Kamil Baderddine | Bioinformatics | Best Researcher Award

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Dr. Kamil Baderddine | Bioinformatics | Best Researcher Award

Dr. Kamil Baderddine | Optimization – Université de Technologie de Compiègne | Lebanon

Dr. Kamil Baderddine is a dedicated Artificial Intelligence expert with a proven ability to blend academic excellence and practical implementation. With extensive experience in teaching, research, and software development, he has consistently demonstrated his ability to inspire students and innovate in AI-driven technologies. His multidisciplinary approach spans neural networks, biomedical signal processing, big data optimization, and natural language processing. Passionate about shaping the next generation of AI professionals, Dr. Baderddine continues to make significant contributions in both academic and applied research contexts.

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🎓 Education & Experience

Dr. Baderddine earned his Ph.D. in Artificial Intelligence from Sorbonne University in France (2018–2022), following a Master’s degree in Computer Science and a Bachelor of Science in Communications Technologies from the Lebanese University in Saida. His professional journey spans both academia and industry. He has served as a lecturer at several institutions including Notre Dame University, Lebanese International University, Arab Open University, and Lebanese University, teaching courses such as Artificial Intelligence, Web Development, Advanced C++, Operating Systems, and Java Programming. In the industry, he worked as a Senior PHP Developer at Layout International (2007–2018) and currently serves as an AI Consultant for SAWA GROUP, where he develops AI-based applications and manages server environments using CentOS.

📜 Professional Development

Dr. Baderddine brings hands-on experience with a wide array of programming languages and platforms including Python, Java, PHP, C++, and JavaScript. He is proficient in both front-end and back-end development, server-side debugging, and database technologies like MySQL and SQL Server. His expertise extends to using APIs (REST, SOAP), and development tools such as Agile and Scrum. He is especially skilled in configuring Linux environments, applying neural networks and deep learning models, and leveraging big data for intelligent system design.

🔬 Research Focus

His research explores the intersection of Artificial Intelligence and healthcare, particularly in analyzing uterine activity during pregnancy and labor using graph theory and deep learning. He also focuses on optimizing big data search engines and developing machine learning models for Arabic resume parsing and job matching. His notable publications include works in IRBM and Studies in Systems, Decision and Control, addressing neural network-based classification, biomedical synchronization, and AI-powered data systems.

🏆 Honors & Awards

Dr. Baderddine holds a doctorate from the prestigious Sorbonne University and has published multiple peer-reviewed articles that contribute to advancements in AI and healthcare technology. He has been entrusted with academic responsibilities across top Lebanese institutions and recognized for his ability to connect innovative research with real-world applications. His scholarly and professional accomplishments position him as a rising leader in the field of Artificial Intelligence.

📚 Selected Publications 

Title: Simulated uterine contractions: Graph theory and connectivity-based analysis of EHG signals

    • Authors: Kamil Bader Eldine, Noujoud Nader, Mohamad Khalil, Catherine Marque

    • Journal: Biomedical Engineering Advances

    • Year: 2025

Title: Optimizing Uterine Synchronization Analysis in Pregnancy and Labor Through Window Selection and Node Optimization

    • Authors: Kamil Bader El Dine, Noujoud Nader, Mohamad Khalil, Catherine Marque

    • Journal: IRBM

    • Year: 2024

Title: Uterine Synchronization Analysis During Pregnancy and Labor Using Graph Theory, Classification Based on Neural Network and Deep Learning

    • Authors: K.B. El Dine, N. Nader, M. Khalil, C. Marque

    • Journal: IRBM

    • Year: 2022

Radwa Rady | Biomedical Engineering | Best Researcher Award

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Dr. Radwa Rady | Biomedical Engineering | Best Researcher Award

Alexandria University | Egypt

PUBLICATION PROFILE

Scopus

Orcid

🌟 INTRODUCTION

Dr. Radwa Rady is a meticulous, bilingual professional with a broad range of skills in IT applications, biomedical engineering, and communication technologies. With her extensive expertise in both theoretical and practical aspects of biomedical technology, Dr. Rady has made significant contributions to academia, research, and industry. Fluent in Arabic and English, she is well-versed in effectively communicating complex technical concepts while also excelling at multitasking and problem-solving. Dr. Rady’s work is characterized by her dedication to innovation and academic excellence, seeking to create lasting contributions in the field of Biomedical Engineering, IT, and Electrical Communication.

🎓 EARLY ACADEMIC PURSUITS

Dr. Radwa’s journey into the world of academia and technology began at Alexandria University, where she earned her Bachelor of Engineering in Communication. This foundational education allowed her to delve deeper into subjects such as digital signal processing and biomedical devices. She continued to build on this knowledge with her Master’s degree in Biomedical Devices, focusing on digital signal processing techniques to analyze respiratory wheeze sounds in children. Her early education laid the groundwork for her extensive research and innovations in biomedical engineering, solidifying her as a dedicated scholar and researcher in the field.

💼 PROFESSIONAL ENDEAVORS

Dr. Radwa Rady’s professional career is marked by diverse roles across academia, research, and software development. From her tenure as a Software Developer at VP .Net, where she contributed to significant projects for the Water and Wastewater Authority and Cataract Hospital, to her current role as Assistant Professor at Inaya Medical Colleges in Riyadh, she has continually sought to bridge the gap between theoretical knowledge and real-world applications. As an instructor, Dr. Rady has taught a wide range of subjects, including digital signal processing, biomedical engineering, and programming. Her leadership skills extend beyond the classroom as she serves on several faculty committees and supervises graduate students’ final projects.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Rady’s research focuses on the intersection of biomedical engineering, digital signal processing, and neurofeedback treatments. One of her primary research endeavors is her thesis on “Quantitative EEG and Neurofeedback Treatment,” which aims to improve attention skills in children with ADHD through real-time EEG analysis and neurofeedback. Her work also extends to the field of respiratory wheeze sound analysis, where she developed a system to assist physicians in diagnosing respiratory conditions in children using digital signal processing. These innovative projects demonstrate Dr. Rady’s commitment to advancing medical technology and improving patient outcomes.

🌍 IMPACT AND INFLUENCE

Dr. Rady has made a significant impact through her involvement in both teaching and research. As an academic, she not only imparts knowledge to her students but also actively contributes to the academic community through workshops and lectures on emotional intelligence and ethical considerations in AI research. Her research, including the published papers and patent application related to EEG analysis for ADHD treatment, demonstrates her ability to influence both academic discourse and practical applications in healthcare technology. Dr. Rady’s work is pushing the boundaries of medical engineering and continues to inspire new generations of researchers and students.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

Dr. Radwa Rady’s contributions to academic research have been widely recognized in peer-reviewed journals. She has authored and co-authored several papers, including one published in the Alexandria Engineering Journal and another in Neural Computing and Applications. She also holds a patent for her work on real-time EEG signal analysis for ADHD treatment. Dr. Rady’s publications, which are accessible through DOI references, have garnered attention within both the biomedical engineering and computer science fields, reflecting the significance of her research contributions.

🏅 HONORS & AWARDS

Dr. Rady’s exceptional academic performance has been consistently recognized. She achieved a GPA of 3.888 in her Doctorate of Science in Engineering at Alexandria University and a GPA of 3.788 in her Master’s degree. Additionally, her research papers have been published in prestigious journals such as Elsevier and Springer. Her work has also led to the submission of a patent for her innovative EEG analysis application, further cementing her status as a leading researcher in biomedical engineering.

🔮 LEGACY AND FUTURE CONTRIBUTIONS

Dr. Rady’s work holds the potential for long-term impact, particularly in the field of healthcare technology. Through her development of neurofeedback applications and digital signal processing systems, she is helping to shape the future of treatment for neurological conditions like ADHD. As a leader in both academia and research, Dr. Rady aims to continue advancing these fields by fostering collaborations and encouraging innovation among her students and colleagues. Her continued research promises to bring about transformative changes in the integration of biomedical engineering and artificial intelligence in medical practices.

📝 FINAL NOTE

Dr. Radwa Rady’s journey in academia, research, and professional development stands as a testament to her dedication to improving the lives of others through technology and education. From her work on respiratory wheeze sound analysis to her groundbreaking EEG research for ADHD, Dr. Rady is committed to making a meaningful difference in the world of biomedical engineering. Her future endeavors promise to build on her solid foundation, leaving a lasting legacy for generations to come.

📚 TOP NOTES PUBLICATIONS

Enhancing affordable EEG to act as a quantitative EEG for inattention treatment using MATLAB

    • Authors: Radwa Magdy Rady, Doaa Elsalamawy, M. R. M. Rizk, Onsy Abdel Alim, Nancy Diaa Moussa

    • Journal: Neural Computing and Applications

    • Year: 2025

A comparison between classical and new proposed feature selection methods for attention level recognition in disordered children

    • Authors: Rady, R.M.; Moussa, N.D.; El Salmawy, D.H.; M Rizk, M.R.; Alim, O.A.

    • Journal: Alexandria Engineering Journal

    • Year: 2022

Respiratory Wheeze Sound Analysis Using Digital Signal Processing Techniques

    • Authors: Rady, R.M.; Akkary, I.M.E.; Haroun, A.N.; Fasseh, N.A.E.; Azmy, M.M.

    • Journal: Proceedings – 7th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2015

    • Year: 2015

Sogand Dehghan | social network analysis | Best Innovation Award

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Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👨‍🎓Professional Profiles

Orcid Profile

Google Scholar  Profile

👩‍💻 Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

💼 Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

👨‍🏫 Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.