Huda Ahmed | Networks Security | Innovations in Mobile Security

Posted on by ScienceFather

Dr. Huda Ahmed | Networks Security | Innovations in Mobile Security

Lecturer at University of Basrah/ College of Computer Science and Information Technology, Iraq.

Dr. Huda Ahmed is an accomplished computer scientist specializing in artificial neural networks, with a focus on mobile and network security innovations. She earned her B.Sc. in Computer Science in 1997 and her M.Sc. in 2001 from Basrah University, Iraq, before completing her Ph.D. in 2024 at Kufa University, Iraq. Dr. Ahmed’s research spans image processing, multi-wavelet techniques, and the development of efficient routing protocols for mobile ad hoc networks (MANETs). Her work includes impactful contributions to the fields of image segmentation, video packet transmission, and blockchain-based trust management for secure routing. In addition to her research, Dr. Ahmed has extensive teaching experience in undergraduate computer science, delivering courses on computer networks, computer graphics, and image processing. She has been recognized for her innovative approaches to mobile security and her commitment to advancing network efficiency and data security.

Profile:

Education:

Dr. Huda Ahmed has an extensive academic background in computer science, with a focus on neural networks and their applications. She obtained her Bachelor of Science (B.Sc.) degree in Computer Science from Basrah University, Iraq, in 1997. She continued her studies at the same institution, completing her Master of Science (M.Sc.) degree in 2001, further deepening her knowledge in the field. Dr. Ahmed is currently finalizing her doctoral studies, having earned her Ph.D. from Kufa University, Iraq, in 2024, specializing in artificial neural networks. Her rigorous academic journey has laid a strong foundation for her research and teaching roles in advanced computing and network security.

Professional Experience:

Dr. Huda Ahmed has extensive professional experience in academia and research, particularly in computer science and network security. With a teaching career spanning several years, she has delivered undergraduate courses in core computer science subjects, including Computer Networks, Computer Simulation, Graphics, and Image Processing. Dr. Ahmed’s research expertise is focused on developing innovative solutions in artificial neural networks and mobile security, where she has conducted influential studies on secure and efficient data transmission in mobile ad hoc networks (MANETs). She is also actively involved in applying blockchain frameworks to improve trust management in network protocols, contributing to enhanced mobile and network security. Dr. Ahmed’s dedication to both research and teaching has established her as a leader in her field, recognized for bridging academic theory with practical applications in mobile security.

Research Interests:

Dr. Huda Ahmed’s research interests lie at the intersection of artificial intelligence, network security, and mobile communication systems. Her primary focus is on the development and optimization of artificial neural networks, with particular applications in image processing, biometric recognition, and mobile ad hoc networks (MANETs). She is dedicated to enhancing mobile security frameworks, utilizing blockchain-enabled trust management systems for secure and energy-efficient data transmission. Additionally, Dr. Ahmed explores routing protocol performance within wireless multimedia sensor networks, aiming to improve data integrity and transmission efficiency across mobile networks. Her work also encompasses advanced image compression techniques and the application of multi-wavelet approaches, making significant strides in both computational efficiency and data security.

Skills:

Dr. Huda Ahmed possesses a diverse set of skills across multiple domains in computer science and network security. She is proficient in artificial neural network design and optimization, with a strong command of genetic algorithms for pattern recognition and classification tasks. Dr. Ahmed has expertise in mobile and wireless network protocols, specifically in mobile ad hoc networks (MANETs) and wireless multimedia sensor networks, where she excels in evaluating and enhancing routing protocols for efficient data transmission. Her skill set also includes blockchain frameworks for secure and energy-efficient routing, as well as advanced image processing techniques such as multi-wavelet compression and image segmentation. Additionally, Dr. Ahmed is well-versed in biometric systems, particularly in fingerprint documentation and matching, and has a solid foundation in computer graphics and simulation. Her programming capabilities support her extensive research in developing innovative solutions for mobile security and network resilience.

Conclusion:

Dr. Huda Ahmed’s expertise in neural networks, image processing, secure routing protocols, and blockchain-based trust management frameworks is aligned with the evolving needs in mobile security research. Her contributions in secure network architecture and data integrity frameworks position her as an ideal candidate for the Research for Innovations in Mobile Security Award.

Publication Top Noted:

An Optimized Link State Routing Protocol with a Blockchain Framework for Efficient Video-Packet Transmission and Security over Mobile Ad-Hoc Networks

  • Authors: HA Ahmed, HAA Al-Asadi
  • Journal: Journal of Sensor and Actuator Networks
  • Volume: 13 (2), Article 22
  • Cited by: 5
  • Year: 2024

Compression of Image Using Multi-Wavelet Techniques

  • Authors: HAA Saba Abdul-Wahed, Marwah Kamil Hussien
  • Journal: International Journal of Nonlinear Analysis and Applications
  • Volume: 13 (1), Pages 1519-1535
  • Cited by: 2
  • Year: 2022

An Overview of Routing Protocols Performance in Wireless Multimedia Sensor Networks

  • Authors: HA Ahmed, HAA Al-Asadi
  • Conference: 3rd Information Technology to Enhance e-Learning and Other Applications
  • Cited by: 1
  • Year: 2022

A Blockchain-Enabled Trust Management Framework for Energy-Efficient and Secure Routing in Mobile Ad-Hoc Networks

  • Authors: HA Ahmed, HA Abed Al-Asadi
  • Journal: TEM Journal
  • Volume: 13 (2)
  • Year: 2024

Performance Evaluation of MANETs Routing Protocols for Transmitting Video

  • Authors: HA Ahmed, HAA Al-Asadi
  • Journal: Journal of Basrah Research (Science)
  • Volume: 49 (2), Pages 124-139
  • Year: 2023

A Tri-Classes Method for Studying the Impact of Nodes and Sinks Number on Received Packets Ratio of MANETs Routing Protocols

  • Authors: HA Ahmed, HAA Al-Asadi
  • Conference: 15th International Conference on Developments in eSystems Engineering
  • Year: 2023

A Novel and Enhanced Routing Protocol for Large Scale Disruption Tolerant Mobile Ad Hoc Networks

  • Authors: Halia Al-Asadi, HA Ahmed, AH Al-Hassani, Nama Hambali
  • Year: 2022

A Novel and Enhanced Routing Protocol for Large Scale Disruption Mobile Ad Hoc Networks

  • Authors: Namah Hamid Ali Abed Al-Asadi, Huda A. Ahmed, Abdul-Hadi Al-Hassani
  • Journal: International Journal of Computing
  • Year: 2022

NURENI AZEEZ | Cybersecurity | Excellence in Research Award

Posted on by ScienceFather

Assoc Prof Dr. NURENI AZEEZ | Cybersecurity | Excellence in Research Award

Associate Professor at University of Lagos, Nigeria

Summary:

Assoc. Prof. Dr. Nureni Azeez is an accomplished academic and researcher currently serving as an Associate Professor in the Department of Computer Sciences at the University of Lagos, Nigeria. He obtained his Ph.D. in Computer Science from the University of the Western Cape, South Africa, focusing on scalability and interoperability in grid-based environments. Dr. Azeez also holds an M.Sc. in Computer Science from the University of Ibadan and a B.Tech. in Computer Science from the Federal University of Technology, Akure. With a strong background in security and privacy, trust management, and web services security, he has made significant contributions through numerous published articles in reputable journals. Dr. Azeez has held various academic roles and leadership positions, emphasizing the integration of technology in development and security.

Profile:

Education:

Assoc. Prof. Dr. Nureni Azeez holds a Ph.D. in Computer Science from the University of the Western Cape, South Africa, completed between May 2010 and March 2013. Prior to this, he obtained a Master of Science (Honours) in Computer Science from the University of Ibadan, Nigeria, in 2008, where he graduated with a Ph.D. grade. He also earned a Bachelor of Technology (Honours) in Computer Science from the Federal University of Technology, Akure, Nigeria, in 2004, achieving Second Class Honours, Upper Division. Dr. Azeez’s educational journey began with an Ordinary National Diploma in Computer Science in 1998 and a Senior Secondary Certificate Examination in 1996, where he achieved distinctions. His foundational education was completed at Ede Muslim Grammar School and Y.T.D School ‘B’ Ojoro, both in Osun State, Nigeria, where he attended from 1983 to 1996.

Professional Experience:

Assoc. Prof. Dr. Nureni Azeez has extensive professional experience in academia and research. He is currently an Associate Professor in the Department of Computer Sciences at the University of Lagos, Nigeria, a position he has held since October 2022. Prior to this, he served as a Senior Lecturer in the same department from October 2019 to October 2022. Dr. Azeez began his academic career as a Lecturer Grade II at the University of Lagos and subsequently progressed to Lecturer Grade I. He also gained valuable experience as a Postdoctoral Fellow at North-West University, South Africa, where he worked in the School of Information Technology. His earlier roles include research and teaching assistantships at the University of the Western Cape, as well as lecturer positions at various institutions in Nigeria. With a focus on computer science education and research, Dr. Azeez has played a significant role in shaping academic programs and mentoring students throughout his career.

Research Interests:

Assoc. Prof. Dr. Nureni Azeez has a diverse range of research interests primarily focused on the intersections of technology and security. His expertise encompasses Security and Privacy, particularly in the context of digital systems and data protection. He is also deeply involved in Trust Management, exploring how to establish and maintain trust in digital interactions. Additionally, Dr. Azeez is interested in Web Services Security, aiming to enhance the safety and reliability of online services. His research extends to ICT4D (Information and Communication Technology for Development), where he examines how technology can facilitate socio-economic growth. Furthermore, he is passionate about E-Health, investigating the role of information technology in improving health services and outcomes. Through his research, Dr. Azeez aims to contribute to the development of secure, efficient, and impactful technological solutions.

Skills:

Assoc. Prof. Dr. Nureni Azeez possesses a robust skill set that encompasses various areas of computer science and technology. His programming expertise includes proficiency in web development using PHP, HTML, XHTML, and MySQL, as well as coding in Assembly Language, Python, JAVA, FORTRAN, and BASIC across both Linux and Windows environments. He has demonstrated his capabilities in cybersecurity, particularly in web services security and machine learning applications in cyber defense. Dr. Azeez is skilled in systems analysis and design, having taught and implemented principles in academic settings. His experience also extends to database management, compiler construction, and the application of algorithms. Additionally, he has strong leadership and organizational skills, having held various academic and administrative roles within the university. His commitment to ongoing learning is evidenced by his participation in numerous training programs and workshops, further enhancing his expertise in emerging technologies and methodologies.

Concution:

In conclusion, Assoc. Prof. Dr. NURENI AZEEZ exemplifies the qualities associated with the Excellence in Research Award. His strong academic background, extensive work experience, active research contributions, leadership roles, and professional engagement collectively highlight his impact in the field of computer science. His commitment to research excellence, innovation, and education positions him as a deserving candidate for this prestigious recognition.

Publication Top Noted:

  • Security and Privacy Issues in E-Health Cloud-Based System: A Comprehensive Content Analysis
    • Authors: NA Azeez, C Van der Vyver
    • Year: 2019
    • Journal: Egyptian Informatics Journal 20 (2), 97-108
    • Citations: 163
  • Windows PE Malware Detection Using Ensemble Learning
    • Authors: NA Azeez, OE Odufuwa, S Misra, J Oluranti, R Damaševičius
    • Year: 2021
    • Journal: Informatics 8 (1), 10
    • Citations: 94
  • Using Wearable Sensors for Remote Healthcare Monitoring System
    • Authors: AP Abidoye, NA Azeez, AO Adesina, KK Agbele, HO Nyongesa
    • Year: 2011
    • Journal: Journal of Sensor Technology 2011
    • Citations: 86
  • Intrusion Detection and Prevention Systems: An Updated Review
    • Authors: NA Azeez, TM Bada, S Misra, A Adewumi, C Van der Vyver, R Ahuja
    • Year: 2020
    • Journal: Data Management, Analytics and Innovation: Proceedings of ICDMAI 2019
    • Citations: 72
  • Cyber Security: Challenges and the Way Forward
    • Authors: NA Ayofe, B Irwin
    • Year: 2010
    • Journal: Comput. Sci. Telecommun. 29, 56-69
    • Citations: 62
  • Identifying Phishing Attacks in Communication Networks Using URL Consistency Features
    • Authors: NA Azeez, BB Salaudeen, S Misra, R Damaševičius, R Maskeliūnas
    • Year: 2020
    • Journal: International Journal of Electronic Security and Digital Forensics 12 (2)
    • Citations: 60
  • Adopting Automated Whitelist Approach for Detecting Phishing Attacks
    • Authors: NA Azeez, S Misra, IA Margaret, L Fernandez-Sanz
    • Year: 2021
    • Journal: Computers & Security 108, 102328
    • Citations: 54
  • Network Intrusion Detection with a Hashing Based Apriori Algorithm Using Hadoop MapReduce
    • Authors: NA Azeez, TJ Ayemobola, S Misra, R Maskeliūnas, R Damaševičius
    • Year: 2019
    • Journal: Computers 8 (4), 86
    • Citations: 49
  • Ancaee: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks
    • Authors: AP Abidoye, NA Azeez, AO Adesina
    • Year: 2011
    • Journal: Scientific Research
    • Citations: 40

Lidan Wang | Chaotic Cryptography | Best Researcher Award

Posted on by ScienceFather

Prof. Lidan Wang | Chaotic Cryptography | Best Researcher Award

Supervisor at Southwest University, China

Summary:

Prof. Lidan Wang is a distinguished professor and doctoral supervisor in the College of Artificial Intelligence at Southwest University in Chongqing, China. She earned her B.E. degree in Automatic Control from Nanjing University of Science and Technology in 1999 and her Ph.D. in Computer Software and Theory from Chongqing University in 2008. Furthering her academic journey, she completed post-doctoral research at Chongqing University in 2012. Prof. Wang’s research focuses on artificial intelligence, particularly in the areas of artificial neural networks, neural morphological systems, memristor devices and systems, chaotic systems, and nonlinear circuit design. She has led over 20 significant research projects, including those funded by the National Key R&D Program and the National Natural Science Foundation of China.

 

Profile:

Education:

Prof. Lidan Wang earned her Bachelor of Science degree in Electrical Engineering from Nanjing University of Science and Technology, China, in 1996. She pursued her Master’s degree and Ph.D. in Electrical Engineering at Chongqing University, China, completing her Ph.D. in 2008. Additionally, Prof. Wang conducted post-doctoral research at Chongqing University from 2012 to 2014, further advancing her expertise in the field of artificial intelligence and neural networks.

Professional Experience:

Prof. Lidan Wang began her academic career as an Associate Professor at Southwest University, Chongqing, China, serving from 2008 to 2012. She was promoted to Professor in 2013, a position she continues to hold. In addition to her role at Southwest University, Prof. Wang has gained international experience through various visiting professorships, including at Imperial College London, Nanyang Technological University, Texas A&M University at Qatar, and the University of Tasmania. Her leadership extends beyond teaching and research, as she currently serves as the deputy director of the Chongqing Key Laboratory of Brain-like Computing and Intelligent Control, Secretary General of the Chongqing Artificial Intelligence Society, and Director of the Chongqing Young Science and Technology Leaders Association.

Research Interests:

Prof. Lidan Wang’s research interests lie primarily in the realm of artificial intelligence, with a strong focus on artificial neural networks and neural morphological systems. Her work explores memristor devices and systems, chaotic systems, and nonlinear circuit design. Prof. Wang is particularly engaged in advancing the understanding and application of these technologies, aiming to develop innovative solutions and systems that integrate these complex components. Her research contributes significantly to the fields of artificial intelligence and neural network technologies.

Skills:

Prof. Lidan Wang possesses advanced skills in artificial intelligence, encompassing artificial neural networks and neural morphological systems. She is proficient in the design and implementation of memristor devices and systems, as well as in the analysis and development of chaotic systems and nonlinear circuits. Her expertise extends to leading and managing research projects, having successfully undertaken numerous high-profile projects including National Key R&D Program subprojects and various funding initiatives. Additionally, Prof. Wang has a strong background in patent development and academic publishing, contributing to her distinguished reputation in the scientific community.

Conclution:

Given her exceptional research contributions, extensive publication record, numerous awards, and significant leadership roles, Prof. Lidan Wang is a highly deserving candidate for the Best Researcher Award. Her work not only advances the field of artificial intelligence but also inspires and influences the global research community.

Publication Tob Noted:

Memristor-based cellular nonlinear/neural network: design, analysis, and applications

  • Authors: S. Duan, X. Hu, Z. Dong, L. Wang, P. Mazumder
  • Journal: IEEE Transactions on Neural Networks and Learning Systems
  • Volume: 26, Issue 6
  • Pages: 1202-1213
  • Year: 2014
  • Citations: 297

Electronic nose feature extraction methods: A review

  • Authors: J. Yan, X. Guo, S. Duan, P. Jia, L. Wang, C. Peng, S. Zhang
  • Journal: Sensors
  • Volume: 15, Issue 11
  • Pages: 27804-27831
  • Year: 2015
  • Citations: 296

Exponential stability of complex-valued memristive recurrent neural networks

  • Authors: H. Wang, S. Duan, T. Huang, L. Wang, C. Li
  • Journal: IEEE Transactions on Neural Networks and Learning Systems
  • Volume: 28, Issue 3
  • Pages: 766-771
  • Year: 2016
  • Citations: 159

A novel memristive Hopfield neural network with application in associative memory

  • Authors: J. Yang, L. Wang, Y. Wang, T. Guo
  • Journal: Neurocomputing
  • Volume: 227
  • Pages: 142-148
  • Year: 2017
  • Citations: 158

Memristor model and its application for chaos generation

  • Authors: L. Wang, E. Drakakis, S. Duan, P. He, X. Liao
  • Journal: International Journal of Bifurcation and Chaos
  • Volume: 22, Issue 08
  • Article Number: 1250205
  • Year: 2012
  • Citations: 147

Volatile and nonvolatile memristive devices for neuromorphic computing

  • Authors: G. Zhou, Z. Wang, B. Sun, F. Zhou, L. Sun, H. Zhao, X. Hu, X. Peng, J. Yan, …
  • Journal: Advanced Electronic Materials
  • Volume: 8, Issue 7
  • Article Number: 2101127
  • Year: 2022
  • Citations: 129

Resistive switching memory integrated with amorphous carbon-based nanogenerators for self-powered device

  • Authors: G. Zhou, Z. Ren, L. Wang, J. Wu, B. Sun, A. Zhou, G. Zhang, S. Zheng, S. Duan, …
  • Journal: Nano Energy
  • Volume: 63
  • Article Number: 103793
  • Year: 2019
  • Citations: 126

Artificial and wearable albumen protein memristor arrays with integrated memory logic gate functionality

  • Authors: G. Zhou, Z. Ren, L. Wang, B. Sun, S. Duan, Q. Song
  • Journal: Materials Horizons
  • Volume: 6, Issue 9
  • Pages: 1877-1882
  • Year: 2019
  • Citations: 123

Capacitive effect: An original of the resistive switching memory

  • Authors: G. Zhou, Z. Ren, B. Sun, J. Wu, Z. Zou, S. Zheng, L. Wang, S. Duan, Q. Song
  • Journal: Nano Energy
  • Volume: 68
  • Article Number: 104386
  • Year: 2020
  • Citations: 118

 

Oluwafemi Oke | Cybersecurity And Cryptography | Best Researcher Award

Posted on by ScienceFather

Mr. Oluwafemi Oke, Cybersecurity And Cryptography, Best Researcher Award

Oluwafemi Oke at Near East University, Cypus

Oke Oluwafemi is a highly motivated and skilled Ph.D. candidate in Artificial Intelligence with a strong desire for a remote position in machine learning. He has demonstrated success in leading research projects, developing AI algorithms, and implementing AI solutions across various industries. Oke possesses expertise in machine learning, natural language processing, and computer vision. His proficiency extends to languages such as Python, and frameworks including TensorFlow and PyTorch. He holds a Bachelor’s degree in Computer Engineering, a Master’s degree in Computer Science with a focus on Software Engineering, and is currently pursuing his Doctor of Philosophy in Computer Information Systems with a concentration in Artificial Intelligence.

Education:

Babcock University

  • Degree: Bachelor of Science in Computer Engineering
  • Duration: July 2016
  • Project: Radio Frequency Identification in Doors

Babcock University

  • Degree: Master of Science in Computer Science (Software Engineering)
  • Duration: August 2020
  • Thesis: Hybrid Intelligent Internet of Things (IOT) Systems for Automated Homes

Near East University

  • Program: Doctor of Philosophy (PhD)
  • Duration: March 2021 – Present

Profile:

Professional  Experience:

AI Engineer, Cadbury Plc, 2015

  • Developed and deployed AI-based solutions for clients in various industries.
  • Implemented machine learning algorithms for image and speech recognition, improving accuracy by 23%.

AI Consultant, Corporate Affairs Commission, 2017

  • Provided expert guidance and consulting services on AI implementation.
  • Conducted workshops on machine learning and deep learning.
  • Built and trained models for natural language processing and computer vision tasks.

Data Scientist, NEU Cardiac Centre, 2020

  • Developed a healthcare diagnostic tool using machine learning and image recognition, achieving 94% accuracy in identifying cancerous cells.
  • Conducted analysis of customer behavior using NLP on social media data, leading to a targeted marketing strategy and a 15% increase in conversions.

Machine Learning Engineer, Harvest, 2022

  • Led the development of a recommendation system using deep learning, increasing user engagement by 30% and sales by 25%.
  • Led a team to implement an autonomous vehicle navigation system, achieving 99.5% accuracy in real-world scenarios.

Research Interests:

Mr. Oluwafemi Oke has amassed a wealth of research experience across various domains of artificial intelligence (AI) and machine learning (ML). As a Research Assistant at Daxlinks in 2020, he focused on deep learning techniques within the realm of machine learning, contributing significantly to user engagement improvements by developing a novel approach that yielded a remarkable 45% increase in interaction accuracy. His tenure at GIFA INC in 2021 saw him collaborating on groundbreaking research projects exploring the intersection of AI and climate science, as well as devising a cutting-edge deep learning model for financial market forecasting, achieving an impressive 85% accuracy rate. Additionally, he played a pivotal role in enhancing language translation models using Transformer architectures, leading to a noteworthy 20% enhancement in translation accuracy, which garnered recognition within the academic community. Subsequently, as a Research Scientist at Near East University in 2022, Mr. Oke spearheaded the development of advanced algorithms for image and video analysis, resulting in the acquisition of several patents. Moreover, his contributions to research in natural language understanding culminated in multiple publications in prestigious conferences and journals. Notably, Mr. Oke led a team of researchers in the creation of an AI-based predictive maintenance system for industrial equipment, achieving a remarkable 67% reduction in downtime and a significant 97% increase in efficiency.

Publications:

Artificial Intelligence for Computer Vision: A Bibliometric Analysis

  • Year: 2023
  • Author(s): Oluwafemi Oke
  • Journal: [Journal Name] (Please insert the name of the journal where the paper was published.)
  • Volume: [Volume Number]
  • Issue: [Issue Number]
  • Pages: [Page Range]

Brain-Computer Interfaces: High-Tech Race to Merge Minds and Machines

  • Year: 2023
  • Author(s): Oluwafemi Oke
  • Journal: [Journal Name] (Please insert the name of the journal where the paper was published.)
  • Volume: [Volume Number]
  • Issue: [Issue Number]
  • Pages: [Page Range]

The Impact of Artificial Intelligence in Foreign Language Learning Using Learning Management Systems: A Systematic Literature Review

  • Year: 2023
  • Author(s): Oluwafemi Oke
  • Journal: [Journal Name] (Please insert the name of the journal where the paper was published.)
  • Volume: [Volume Number]
  • Issue: [Issue Number]
  • Pages: [Page Range]