Prof. Khaled Shaban | Data Science | Best Researcher Award

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Prof. Khaled Shaban | Data Science | Best Researcher Award

Prof. Khaled Shaban, Qatar University, Qatar

Prof. Khaled Shaban is a distinguished researcher and professor in Computer Science and Engineering at Qatar University. With expertise in Computational Intelligence, Machine Learning, and Data Science, he has significantly contributed to advancing pattern recognition, cloud computing, and cybersecurity. A senior member of IEEE and ACM, he has received multiple accolades for his groundbreaking research. He also holds an adjunct professorship at the University of Waterloo, reinforcing his global academic influence. His work focuses on AI-driven disease prediction, smart systems, and optimization techniques, making him a leader in intelligent computing innovations.

🌍 Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for Best Researcher Award

Prof. Khaled Shaban’s research excellence, innovative contributions, and global recognition make him an ideal candidate for the Best Researcher Award. His pioneering work in Machine Learning, AI, and Computational Intelligence has led to influential publications and prestigious awards, such as the Best Paper Award at IRICT 2021. His ability to merge theory and application in AI, cloud computing, and cybersecurity has significantly impacted academia and industry. His leadership in top-tier conferences and IEEE/ACM communities underscores his commitment to advancing knowledge, making him a highly deserving candidate for this distinguished recognition.

🎓 Education

Prof. Khaled Shaban holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2006), specializing in Pattern Recognition and Machine Intelligence. His academic journey began with an M.Sc. in Engineering Systems and Computing (2002) from the University of Guelph, Canada, where he developed a strong foundation in computational intelligence and optimization. His interdisciplinary education has enabled him to integrate machine learning, data science, and engineering systems into cutting-edge research. His expertise in algorithms and computing theory has positioned him as a global leader in AI and intelligent systems research.

💼 Experience

Prof. Khaled Shaban has an extensive academic career, currently serving as a Professor at Qatar University’s College of Engineering (since April 2021). He previously held roles as Associate Professor (2016-2021) and Assistant Professor (2008-2016). Additionally, he is an Adjunct Professor at the University of Waterloo (2021-2027), collaborating on AI-driven computing innovations. His professional affiliations with IEEE, ACM, and international research communities enhance his impact on global technological advancements. Over the years, he has mentored numerous students and led transformative research in Artificial Intelligence, Data Science, and Optimization.

🏅 Awards & Honors

  • 🏆 Best Paper Award – IRICT 2021 for “C-SAR: Class-Specific and Adaptive Recognition for Arabic Handwritten Cheques”
  • 🏅 Nomination for Best Paper Award – ICVS 2021 for “MARL: Multimodal Attentional Representation Learning for Disease Prediction”
  • 🎖 Promoted to Professor – Qatar University, 2021
  • 🔬 Senior Member, IEEE & ACM – Recognized for contributions to AI and Computational Intelligence
  • 🌍 International Collaborations – Adjunct Professor at the University of Waterloo, fostering global research partnerships

🔬 Research Focus

Prof. Khaled Shaban’s research lies at the intersection of Artificial Intelligence, Computational Intelligence, and Data Science. His work in Machine Learning-driven healthcare analytics, particularly in disease prediction and medical image analysis, is widely recognized. He has also made significant contributions to cybersecurity, cloud computing, and smart grid systems. His studies on optimization and knowledge discovery enhance IoT, AI-based automation, and intelligent computing solutions. Through numerous publications and projects, he has addressed real-world challenges in AI, energy-efficient computing, and adaptive learning systems, making his research impactful across academia and industry.

📖 Publication Top Notes

  • Urban Air Pollution Monitoring System with Forecasting Models

    • Year: 2016
    • Citations: 341

  • Fault Detection, Isolation, and Service Restoration in Distribution Systems: State-of-the-Art and Future Trends

    • Year: 2016
    • Citations: 321

  • Delay-Aware Scheduling and Resource Optimization with Network Function Virtualization

    • Year: 2016
    • Citations: 266

  • A Reliability-Aware Network Service Chain Provisioning with Delay Guarantees in NFV-Enabled Enterprise Datacenter Networks

    • Year: 2017
    • Citations: 224

  • Deep Learning Models for Sentiment Analysis in Arabic

    • Year: 2015
    • Citations: 150

 

 

Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

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Satish Mahadevan Srinivasan | Machine Learning | Best Researcher Award

Dr. Satish Mahadevan Srinivasan, Penn State Great Valley , United States.

Dr. Satish Mahadevan Srinivasan is a Tenured Associate Professor of Information Science at Penn State Great Valley, with expertise spanning data mining, machine learning, cybersecurity, and bioinformatics. With a Ph.D. in Information Technology from the University of Nebraska, his research contributions include class-specific motif discovery in protein classification and tools for metagenomic analysis. Dr. Srinivasan’s work merges cutting-edge technologies with practical applications, contributing to bioinformatics, distributed computing, and artificial intelligence. He has a rich academic and professional journey, publishing impactful research and developing transformative software tools. 🌐📊🔬

Publication Profiles

Googlescholar

Education and Experience

Education

  • 🎓 Ph.D. in Information Technology, University of Nebraska, 2010
  • 🎓 M.S. in Industrial Engineering & Management, IIT Kharagpur, 2005
  • 🎓 B.E. in Information Technology, Bharathidasan University, 2001

Experience

  • 📚 Tenured Associate Professor, Penn State Great Valley (2019–Present)
  • 📚 Assistant Professor, Penn State Great Valley (2013–2019)
  • 🔬 Postdoctoral Researcher, Computational Bioinformatics, UNMC (2011–2013)
  • 💻 Postdoctoral Research Assistant, Computer Science, University of Nebraska (2010–2011)
  • 🛠️ Project Assistant, IIT Kharagpur (2001–2005)

Suitability For The Award

Dr. Satish Mahadevan Srinivasan, a Tenured Associate Professor at Penn State, excels in interdisciplinary research spanning data mining, bioinformatics, machine learning, and cybersecurity. His groundbreaking tools like MetaID and Monarch have advanced microbial analysis and software engineering. With impactful publications, innovative solutions, and practical applications, Dr. Srinivasan exemplifies research excellence, making him highly deserving of the Best Researcher Award.

Professional Development

Dr. Srinivasan has developed innovative tools and frameworks, including MetaID for metagenomic studies and Monarch for transforming Java programs for embedded systems. His interdisciplinary research bridges machine learning, predictive analytics, and cybersecurity with bioinformatics, aiding microbial classification and software optimization. By integrating artificial intelligence and distributed computing, he has addressed complex challenges in data science, genomics, and engineering. His professional journey reflects a commitment to cutting-edge technology, impactful research, and knowledge dissemination through teaching and mentorship. 🌟🔍

Research Focus

Dr. Satish Mahadevan Srinivasan’s research focuses on leveraging advanced technologies to address complex problems in data science, bioinformatics, and cybersecurity. His work in data mining and machine learning aims to uncover patterns and develop predictive models for diverse applications. In bioinformatics, he has designed tools like MetaID for microbial classification and motif discovery in protein sequences, contributing to genomics and medical advancements. His expertise extends to cybersecurity, where he explores cryptographic techniques to enhance internet security, and distributed computing, optimizing system performance. Dr. Srinivasan’s interdisciplinary approach bridges artificial intelligence, predictive analytics, and software engineering to create impactful solutions. 🌐🔬📊

Awards and Honors

  • 🏆 Awarded research grants for innovative bioinformatics tools.
  • 📜 Recognized for contributions to cybersecurity and internet authentication.
  • 🌟 Acknowledged as a leading researcher in predictive analytics and machine learning.
  • 📊 Published in high-impact journals like BMC Bioinformatics and BMC Genomics.

Publication Top Notes

  • Effect of negation in sentences on sentiment analysis and polarity detection  – Cited by 93, 2021 📊📚
  • LocSigDB: A database of protein localization signals  – Cited by 49, 2015 🧬📖
  • K-means clustering and principal components analysis of microarray data of L1000 landmark genes– Cited by 46, 2020 🧪📊
  • Mining for class-specific motifs in protein sequence classification – Cited by 29, 2013 🔬📜
  • Web app security: A comparison and categorization of testing frameworks– Cited by 27, 2017 🔒🖥️
  • MetaID: A novel method for identification and quantification of metagenomic samples – Cited by 23, 2013 🌍🔍
  • Sensation seeking and impulsivity as predictors of high-risk sexual behaviours among international travellers – Cited by 21, 2019 ✈️🧠
  • Cybersecurity for AI systems: A survey – Cited by 20, 2023 🤖🔐

Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

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Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

Dr. Thomas Kotoulas, Aristotle University of Thessaloniki, Greece, Greece

Dr. Thomas Kotoulas is a renowned physicist specializing in Newtonian dynamics and celestial mechanics. He has built a distinguished career in the study of dynamical systems, particularly the behavior of small bodies in the outer Solar System. He is currently a researcher at the University of Thessaloniki, where he earned his B.Sc. in Physics (1995) and Ph.D. in Physics (2003). Over the years, Kotoulas has become a key figure in the field of celestial mechanics, with numerous publications and contributions to the study of periodic orbits, stability, and resonance dynamics. His expertise extends to inverse problems in Newtonian dynamics and its applications in astronomy. Dr. Kotoulas has been awarded for his excellence as an external reviewer and continues to significantly contribute to the advancement of his research areas.

Professional Profile:

Google Scholar

Scopus

Summary of Suitability for Award:

Dr. Thomas Kotoulas is a strong contender for the Best Researcher Awards. His in-depth expertise, consistent scholarly output, contributions to high-impact research, leadership in projects, and acknowledgment from prestigious journals position him as a leading figure in the field of celestial mechanics. Given his outstanding research achievements and influential role in advancing scientific knowledge, Dr. Kotoulas is undoubtedly deserving of recognition as a top researcher in his field.

🎓Education: 

Dr. Kotoulas completed his B.Sc. in Physics at the Department of Physics at Aristotle University of Thessaloniki (A.U.Th.). He further pursued his postgraduate studies, culminating in a Ph.D. in Physics from the same department in 2003. His doctoral research focused on the dynamical evolution of small bodies in resonant areas within the outer Solar System, for which he received an excellent evaluation. His Ph.D. work was supervised by Professor John D. Hadjidemetriou. In addition to his academic qualifications, Dr. Kotoulas was awarded a fellowship from the National Foundation of Fellowships (Ι.Κ.Υ.) during his doctoral studies, where he specialized in dynamical systems and celestial mechanics. His academic journey was marked by excellence, shaping his future contributions to the scientific community in the fields of celestial mechanics and dynamics.

🏢Work Experience:

Dr. Kotoulas has accumulated extensive experience in the field of celestial mechanics and dynamical systems. He has worked on several significant research projects, including the “Dynamics of the restricted three-body problem and applications in Celestial Mechanics,” which was funded by the Greek Ministry of Education and the European Community. As a post-doctoral researcher, he contributed to the study of retrograde periodic orbits in the restricted three-body problem, focusing on applications in asteroids and the Kuiper Belt. Over the years, he has also served as a reviewer for several esteemed journals, such as “Celestial Mechanics and Dynamical Astronomy,” “Astrophysics and Space Science,” and “Research in Astronomy and Astrophysics.” His academic career is marked by his deep involvement in the application of inverse problems in Newtonian dynamics, which he continues to explore and develop through his research.

🏅Awards:

Dr. Thomas Kotoulas has received several prestigious awards and honors throughout his career. Notably, he was recognized as one of the best external reviewers for the journal “Research in Astronomy and Astrophysics” in 2022, receiving the Outstanding Reviewer Award for his valuable contributions. He also received a letter of recognition from Dr. Fabio Santos, the Publishing Editor of “Astrophysics and Space Science,” for his outstanding work as a reviewer during 2021 and 2022. Furthermore, Dr. Kotoulas was included in the Mathematical Reviews database, where he has written reviews for numerous papers on celestial mechanics. His work has been consistently acknowledged by the scientific community, affirming his expertise in dynamical systems and celestial mechanics. These honors highlight his significant contributions to the field, particularly in the areas of celestial mechanics, dynamics, and inverse problems.

🔬Research Focus:

Dr. Kotoulas’ primary research focus lies in the field of Newtonian dynamics and celestial mechanics, with an emphasis on the restricted three-body problem, orbital stability, and resonance dynamics. His research explores the dynamical evolution of small bodies, particularly in the outer Solar System, and how these bodies behave under the influence of resonances with larger celestial bodies. He specializes in the computation of families of periodic orbits, spectral analysis, and stability/instability in resonance regions. Additionally, Dr. Kotoulas works on inverse problems in Newtonian dynamics, applying them to astronomy and galactic dynamics. His work involves finding generalized force fields from families of orbits, as well as applying these techniques to improve our understanding of the structure and stability of orbital systems. Through his research, Dr. Kotoulas has significantly contributed to advancing theoretical models that describe the motion of celestial bodies and their dynamical interactions.

Publication Top Notes: 

  • “Planar Periodic Orbits in Exterior Resonances with Neptune”
    • Citations: 44
  • “Comparative Study of the 2:3 and 3:4 Resonant Motion with Neptune: An Application of Symplectic Mappings and Low Frequency Analysis”
    • Citations: 43
  • “On the Stability of the Neptune Trojans”
    • Citations: 34
  • “Symmetric and Nonsymmetric Periodic Orbits in the Exterior Mean Motion Resonances with Neptune”
    • Citations: 32
  • “On the 2/1 Resonant Planetary Dynamics–Periodic Orbits and Dynamical Stability”
    • Citations: 31

 

 

 

 

Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

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Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

Dr. Julius Olaniyan, Bowen University, Nigeria 

Olaniyan Julius in Odo-Owa, Kwara State, Nigeria. He is a Lecturer II in the Computer Science Department at Bowen University, Iwo, Osun State, Nigeria. Julius holds a Ph.D. in Computer Science (2023) and has extensive experience in software development, data analysis, and teaching. He has worked in several institutions, including Landmark University, Federal Polytechnic Auchi, and Feghas Solutions Ltd. Over his career, he has developed various applications using programming languages such as C, C++, Java, Python, and PHP. Julius specializes in Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation. A devoted husband and father of three, Julius is passionate about advancing AI and its application in healthcare and education. He has contributed to several innovative research papers in the field of computer science and AI.

Professional Profile:

Google Scholar

Summary of Suitability for Award:

Dr. Olaniyan has demonstrated outstanding proficiency and expertise in the fields of Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation, with a solid academic background in Computer Science. He holds a Ph.D. in Computer Science from Landmark University, and has published extensively in high-impact journals and conferences. His work on cataract detection using deep learning, as well as his innovative contributions in areas like speech refinement and emotion recognition, highlights his commitment to advancing technology for real-world applications. Furthermore, his ability to collaborate across interdisciplinary research teams and contribute to several peer-reviewed articles reflects his academic rigor and leadership.

🎓Education: 

Olaniyan Julius completed his Ph.D. in Computer Science at Landmark University (2023). He also holds a Master’s in Computer Science (M.Tech) from the Federal University of Technology, Akure (2019), where he also earned a Postgraduate Diploma (PGD) in 2012. Julius started his academic journey with a Bachelor’s in Computer Science from the Federal University of Oye Ekiti (2022). His earlier qualifications include a Higher National Diploma (HND) in Computer Science from Auchi Polytechnic (2006), and a National Diploma (ND) in the same field (2000). Julius completed his Secondary Education at Orota Community High School, Odo-Owa (1994) and his Primary Education at St. Thomas Catholic School (1988). His strong educational foundation in Computer Science has shaped his successful academic and professional career.

🏢Work Experience:

Olaniyan Julius has a diverse career in academia and industry. He is currently a Lecturer II at Bowen University, Nigeria. Previously, he served as a Lecturer II at Landmark University (2023-2024) and as a Data Analyst at Federal Polytechnic Auchi (2013-2022). His industry experience includes working as a Software Developer/Business Developer at Feghas Solutions Ltd. (2009-2012) and a Tutor/Application Developer at Pesoka Systems Ltd. (2008). Julius also has teaching experience from his time as a Lecturer during his NYSC service at Maritime Academy of Nigeria (2007-2008). His early career included roles like Data Processing Officer at Ajaokuta Steel Company (2002-2004) and School Database Admin at Sani Bello Secondary School (2001). Julius’s experience spans academic teaching, research, software development, data analysis, and project management.

🏅Awards:

Olaniyan Julius has received numerous accolades throughout his academic and professional journey. His Ph.D. dissertation was highly recognized, contributing to his recognition as an emerging scholar in Computer Science. He was awarded a best student award during his time at Landmark University and has been recognized by the Federal Polytechnic Auchi for his outstanding performance as a Data Analyst. Julius’s commitment to education and research has earned him several institutional commendations for his efforts in developing AI-driven solutions in healthcare and education. His research in Artificial Intelligence and Machine Translation has garnered him recognition at international conferences. He is also an active member of several professional organizations in computer science and artificial intelligence. Julius’s leadership and contributions to academic and professional initiatives have cemented his reputation as a passionate educator and researcher.

🔬Research Focus:

Olaniyan Julius specializes in Artificial Intelligence (AI), with a focus on Computer Vision, Natural Language Processing (NLP), and Machine Translation. His work primarily involves using deep learning techniques to create solutions for healthcare (e.g., cataract detection) and education (e.g., student performance evaluation). Julius is dedicated to developing hybrid AI models that combine traditional methods with transformative learning approaches. His research in audio signal denoising and speech-to-speech translation aims to enhance communication and multilingual interaction. He is passionate about designing AI-powered systems that can automate and optimize processes, improving outcomes in health diagnostics and online learning environments. Julius’s work on emotion detection in virtual classrooms and the integration of CNN models for speech emotion recognition represents a significant contribution to the AI field. His interdisciplinary research approach holds promise for real-world AI applications in various domains.

Publication Top Notes: 

  • “Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media”
  • “Implementation of Audio Signals Denoising for Perfect Speech-to-Speech Translation Using Principal Component Analysis”
  • “Advancements in Accurate Speech Emotion Recognition Through the Integration of CNN-AM Model”
  • “Transformative Transparent Hybrid Deep Learning Framework for Accurate Cataract Detection”
  • “Parallel Attention Driven Model for Student Performance Evaluation”

 

 

 

 

Dr. Jianhuan Cen | AI for Science Awards | Best Researcher Award

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Dr. Jianhuan Cen | AI for Science Awards | Best Researcher Award

Dr. Jianhuan Cen, Sun Yat-sen University, China

Dr. Jianhuan Cen holds a master’s degree in Computational Mathematics and a bachelor’s degree in Information and Computing Science from Sun Yat-sen University, where he has consistently excelled academically and earned multiple scholarships. His research has made significant strides in AI model benchmarking for molecular property prediction and crystal structure prediction using diffusion models, showcasing his ability to integrate deep learning with scientific computation. Dr. Cen’s work has implications for material science and molecular simulation. He is known for his collaborative spirit and leadership in various research projects and software development efforts, and his versatility is evident from his involvement in programming problem review and testing school OJ websites.

Professional Profile:

Scopus
Google Scholar

Educational Background:

Dr. Cen has a robust academic foundation, with a master’s degree in Computational Mathematics and a bachelor’s degree in Information and Computing Science from Sun Yat-sen University, a leading institution in China. He has excelled academically and received multiple scholarships for his achievements.

Technical Skills and Contributions:

He has extensive hands-on experience in distributed computing, high-performance computing, and algorithm implementation using C/C++, Python, and Matlab. Dr. Cen’s project experience includes:

Implementing Locality Sensitive Hashing (LSH) on distributed clusters using Hadoop and Spark.

Developing a Non-Volatile Memory (NVM) based linear hash index, showcasing expertise in advanced database systems and memory environments.

Research Impact:

Dr. Cen has contributed to various high-impact projects, including AI model benchmarking for molecular property prediction and crystal structure prediction using diffusion models. His interdisciplinary work bridges the gap between deep learning and scientific computation, which could have broad applications in areas like material science and molecular simulation.

Collaboration and Leadership:

He has been involved in multiple research projects and collaborative software development efforts, indicating strong teamwork and leadership capabilities. He has also reviewed programming problems and tested school OJ websites, demonstrating his versatility.

Research Excellence:

Dr. Cen’s research focuses on solving high-dimensional partial differential equations (PDEs) using deep learning methods. He has developed innovative approaches that combine cutting-edge deep learning techniques with finite volume methods to tackle these complex problems.

Research Publications

1.  “Adaptive Trajectories Sampling for Solving PDEs with Deep Learning Methods” (Applied Mathematics and Computation).

2.  “Deep Finite Volume Methods for Partial Differential Equations” (SSRN).

Conclusion:

Dr. Jianhuan Cen’s academic achievements, research contributions in deep learning and computational mathematics, and technical prowess make him an outstanding candidate for the Best Researcher Award. His work is not only theoretically rigorous but also practically applicable, showing promise for future advancements in both academic and industrial contexts.

 

 

 

Assoc Prof Dr. Khaled EL Sayed | AI Awards | Best Researcher Award-3044

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Assoc Prof Dr. Khaled EL Sayed | AI in medicine | Best Researcher Award

Assoc Prof Dr. Khaled EL Sayed, Benha University, Egypt

Prof. Dr. Khaled El Sayed is an esteemed Associate Professor of Biomedical Engineering at Benha University, Egypt, with a comprehensive academic background including a B.Sc., M.Sc., and Ph.D. from Cairo University, specializing in hand geometry verification, protein function prediction, and EEG dynamics. He holds a Diploma in Medical Radiation Protection and is pursuing DBA studies. His notable achievements include awards for Excellence in Graduate Studies and patents for innovative medical systems, including a smart treatment system for heat/sun stroke and a smart patient mattress disinfection system. Prof. El Sayed has extensive teaching experience and has held significant roles, such as heading the Biomedical Department at MTI and consulting for various organizations. Currently, he is also a Medical Planning Consultant for ECG, Executive Manager at the Medical Equipment Manufacture Incubator (MED-Tech), and oversees the Medical Equipment Calibration Lab at Benha University. His expertise extends to BCI, electronic and microcontroller design, and infection control, and he contributes as a reviewer and board member for prominent journals in his field.

Professional Profile🌍

Orcid

Suitability for the Best Researcher Award

Prof. Dr. Khaled El Sayed is highly suitable for the Best Researcher Award due to the following reasons:

  1. Extensive Experience and Expertise: His broad experience spans academia, industry, and consultancy, showcasing his comprehensive understanding and leadership in biomedical engineering. His roles in teaching, research, and management highlight his multifaceted expertise.
  2. Significant Contributions: Prof. El Sayed’s work in developing innovative medical systems and his patents demonstrate a significant impact on medical technology. His contributions in bioinformatics and medical planning underscore his research excellence.
  3. Academic and Research Achievements: His extensive teaching experience, research publications, and editorial roles reflect his commitment to advancing knowledge in his field. His involvement in high-impact journals and conferences further illustrates his active participation in the research community.
  4. Leadership and Management: His leadership roles in various projects, including managing medical equipment incubators and calibration labs, demonstrate his capability in steering important initiatives and fostering collaboration.
  5. Awards and Recognition: His recognition through awards and patents, coupled with his ongoing DBA thesis, highlights his continued dedication to research and development.

Educational Background:

Prof. El Sayed earned his B.Sc., M.Sc., and Ph.D. in Biomedical Engineering from Cairo University, with notable research on hand geometry verification, protein function prediction, and EEG dynamics. His academic journey includes a Diploma in Medical Radiation Protection and ongoing DBA studies. 🎓

Prizes and Patents:

He has been awarded for Excellence in Graduate Studies and holds patents for a smart system for treating heat/sun stroke and a smart patient mattress disinfection system. 🏅

Professional Experience:

He has extensive experience teaching Biomedical Engineering courses at Benha University, previously headed the Biomedical Department at MTI, and consulted for various organizations. His earlier roles include Senior Biomedical Engineer at Dar Al-Fouad Hospital and Electronics Instructor at Cairo University. 📚

Current Positions:

Prof. Dr. Khaled El Sayed is an Associate Professor at Benha University in Egypt, specializing in Biomedical Engineering. He also serves as a Medical Planning Consultant for ECG, Executive Manager at the Medical Equipment Manufacture Incubator (MED-Tech), and Executive Manager of the Medical Equipment Calibration Lab at Benha University. Additionally, he is a Biomedical Engineering Consultant for the Egyptian Engineering Syndicate and a Board Member of the Egyptian Biomedical Engineering Society. 🏥

Special Skills and Interests:

Prof. El Sayed is proficient in PC software, MATLAB, and various programming languages. His interests include BCI, electronic design, microcontroller design, and infection control. He is fluent in Arabic and English. 💻

Editorial and Review Positions:

He contributes as a reviewer and editorial board member for journals such as AJMB and the American Journal of Bioinformatics Research. 📝

Publication Top Notes:

  • Title: A Low-Cost and PC-Based Automatic Hand Geometry Verification System
    • Year: 2009
  • Title: Comparison Between Different Methods for Protein Function Prediction
    • Year: 2009
  • Title: Estimation of the Correlation Between Protein Sub-Function Categories Based on Overlapping Proteins
    • Year: 2010
  • Title: Exploring Protein Functions Correlation Based On Overlapping Proteins and Cluster Interactions
    • Year: 2011
  • Title: Determining the Relations Between Protein Sub-Function Categories Based On Overlapping Proteins
    • Year: 2011