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

Omar Haddad | Artificial Intelligence | Best Researcher Award

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Dr. Omar Haddad l Artificial Intelligence | Best Researcher Award

MARS Research Lab, Tunisia

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Omar Haddad began his academic journey with a solid foundation in mathematics, earning his Bachelor in Mathematics from Mixed High School, Tataouine North, Tunisia, in 2008. Building on this, he pursued a Fundamental License in Computer Science at the Faculty of Sciences of Monastir, University of Monastir, Tunisia, graduating with honors in 2012. He further honed his skills in advanced topics through a Research Master in Computer Science specializing in Modeling of Automated Reasoning Systems (Artificial Intelligence) at the same institution, completing his thesis on E-Learning, NLP, Map, and Ontology in 2016. This laid the groundwork for his doctoral studies in Big Data Analytics for Forecasting Based on Deep Learning, which he completed with highest honors at the Faculty of Economics and Management of Sfax, University of Sfax, Tunisia, in 2023.

💼 Professional Endeavors

Currently, Dr. Haddad is an Assistant Contractual at the University of Sousse, Tunisia, where he contributes to the academic and technological growth of the institution. He is a dedicated member of the MARS Research Laboratory at the University of Sousse, where he collaborates on cutting-edge projects in Artificial Intelligence and Big Data Analytics. His professional expertise extends to teaching across various levels, including preparatory, license, engineer, and master levels, with over 2,000 hours of teaching experience in state and private institutions.

📚 Contributions and Research Focus

Dr. Haddad’s research spans several transformative domains, including:

  • Artificial Intelligence (AI) and its application in solving complex problems.
  • Machine Learning (ML) and Deep Learning (DL) for advanced predictive modeling.
  • Generative AI and Large Language Models (LLMs) for innovation in Natural Language Processing (NLP).
  • Big Data Analytics for informed decision-making and forecasting.
  • Computer Vision for visual data interpretation and insights.

He has published three significant contributions in Q1 and Q2 journals and participated in Class C conferences, highlighting his commitment to impactful and high-quality research.

🌟 Impact and Influence

As a peer reviewer for prestigious journals like The Journal of Supercomputing, Journal of Electronic Imaging, SN Computer Science, and Knowledge-Based Systems, Dr. Haddad ensures the integrity and quality of academic contributions in his field. His work has influenced a diverse range of domains, from computer science education to applied AI, establishing him as a thought leader in his areas of expertise.

🛠️ Technical Skills

Dr. Haddad possesses a robust set of technical skills, including:

  • Proficiency in Deep Learning frameworks and Big Data tools.
  • Expertise in programming languages such as Python and C.
  • Knowledge of Database Engineering and algorithms.
  • Application of Natural Language Processing (NLP) in academic and industrial projects.

👨‍🏫 Teaching Experience

Dr. Haddad has an extensive teaching portfolio, covering a wide range of topics:

  • Database Engineering, Algorithms, and Programming, taught across license and engineer levels.
  • Advanced topics such as Big Data Frameworks, Foundations of AI, and Object-Oriented Programming.
  • Specialized courses on Information and Communication Technologies in Teaching and Learning.

His dedication to education is evident in his ability to adapt teaching strategies to different academic levels and institutional needs.

🏛️ Legacy and Future Contributions

Dr. Haddad’s legacy lies in his ability to bridge academia and industry through innovative research and teaching. As he continues to expand his expertise in Generative AI and LLMs, his future contributions will likely shape the next generation of intelligent systems and predictive analytics. His goal is to inspire students and researchers to harness the transformative potential of AI and Big Data to address global challenges.

🌐 Vision for the Future

Dr. Omar Haddad envisions a future where AI and Big Data technologies are seamlessly integrated into various sectors to enhance decision-making, foster innovation, and empower global communities. By combining his teaching, research, and technical skills, he aims to leave a lasting impact on the academic and technological landscape.

📖 Top Noted Publications
Toward a Prediction Approach Based on Deep Learning in Big Data Analytics
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Neural Computing and Applications
    • Year: 2022
A Survey on Distributed Frameworks for Machine Learning Based Big Data Analysis
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Proceedings of the 21st International Conference on New Trends in Intelligent Software Systems
    • Year: 2022
An Intelligent Sentiment Prediction Approach in Social Networks Based on Batch and Streaming Big Data Analytics Using Deep Learning
    • Authors: O. Haddad, F. Fkih, M.N. Omri
    • Journal: Social Network Analysis and Mining
    • Year: 2024
Big Textual Data Analytics Using Transformer-Based Deep Learning for Decision Making
    • Authors: O. Haddad, M.N. Omri
    • Journal: Proceedings of the 16th International Conference on Computational Collective Intelligence
    • Year: 2024

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