural and urban communities. Her work with the International Labour Organization (ILO) and various NGOs has supported entrepreneurial initiatives aimed at creating sustainable economic opportunities. Her efforts in building the capacity of SMEs and promoting socially impactful business practices have earned her recognition as a leader in both the food industry and community development sectors. Moreover, her role as a mentor and trainer for aspiring entrepreneurs has inspired many to develop their own successful ventures.

ACADEMIC CITATIONS AND RECOGNITION 🏅

Youmna’s research has been widely cited in academic circles, contributing to the fields of food science and public health. Her work on the physicochemical properties of labneh anbaris and her studies in the areas of food security and nutrition have been valuable in shaping food safety protocols and product development in Lebanon. She is recognized for her expertise in food technology and food safety, as well as for her commitment to advancing the quality and sustainability of food production systems in Lebanon and the broader region. Her contributions have made her a sought-after consultant and expert in various food safety and quality assurance projects.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Looking forward, Youmna Iskandarani is poised to continue making meaningful contributions to the fields of food science, business development, and community empowerment. Her passion for sustainability and rural development, combined with her technical expertise in food safety and quality assurance, will continue to guide her efforts in enhancing food systems and promoting socio-economic growth. Her vision for the future includes empowering more women and SMEs in the agri-food sector, improving the resilience of local food production systems, and advocating for healthier, safer, and more sustainable food practices. Youmna’s legacy will be built on her commitment to food security, innovation, and the betterment of her community and the global food industry.

 Top Noted Publications 📖

Microbial Quality and Production Methods of Traditional Fermented Cheeses in Lebanon

Authors: Mabelle Chedid, Houssam Shaib, Lina Jaber, Youmna El Iskandarani, Shady Kamal Hamadeh, Ivan Salmerón
Journal: International Journal of Food Science
Year: 2025

Machine Learning Method (Decision Tree) to Predict the Physicochemical Properties of Premium Lebanese Kishk Based on Its Hedonic Properties

Authors: Ossama Dimassi, Youmna Iskandarani, Houssam Shaib, Lina Jaber, Shady Hamadeh
Journal: Fermentation
Year: 2024

Development and Validation of an Indirect Whole-Virus ELISA Using a Predominant Genotype VI Velogenic Newcastle Disease Virus Isolated from Lebanese Poultry

Authors: Houssam Shaib, Hasan Hussaini, Roni Sleiman, Youmna Iskandarani, Youssef Obeid
Journal: Open Journal of Veterinary Medicine
Year: 2023

Effect of Followed Production Procedures on the Physicochemical Properties of Labneh Anbaris

Authors: Ossama Dimassi, Youmna Iskandarani, Raymond Akiki
Journal: International Journal of Environment, Agriculture and Biotechnology
Year: 2020

Production and Physicochemical Properties of Labneh Anbaris, a Traditional Fermented Cheese Like Product, in Lebanon

Authors: Ossama Dimassi, Youmna Iskandarani, Michel Afram, Raymond Akiki, Mohamed Rached
Journal: International Journal of Environment, Agriculture and Biotechnology
Year: 2020

Feng Hu | Multi-modal feature recognition | Best Researcher Award

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Assoc Prof Dr. Feng Hu l Multi-modal feature recognition | Best Researcher Award

Communication University of China, China

Author Profile

Scopus

Early Academic Pursuits 🎓

Assoc. Prof. Dr. Feng Hu’s academic journey began with a deep interest in communication and information systems. He earned his Ph.D. in Communication and Information Systems from the prestigious Communication University of China (CUC), Beijing, in 2013. This educational foundation set the stage for his distinguished career in the fields of wireless communications, media convergence, and related technologies, shaping his future research and academic contributions.

Professional Endeavors and Contributions 🌐

Dr. Feng Hu is a prominent figure in the domain of 5G/6G wireless communications, and his professional journey has been marked by several key roles. Since December 2018, he has been an Associate Professor at Communication University of China and a master tutor, where he plays a significant role in mentoring future engineers and researchers. He has also been an active member of the Working Group of Radio, Film, and Television Administration for Wireless Interactive Radio and Television, as well as a member of the Working Group of 5G Broadcast. These positions have allowed him to contribute to the development and regulation of cutting-edge technologies in the media and communications sector.

Research Focus and Impact 🔬

Dr. Hu’s research interests lie in the development of transmitting and receiving techniques for 5G and 6G wireless communications. His work focuses on optimizing wireless communication systems, utilizing machine learning, and exploring optimization theory to enhance the efficiency and performance of modern communication technologies. His research has significant implications for the advancement of wireless communication systems, contributing to the global transition to next-generation technologies and improving communication capabilities in various sectors.

Technical Skills and Expertise ⚙️

Dr. Hu is highly skilled in the areas of wireless communications, machine learning, and optimization theory. His expertise includes developing novel algorithms and techniques for 5G/6G systems, addressing challenges in data transmission, signal processing, and system optimization. He is proficient in applying advanced mathematical models and machine learning approaches to improve communication systems’ performance, reliability, and security, making him a key player in advancing the state-of-the-art in wireless communications.

Teaching Experience and Mentorship 🍎

As an Associate Professor and master tutor, Dr. Hu is deeply involved in shaping the next generation of professionals in communication and information systems. He has taught a variety of undergraduate and graduate-level courses, imparting his knowledge in wireless communications, machine learning, and optimization. His mentorship extends beyond the classroom, guiding students in research and academic pursuits, while fostering a culture of innovation and critical thinking in the field of communications.

Legacy and Future Contributions 🌱

Dr. Hu’s legacy is rooted in his pioneering work in the development of 5G/6G wireless communication systems and his significant contributions to the academic and professional communities. Looking ahead, he aims to continue pushing the boundaries of wireless communication technologies, with a particular focus on optimizing next-generation communication networks and integrating machine learning approaches to improve system efficiencies. His future contributions will likely influence both academic research and practical implementations in the rapidly evolving fields of wireless communications and media convergence.

Academic Citations and Recognition 🏆

Dr. Feng Hu’s research has garnered recognition in top-tier academic journals and conferences in the fields of communication systems and wireless technology. His work has not only contributed to the scientific community but has also influenced industry practices and standards in wireless communication. He continues to be a sought-after figure in academic circles, providing valuable insights into the development of 5G/6G systems and machine learning applications in communications.

Professional Affiliations and Leadership 🌍

Dr. Hu is an active member of several esteemed organizations, including IEEE and the Society of Communications, where he holds the prestigious title of Senior Member. His involvement in key working groups related to wireless interactive radio and television and 5G broadcast further highlights his leadership in shaping the future of communication technologies. These affiliations enhance his ability to drive impactful research and contribute to the global dialogue on the future of communication systems.

Future Outlook and Innovation 🚀

With his vast expertise in wireless communication systems and emerging technologies, Dr. Hu’s future endeavors will focus on leading innovations in 6G communication systems, integrating artificial intelligence and machine learning to enhance system performance, and tackling the challenges posed by next-generation wireless networks. His ongoing research will play a critical role in shaping the future of global communication, advancing both academic theory and practical applications in the field.

 Top Noted Publications 📖

SDDA: A progressive self-distillation with decoupled alignment for multimodal image–text classification

Authors: Chen, X., Shuai, Q., Hu, F., Cheng, Y.
Journal: Neurocomputing
Year: 2025

EmotionCast: An Emotion-Driven Intelligent Broadcasting System for Dynamic Camera Switching

Authors: Zhang, X., Ba, X., Hu, F., Yuan, J.
Journal: Sensors
Year: 2024

 Asymptotic performance of reconfigurable intelligent surface assisted MIMO communication for large systems using random matrix theory

Authors: Hu, F., Zhang, H., Chen, S., Zhang, J., Feng, Y.
Journal: IET Communications
Year: 2024

Real-Time Multi-Service Adaptive Resource Scheduling Algorithm Based on QoE

Authors: Li, W., Li, S., Hu, F., Yin, F.
Conference: 2024 IEEE 12th International Conference on Information and Communication Networks, ICICN 2024
Year: 2024

5G RAN Slicing Resource Allocation Based on PF/M-LWDF

Authors: Hu, F., Qiu, J., Chen, A., Yang, H., Li, S.
Conference: 2024 4th International Conference on Computer Communication and Artificial Intelligence, CCAI 2024
Year: 2024

Kuo-Ching Ying | Metaheuristics | Best Researcher Award

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Prof Dr. Kuo-Ching Ying | Metaheuristics | Best Researcher Award

National Taipei University of Technology, Taiwan

Author Profiles

orcid

Scopus

👨‍🏫 Current Position and Leadership Roles

Prof. Dr. Kuo-Ching Ying is currently a Distinguished Professor in the Department of Industrial Engineering and Management at National Taipei University of Technology, Taiwan. In addition to his role as a faculty member, he also serves as the Associate Dean of the College of Management and Vice Director of the EMBA Program at the university. His leadership positions reflect his deep commitment to advancing education and research in the fields of industrial engineering and management.

🎓 Early Academic Pursuits and Education

Prof. Ying’s academic journey began with a Master’s degree in Industrial Management from the National Taiwan University of Science and Technology in 1992. His academic pursuits culminated in a Ph.D. in Industrial Management from the same institution in 2003. His educational background provided the foundation for his current expertise in operations scheduling, combinatorial optimization, and various aspects of industrial management.

💼 Professional Endeavors and Editorial Contributions

Prof. Ying has significantly contributed to the academic community as an editor for several prestigious journals. He has been serving as an editor for Advances in Industrial Engineering and Management since December 2012 and has held editorial roles for other journals like IEEE Access (since 2018), Applied Sciences (since 2021), and American Journal of Operations Management and Information Systems (since 2020). His editorial work spans across more than 10 journals, underscoring his significant involvement in shaping the direction of research in industrial management and optimization fields.

🔬 Contributions and Research Focus

Prof. Ying’s primary research interests revolve around operations scheduling, combinatorial optimization, and industrial management. He has authored more than 130 academic papers in top-tier international journals such as IEEE Access, Computers and Operations Research, Applied Soft Computing, and European Journal of Operational Research. His research delves into innovative approaches to solving complex problems in industrial settings, particularly in operations management, manufacturing, and logistics.

🌍 Impact and Influence in Academia

Through his extensive research contributions and editorial roles, Prof. Ying has become a recognized figure in the fields of industrial engineering and management. His work has been cited numerous times in academic research, demonstrating his influence in advancing knowledge in operations scheduling and combinatorial optimization. His efforts have led to advancements in how industries manage production, operations, and logistics.

📚 Academic Citations and Recognition

Prof. Ying’s scholarly output has earned him wide recognition within the academic community. His work has been cited extensively across numerous journals, reflecting the importance and impact of his research. The high citation rate of his publications is a testament to the relevance and applicability of his work in both academic and industrial contexts. He is widely regarded as a thought leader in industrial management research.

💡 Technical Skills and Expertise

Prof. Ying possesses strong technical skills in areas such as operations research, optimization algorithms, and industrial management. He is particularly skilled in developing models and techniques for solving complex optimization problems related to manufacturing, logistics, and scheduling. His expertise in artificial intelligence and computational techniques further enhances his ability to contribute to cutting-edge research in these fields.

👩‍🏫 Teaching Experience and Mentorship

Prof. Ying has been a mentor to numerous students in the Department of Industrial Engineering and Management at National Taipei University of Technology. As an educator, he has significantly shaped the careers of many professionals in industrial management. His teaching philosophy emphasizes the application of theory to real-world problems, preparing students to tackle challenges in operations management and optimization. His experience in teaching and mentoring plays a key role in nurturing the next generation of scholars and industry leaders.

🌱 Legacy and Future Contributions

Prof. Ying’s legacy is already well established through his substantial academic achievements, his leadership in educational programs, and his continued contributions to the field. Looking ahead, he is likely to continue shaping the future of industrial engineering research, particularly in optimizing industrial processes and the integration of new technologies. His future contributions will likely focus on further advancing operations research, combinatorial optimization, and artificial intelligence applications in industrial contexts.

📖 Top Noted Publications 

Reinforcement Learning-based Alpha-list Iterated Greedy for Production Scheduling
  • Authors: Kuo-Ching Ying, Pourya Pourhejazy, Shih-Han Cheng
    Journal: Intelligent Systems with Applications
    Year: 2024
Minimizing makespan in two-stage assembly additive manufacturing: A reinforcement learning iterated greedy algorithm
  • Authors: Kuo-Ching Ying, Shih-Wei Lin
    Journal: Applied Soft Computing
    Year: 2023
Meta-Lamarckian-based iterated greedy for optimizing distributed two-stage assembly flowshops with mixed setups
  • Authors: Pourya Pourhejazy, Chen-Yang Cheng, Kuo-Ching Ying, Nguyen Hoai Nam
    Journal: Annals of Operations Research
    Year: 2023
Supply chain-oriented permutation flowshop scheduling considering flexible assembly and setup times
  • Authors: Kuo-Ching Ying, Pourya Pourhejazy, Chen-Yang Cheng, Ren-Siou Syu
    Journal: International Journal of Production Research
    Year: 2023
Adjusted Iterated Greedy for the optimization of additive manufacturing scheduling problems
  • Authors: Kuo-Ching Ying, Fruggiero, F., Pourhejazy, P., Lee, B.-Y.
    Journal: Expert Systems with Applications
    Year: 2022

Jing An | Artificial Intelligence | Best Researcher Award

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Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

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