ISMAIL NEGABI | Embedded Cryptographic Systems and Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr ISMAIL NEGABI | Embedded Cryptographic Systems and Artificial Intelligence | Best Researcher Award

Lecturer, Abdelmalek Essaadi University, Morocco

Ismail Negabi is a dedicated researcher and educator specializing in Embedded Cryptographic Systems and Artificial Intelligence. He holds a Doctorate from Université Abdelmalek Essaâdi, where he focused on enhancing cryptographic system security against side-channel attacks using deep learning. With a strong academic background, including a Master’s in Signal Processing and Automatic Learning and a Bachelor’s in Physical Sciences, Ismail has consistently demonstrated excellence in his field. He is currently a primary school teacher and a reviewer for the International Journal of Computer Systems and Digital Systems. Ismail is passionate about leveraging AI and cryptography to address real-world security challenges.

Professional Profile

Google Scholar

Orcid

Scopus

Education 🎓

Ismail Negabi earned his Doctorate in 2023 from Université Abdelmalek Essaâdi, specializing in Embedded Cryptographic Systems and Artificial Intelligence. He completed his Master’s in Signal Processing and Automatic Learning in 2019 and his Bachelor’s in Physical Sciences in 2017, both from Moroccan universities. His academic journey began with a Baccalaureate in Physical and Chemical Sciences in 2011. Throughout his education, Ismail has consistently achieved high honors, including a “Très Honorable” distinction for his doctoral thesis.

Experience 💼

Ismail has a diverse professional background, including roles as a primary school teacher since 2020 and a reviewer for the International Journal of Computer Systems and Digital Systems. He has also worked as a trainer for the General Population and Housing Census in Morocco and completed internships in algorithm development and FPGA-based cryptographic systems. His experience spans teaching, research, and practical applications of AI and cryptography.

Awards and Honors 🏆

Ismail Negabi has received numerous accolades, including the “Très Honorable avec Félicitations” distinction for his doctoral thesis. His research has been published in prestigious journals indexed in Scopus, and he has presented at international conferences. Ismail’s contributions to AI and cryptography have earned him recognition as a promising researcher in his field.

Research Focus 🔍

Ismail’s research focuses on enhancing the security of cryptographic systems using deep learning techniques, particularly against side-channel attacks. He explores the integration of AI with encryption methods like AES to improve embedded system security. His work also extends to applications of deep learning in remote sensing, such as building extraction from satellite images, and anomaly detection for connected objects.

Publication Top Notes 📚

  1. “Building extraction from remote sensing imagery: advanced squeeze-and-excitation residual network based methodology”
  2. “Deep Learning-based Power Analysis Attack for Extracting Advanced Encryption Standard Keys on Microcontroller”
  3. “Convolutional neural network based key generation for security of data through encryption with AES”
  4. “Enhancing Building Extraction from Remote Sensing Images through UNet and Transfer Learning”
  5. “A Modular System based on U-Net for Automatic Building Extraction from very high-resolution satellite images”
  6. “Enhancing Cryptosystem Security with a CNN-based Countermeasure against Power Analysis Attacks”
  7. “Beyond Encryption: How DL Can Break Microcontroller Security Through Power Analysis”
  8. “Encryption of Sensitive Data by Intelligent Cryptosystem based on AES and CNN for Embedded Systems Security”
  9. “Combining Convolutional Neural Network with Feature Extraction for Automatic Building Extraction”
  10. “Towards an Intelligent Cryptosystem Design: Deep Learning Cryptography for Embedded Systems Security”

Conclusion 🌟

Ismail Negabi is a highly accomplished researcher and educator with a passion for advancing the fields of AI and cryptography. His innovative work on deep learning-based cryptographic security and remote sensing applications has made significant contributions to the academic and professional communities. With a strong foundation in education, diverse professional experience, and a commitment to excellence, Ismail continues to inspire and lead in his field.

 

Ali Abdullah S. AlQahtani | Cybersecurity | Best Researcher Award

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Dr Ali Abdullah S. AlQahtani | Cybersecurity | Best Researcher Award 

Assistant Professor, Prince Sultan University, Saudi Arabia

Dr. Ali Abdullah S. AlQahtani is an esteemed cybersecurity researcher and academic affiliated with Prince Sultan University. His expertise spans digital authentication, cybersecurity, IoT applications, and machine learning. He has contributed significantly to authentication systems, including zero-effort two-factor authentication and continuous authentication mechanisms. Dr. AlQahtani has authored numerous high-impact publications and has been cited widely for his research in secure digital identification and privacy protection. His contributions extend to academia and industry, where he has collaborated on innovative security solutions.

PROFESSIONAL PROFILE

Google Scholar

STRENGTHS FOR THE AWARD

  1. Strong Academic Background – Dr. AlQahtani holds a Ph.D. in Engineering (Cyberspace Engineering) from Louisiana Tech University, along with master’s degrees in Electrical Engineering and Computer & Information Science (Cybersecurity & Privacy). His education is well-aligned with cutting-edge cybersecurity research.
  2. High Citation and Research Impact – He has multiple peer-reviewed publications, including papers in IEEE Access and leading cybersecurity conferences. His work on machine learning, cybersecurity, digital authentication, and IoT security has received substantial citations, indicating strong influence in the field.
  3. Innovative Research Contributions – His work on Zero Effort Two-Factor Authentication (0E2FA) and Beacon Frame Two-Factor Authentication (BF2FA) demonstrates significant contributions to authentication mechanisms, enhancing security with minimal user interaction.
  4. Focus on Emerging Topics – Dr. AlQahtani’s research spans biometric authentication, IoT security, AI-driven cybersecurity, and location-based authentication systems, aligning with global challenges in cybersecurity.
  5. Diverse Research Collaborations – He has worked with multiple researchers across different institutions and has interdisciplinary collaborations in cybersecurity, AI, and IoT security, enhancing the practical applicability of his research.

AREAS FOR IMPROVEMENT

  1. Industry Collaboration & Patents – While his research is strong, expanding collaboration with industry leaders in cybersecurity and obtaining patents on his authentication systems could enhance the practical impact of his work.
  2. Government & Policy Influence – Given the increasing importance of cybersecurity policies, contributing to government regulations or cybersecurity frameworks could further solidify his global recognition.
  3. Large-Scale Real-World Implementation – While his research on user authentication and IoT security is promising, implementing his solutions at scale (e.g., national security, enterprise cybersecurity, or smart cities) would further validate his innovations.

EDUCATION

🎓 Doctor of Philosophy in Engineering (Cyberspace Engineering) – Louisiana Tech University, USA (2017-2020)
📝 Dissertation: “0E2FA: Zero Effort Two Factor Authentication”
📊 GPA: 3.667/4.00

🎓 Master of Engineering in Electrical Engineering – Louisiana Tech University, USA (2017-2019)
📊 GPA: 3.667/4.00

🎓 Master of Science in Computer and Information Science – Southern Arkansas University, USA (2016-2017)
🔬 Concentration: Cybersecurity and Privacy
📊 GPA: 3.90/4.00

🎓 Bachelor of Science in Computer Science – Grambling State University, USA (2013-2016)
📊 Major & Math GPA: 4.00/4.00 | Overall GPA: 3.90/4.00

EXPERIENCE

With a diverse background in academia, research, industry, and military service, I have gained extensive expertise in cybersecurity, computer science, and leadership roles. As an Assistant Professor of Cybersecurity at Prince Sultan University and previously at North Carolina A&T State University, I have taught graduate and undergraduate courses, mentored students, and led research initiatives. My research spans cybersecurity, authentication systems, and artificial intelligence, securing over $1.9M in funding. I also held leadership roles as Projects Director at King Saud University and Founding Director of CyberNex Lab, spearheading cybersecurity initiatives. My industry experience includes working as a Software Engineer Intern at CenturyLink, developing innovative mobile applications. Additionally, I served in the Royal Saudi Air Force (2004-2011), gaining expertise in technical operations and leadership. My multidisciplinary experience enables me to contribute effectively to academia, research, and industry collaborations.

AWARDS AND HONORS

🏆 Best Research Paper Award – Multiple conferences on cybersecurity and authentication
🏆 Outstanding Research Contribution – Recognized for innovations in digital authentication
🏆 Cybersecurity Excellence Award – Honored for advancements in secure IoT applications
🏆 Best Academic Performance – Awarded for excellence in computer science education

RESEARCH FOCUS

🔐 Cybersecurity – Enhancing digital security frameworks
🆔 Digital Authentication – Developing zero-effort and two-factor authentication models
📡 IoT Applications – Securing IoT networks and devices
🤖 Machine Learning in Security – Applying ML for authentication and threat detection

PUBLICATION TOP NOTES📚

📝 Distinguishing Human-Written and ChatGPT-Generated Text Using Machine Learning
📝 0EISUA: Zero Effort Indoor Secure User Authentication
📝 A Survey on User Authentication Factors
📝 Zero-Effort Indoor Continuous Social Distancing Monitoring System
📝 COVID-19 Zero-Interaction School Attendance System
📝 TS2FA: Trilateration System Two Factor Authentication
📝 BF2FA: Beacon Frame Two-Factor Authentication
📝 A Cheat-Proof System to Validate GPS Location Data
📝 Comprehensive Survey: Biometric User Authentication Application, Evaluation, and Discussion
📝 IoT Devices Proximity Authentication in Ad Hoc Network Environment
📝 Analysis of the Design Requirements for Remote Internet-Based E-Voting Systems
📝 0EI2FA: Zero Effort Indoor Two Factor Authentication
📝 CI2FA: Continuous Indoor Two-Factor Authentication Based On Trilateration System
📝 Architecture for Continuous Authentication in Location-Based Services
📝 A Weighting System for Building RSS Maps by Crowdsourcing Data from Smartphones
📝 Leveraging Machine Learning for Wi-Fi-Based Environmental Continuous Two-Factor Authentication
📝 Navigating Cybersecurity Training: A Comprehensive Review
📝 Comparative Analysis of Underwater Positioning and Navigation Systems
📝 Two Methods for Authentication Using Variable Transmission Power Patterns
📝 Securing IoT-Based Healthcare Systems Against Malicious and Benign Congestion

CONCLUSION

Dr. Ali Abdullah S. AlQahtani is a highly qualified candidate for the Best Researcher Award in cybersecurity and authentication technologies. His pioneering work in two-factor authentication, machine learning applications in cybersecurity, and IoT security positions him among top researchers in the field. Strengthening industry partnerships, real-world applications, and policy influence would further enhance his contributions and solidify his status as a leading expert.

Richa Vij – Computer science and engineering – Best Researcher Award

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Richa Vij - Computer science and engineering - Best Researcher Award

IIT Jammu - India

👩‍🏫 ACADEMIC AND RESEARCH LEADER

Richa Vij is an Assistant Professor in the Department of Computer Science and Engineering at the Government College of Engineering and Technology, Jammu. With a focus on retinal imaging and artificial intelligence, she brings significant experience in developing innovative computational models aimed at diagnosing systemic diseases like diabetic retinopathy and Alzheimer's. Her academic contributions, both as a professor and researcher, have made her a prominent figure in the field of AI-powered medical diagnostics.

💻 PROJECT ASSOCIATE AT IIT JAMMU

As a Project Associate-II for a DRDO project at IIT Jammu, Richa works on cutting-edge computer science projects that contribute to national development. Her role involves harnessing deep learning and AI methodologies for real-world applications, reflecting her commitment to both academic advancement and practical innovation.

📚 PUBLISHED AUTHOR IN AI AND HEALTHCARE

Richa Vij has authored multiple impactful publications in high-profile journals such as Metabolic Brain Disease and Computers and Electrical Engineering. Her research has focused on leveraging deep learning techniques to advance the early detection of diseases like Alzheimer's and diabetic retinopathy, contributing significantly to medical imaging and AI diagnostic systems.

🔬 PIONEERING RETINAL DISEASE DIAGNOSIS

Her Ph.D. research at SMVDU, Katra, under the supervision of Dr. Sakshi Arora, centers on using hybrid deep transfer learning-based algorithms to analyze retinal images for systemic disease detection. This work aims to enhance the performance of segmentation and classification models, positioning her research at the intersection of healthcare and advanced AI technologies.

📊 INNOVATIVE M.TECH RESEARCH

Richa’s M.Tech dissertation focused on "Robust Human Face Tracking and Recognition in Video Frames." By developing a novel face recognition model using the AdaBoost algorithm and K-means clustering, she addressed key challenges in face recognition, such as pose variation and occlusion, further showcasing her expertise in machine learning and pattern recognition.

🧠 FOCUS ON DIABETIC RETINOPATHY AND ALZHEIMER’S

Her work is particularly influential in the early diagnosis of Diabetic Retinopathy and Alzheimer’s disease through retinal imaging. By utilizing AI-based models for retinal vessel segmentation, her contributions are paving the way for improved diagnostic frameworks, with potential applications in clinical environments for early and accurate disease detection.

🌟 COMMITMENT TO AI-DRIVEN HEALTHCARE

Richa’s dedication to advancing AI-driven healthcare solutions is reflected in her ongoing research and teaching. She strives to bridge the gap between technology and healthcare by developing intelligent systems that can assist practitioners in diagnosing complex diseases, ultimately contributing to better patient outcomes and more efficient clinical workflows.

NOTABLE PUBLICATION

Title: A systematic review on diabetic retinopathy detection using deep learning techniques
Authors: R. Vij, S. Arora
Journal: Archives of Computational Methods in Engineering
Year: 2023

Title: A novel deep transfer learning based computerized diagnostic Systems for Multi-class imbalanced diabetic retinopathy severity classification
Authors: R. Vij, S. Arora
Journal: Multimedia Tools and Applications
Year: 2023

Title: Computer vision with deep learning techniques for neurodegenerative diseases analysis using neuroimaging: a survey
Authors: R. Vij, S. Arora
Journal: International Conference on Innovative Computing and Communications
Year: 2022

Title: A systematic survey of advances in retinal imaging modalities for Alzheimer’s disease diagnosis
Authors: R. Vij, S. Arora
Journal: Metabolic Brain Disease
Year: 2022

Title: A survey on various face detecting and tracking techniques in video sequences
Authors: R. Vij, B. Kaushik
Journal: 2019 International Conference on Intelligent Computing and Control Systems
Year: 2019

Lili Nurliyana Abdullah – computer technology – Best Researcher Award

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Lili Nurliyana Abdullah - computer technology - Best Researcher Award

UPM - Malaysia

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Lili Nurliyana Abdullah's academic journey began with a Diploma in Computer Science from Universiti Pertanian Malaysia in 1990. She went on to earn a Bachelor's degree in Computer Science from Universiti Putra Malaysia in 1992, graduating with a 2nd Class Upper division. Her pursuit of higher education continued in the UK, where she obtained a Master in Engineering with a specialization in Telematics from the University of Sheffield in 1996. Lili's academic endeavors culminated in a Ph.D. in Information Science from the National University of Malaysia in 2007.

PROFESSIONAL ENDEAVORS

Lili's professional career spans various prestigious roles and institutions. She started as a tutor in Computer Science at UPM in 1993 and progressed to become a lecturer and then an Associate Professor in the Multimedia Department. She also served as the Head of the Multimedia Department at UPM from 2009 to 2012. Beyond academia, she worked as a Project Consultant at Catapult Studios and held teaching attachments and training roles at several universities, including Univ Taibah in Saudi Arabia and L.N. Gumilyov Eurasian National University in Kazakhstan.

CONTRIBUTIONS AND RESEARCH FOCUS

Lili Nurliyana Abdullah's research primarily focuses on computer technology and its applications. Her expertise in multimedia, digital content, and green computing has led to significant contributions in these fields. She has been actively involved in curriculum design, project consultancy, and professional development training, particularly in the areas of multimedia and STEM. Lili's dedication to green computing is evident through her certifications and her role in the Malaysian Communications and Multimedia Commission's Green IT initiatives.

IMPACT AND INFLUENCE

Lili's work has had a profound impact on both academic and professional communities. She has been recognized with numerous awards, including the Lifetime Achievement Award from the International Scientist Awards on Engineering, Science, and Medicine in 2022, and the Outstanding Educator Award from Lattice Science Publication in 2021. Her contributions to computer technology and green computing have influenced policy making, curriculum development, and environmental sustainability in IT practices.

ACADEMIC CITES

Lili's scholarly work is highly regarded, with numerous citations reflecting her influence in the academic community. Her research has been widely published and cited, contributing significantly to the fields of computer technology, green computing, and multimedia applications. She has also served as a peer reviewer and editorial board member for several esteemed journals and conferences, further establishing her reputation as a leading expert in her field.

LEGACY AND FUTURE CONTRIBUTIONS

Lili Nurliyana Abdullah's legacy lies in her pioneering contributions to computer technology and green computing. Her work has laid the foundation for future research and development in sustainable IT practices and multimedia technology. As she continues to innovate and collaborate, Lili's future contributions are expected to further advance these fields, fostering a more sustainable and technologically advanced society.

COMPUTER TECHNOLOGY

Throughout her career, Lili Nurliyana Abdullah has focused on advancing computer technology through her research, teaching, and professional endeavors. Her work on digital content and multimedia applications has enhanced the educational landscape, while her commitment to green computing has promoted sustainable IT practices. Lili's dedication to computer technology is reflected in her extensive professional engagements, certifications, and contributions to policy making and curriculum development in the field. As a recognized leader in computer technology, she continues to inspire and influence future generations of researchers and practitioners.

NOTABLE PUBLICATION

Students’ satisfaction levels of an immersive extended reality for engine assembly tasks in engineering empirical education 2023

Deep learning mango fruits recognition based on tensorflow lite 2023

Playing Gamelan Bonang in the Air: User Requirements for Designing a Digital Musical Instrument for the Malay Bonang 2022 (3)

Comparison of Edge Detection Algorithms for Texture Analysis on Copy-Move Forgery Detection Images 2022 (2)

Chang Su – Computer application – Best Researcher Award

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Chang Su - Computer application - Best Researcher Award

Ocean University of China - China 

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Chang Su's academic journey began at the Department of Information Science and Engineering at Ocean University of China. He showed promise from an early age, demonstrating a keen interest in computer applications. His pursuit of knowledge in this field laid the foundation for his future endeavors in academia and professional practice.

PROFESSIONAL ENDEAVORS

In his professional journey, Chang Su has showcased significant expertise in computer applications. His involvement in the National Key R&D Program of China, collaborating with South China Aero Engine Factory 331, exemplifies his commitment to advancing intelligent manufacturing technologies. This experience has not only enriched his skill set but has also provided valuable insights into real-world applications of computer science.

CONTRIBUTIONS AND RESEARCH FOCUS

Chang Su's research focus lies in intelligent manufacturing, a critical area within computer applications. His contributions to the National Key R&D Program of China, particularly in the manufacturing of aircraft engine casings and blades, highlight his dedication to advancing the field. His research endeavors aim to leverage computer applications to enhance efficiency and innovation in manufacturing processes.

IMPACT AND INFLUENCE

Chang Su's participation in conferences like the IEICE conference and the HCII 2020 underscores his growing influence in the academic community. By publishing manuscripts in reputable venues, he has contributed to the dissemination of knowledge and fostered collaboration among researchers in the field of computer applications.

ACADEMIC CITES

Chang Su's research publications and contributions to prestigious conferences have garnered academic attention and citations. His work serves as a testament to his expertise and scholarly contributions in the domain of computer applications, further solidifying his reputation as a promising researcher in the field.

LEGACY AND FUTURE CONTRIBUTIONS

As Chang Su continues his journey toward obtaining a Ph.D. in Computer Applications, his legacy lies in his dedication to advancing intelligent manufacturing technologies. Through his research, he aims to make significant contributions to the field, shaping the future of computer applications and its impact on various industries. His work will pave the way for continued innovation and progress in the realm of intelligent manufacturing.

NOTABLE PUBLICATION

Zinc-mineralized diatom biosilica/hydroxybutyl chitosan composite hydrogel for diabetic chronic wound healing 2024 (1)

The hierarchical porous structures of diatom biosilica-based hemostat: From selective adsorption to rapid hemostasis 2023 (7)

Diatom-Inspired Bionic Hydrophilic Polysaccharide Adhesive for Rapid Sealing Hemostasis 2023 (4)

PEG-mediated hybrid hemostatic gauze with in-situ growth and tightly-bound mesoporous silicon 2022 (4)

 

Salim Chehida – Smart grid security – Best Researcher Award

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Salim Chehida - Smart grid security - Best Researcher Award

VERIMAG - Université Grenoble alpes - France

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Salim Chehida's academic journey commenced with an Engineer Degree in Computer Science from the University of Mostaganem, Algeria. He furthered his studies with a Magister Degree in Information Systems Engineering and eventually pursued a Ph.D. in Computer Science specializing in Software Engineering and Systems Security from the University of Oran 1 in Algeria in collaboration with the University of Grenoble Alpes in France.

PROFESSIONAL ENDEAVORS

Dr. Salim Chehida has had a diverse professional career, starting as a Software Engineer at the Finance Direction in Algeria and later transitioning to roles as a Scientific Researcher and Assistant Professor at the University of Mostaganem, Algeria. Currently, he serves as a Research and Development Expert at the University of Grenoble Alpes in France, contributing significantly to the fields of Software Engineering and Deep Learning.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Chehida's expertise lies in Software Engineering, particularly in the design, development, security, verification, and validation of software systems. He has made notable contributions to various innovative projects, including those related to cyber-physical systems (CPS) and Internet of Things (IoT) systems. His research focuses on deep learning applications, including image classification, segmentation, and object detection, as well as smart grid security.

IMPACT AND INFLUENCE

Dr. Chehida's research and development work have had a significant impact on academia and industry, particularly in the domains of software engineering and deep learning. His involvement in numerous projects, collaborations with companies and institutions worldwide, and contributions to conferences and publications have established him as a respected expert in his field.

ACADEMIC CITES

Dr. Chehida's publications and technical reports have been widely cited, reflecting the importance and relevance of his research contributions. His work in smart grid security and deep learning applications has garnered attention from researchers and professionals in academia, industry, and government organizations.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Chehida continues to advance his research and development endeavors, his legacy in the fields of software engineering and deep learning is assured. His future contributions are expected to further enhance our understanding and application of smart grid security measures and deep learning techniques, addressing critical challenges in cybersecurity and artificial intelligence for years to come.

NOTABLE PUBLICATION

Model-based Self-adaptive Management in a Smart Grid Substation 2023 (2)

Generation and verification of learned stochastic automata using k-NN and statistical model checking 2022 (1)

Learning and analysis of sensors behavior in IoT systems using statistical model checking 2022 (5)

BRAIN-IoT Architecture and Platform for Building IoT Systems 2022 (2)