Maryam Kheirabadi | Computer Science | Women Researcher Award

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Women Researcher Award

Maryam Kheirabadi
Affiliation Islamic Azad University
Country Iran
Scopus ID 57210153054
Documents 16
Citations 710
h-index 9
Subject Area Computer Science
Event International Academic Achievements & Awards
ORCID 0000-0001-8980-4299

Maryam Kheirabadi
Islamic Azad University, Iran

The Women Researcher Award recognizes distinguished scholarly achievement, research excellence, scientific innovation, and sustained academic contributions by women researchers. Maryam Kheirabadi has established a research profile in computer science, artificial intelligence, medical image analysis, and intelligent healthcare systems through peer-reviewed publications indexed in Scopus. Her work demonstrates interdisciplinary applications of deep learning, convolutional neural networks, recurrent neural networks, and medical decision-support systems, contributing to diagnostic technologies and intelligent recommendation systems.[1]

Abstract

Maryam Kheirabadi’s scholarly work focuses on applying artificial intelligence techniques to healthcare, medical image processing, pattern recognition, and educational recommendation systems. Her publications emphasize convolutional neural networks, deep learning architectures, image classification, recurrent neural networks with attention mechanisms, and computer-assisted diagnosis of gastric diseases. These contributions illustrate the integration of computer science methodologies into practical healthcare applications while advancing intelligent computational models for diagnostic accuracy and automated decision support.[2]

Keywords

Artificial Intelligence, Deep Learning, Computer Science, Medical Image Analysis, Convolutional Neural Networks, Healthcare Informatics, Machine Learning, Clinical Decision Support

Introduction

Artificial intelligence has become an increasingly influential discipline for solving complex healthcare challenges. The combination of machine learning, deep neural networks, and biomedical image analysis has improved diagnostic accuracy, automated disease detection, and clinical decision support. Within this evolving research landscape, Maryam Kheirabadi has contributed to studies addressing intelligent diagnostic systems, neural network optimization, and educational recommender systems, demonstrating interdisciplinary collaboration between computer science and healthcare research.[2]

Research Profile

According to the supplied Scopus metrics, Maryam Kheirabadi has authored sixteen indexed publications, received more than seven hundred citations, and achieved an h-index of nine. Her research portfolio centers on artificial intelligence, image processing, neural networks, biomedical signal analysis, and intelligent software systems. Her publications demonstrate continued engagement with computational approaches that support clinical diagnosis and intelligent educational technologies.[1]

Research Contributions

  • Development of deep convolutional neural network models for gastric cancer diagnosis using tongue image analysis.
  • Research on intelligent educational recommender systems employing recurrent neural networks and attention mechanisms.
  • Advancement of MRI brain tumor classification through convolutional neural network architectures.
  • Application of biomedical image processing techniques for healthcare diagnostics.
  • Contribution to explainable and data-driven medical decision-support technologies.

Publications

  • Diagnosis of Gastric Cancer via Classification of the Tongue Images using Deep Convolutional Networks (2021). Journal of Information Systems and Telecommunication.
  • Dynamic Educational Recommender System Based on Improved Recurrent Neural Networks Using Attention Technique (2021). Applied Artificial Intelligence. DOI: https://doi.org/10.1080/08839514.2021.2005298
  • Increasing the Accuracy in the Diagnosis of Stomach Cancer Based on Color and Lint Features of Tongue (2021). Biomedical Signal Processing and Control. DOI: https://doi.org/10.1016/j.bspc.2021.102782
  • Y-net: A Reducing Gaussian Noise Convolutional Neural Network for MRI Brain Tumor Classification with NADE Concatenation (2021). Biomedical Physics and Engineering Express.
    DOI: https://doi.org/10.1088/2057-1976/ac107b

Research Impact

The reported citation record reflects meaningful scholarly visibility within computer science and healthcare-related artificial intelligence research. Her studies contribute to the development of intelligent diagnostic systems, automated disease classification, medical image interpretation, and educational recommendation technologies. These interdisciplinary contributions support ongoing research into machine learning applications that improve analytical performance and healthcare decision-making.[3]

Award Suitability

Maryam Kheirabadi demonstrates qualifications consistent with the objectives of the Women Researcher Award through sustained scientific publication, interdisciplinary innovation, measurable citation performance, and contributions to artificial intelligence applications in healthcare. Her research profile reflects active engagement in internationally indexed scholarship and supports recognition for advancing computational methods with practical societal applications.[1]

Conclusion

Maryam Kheirabadi’s publication portfolio illustrates the integration of artificial intelligence with healthcare and intelligent information systems. Her contributions to deep learning, neural network design, biomedical imaging, and recommendation systems have strengthened interdisciplinary research in computer science. The documented publication record, citation performance, and research focus collectively support recognition within academic achievement and research excellence programs.

References

  1. Elsevier. (n.d.). Scopus Author Details: Maryam Kheirabadi, Author ID 57210153054. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57210153054
  2. Kheirabadi, M., et al. (2021). Diagnosis of Gastric Cancer via Classification of the Tongue Images using Deep Convolutional Networks. Journal of Information Systems and Telecommunication.
    http://www.scopus.com/inward/record.url?eid=2-s2.0-85111735812&partnerID=MN8TOARS
  3. Kheirabadi, M., et al. (2021). Dynamic Educational Recommender System Based on Improved Recurrent Neural Networks Using Attention Technique. Applied Artificial Intelligence. DOI: https://doi.org/10.1080/08839514.2021.2005298
  4. Kheirabadi, M., et al. (2021). Increasing the Accuracy in the Diagnosis of Stomach Cancer Based on Color and Lint Features of Tongue. Biomedical Signal Processing and Control. DOI: https://doi.org/10.1016/j.bspc.2021.102782
  5. Kheirabadi, M., et al. (2021). Y-net: A Reducing Gaussian Noise Convolutional Neural Network for MRI Brain Tumor Classification with NADE Concatenation. Biomedical Physics and Engineering Express. DOI: https://doi.org/10.1088/2057-1976/ac107b

Divya Gautam | Computer Science | Innovative Research Award

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Innovative Research Award

Divya Gautam
Affiliation STME, SVKM’s NMIMS, Indore
Country India
Scopus ID 57315556700
Documents 17
Citations 81
h-index 4
Subject Area Computer Science
Event International Academic Achievements & Awards
ORCID 0000-0002-1395-997X

Divya Gautam
STME, SVKM’s NMIMS, Indore, India

The Innovative Research Award recognizes researchers whose scholarly contributions demonstrate originality, scientific rigor, and meaningful impact within their respective disciplines. Divya Gautam has established a research portfolio in computer science with particular emphasis on mobile ad hoc networks (MANET), denial-of-service attack detection, machine learning-based network security, and optimization techniques. Her publications have contributed to understanding secure communication mechanisms and intelligent intrusion detection methods for decentralized wireless environments.[1]

Abstract

Divya Gautam’s research primarily investigates cybersecurity challenges within mobile ad hoc networks, focusing on intelligent techniques for detecting and mitigating denial-of-service attacks. Her work integrates support vector machines, particle swarm optimization, and pattern-based analytical methods to improve network resilience and communication reliability. The resulting publications collectively contribute toward advancing practical security frameworks for decentralized wireless systems while supporting broader developments in computer science research.[2]

Keywords

Computer Science, Cybersecurity, Mobile Ad Hoc Networks, DoS Detection, Machine Learning, Network Security, Support Vector Machine, Optimization Algorithms

Introduction

Modern wireless communication environments require effective mechanisms for detecting malicious activities while maintaining reliable network performance. Mobile ad hoc networks remain particularly vulnerable because of their decentralized architecture and dynamic topology. Research conducted by Divya Gautam addresses these challenges through computational intelligence techniques capable of improving attack detection accuracy while reducing network disruption.[3]

Research Profile

According to Scopus, Divya Gautam has authored seventeen indexed publications with eighty-one citations and an h-index of four. Her scholarly activities are concentrated within computer science, particularly network security, intrusion detection, wireless communication, intelligent optimization algorithms, and secure distributed networking. These metrics indicate an active and developing research profile with contributions appearing in journals, conference proceedings, and scholarly book chapters.[1]

Research Contributions

  • Development of pattern-based techniques for detecting DoS and DDoS attacks.
  • Application of Support Vector Machine methodologies for intelligent intrusion detection.
  • Integration of Particle Swarm Optimization with machine learning for improved classification.
  • Comparative evaluation of attack mitigation techniques in MANET environments.
  • Contribution to secure wireless networking research through conference and journal publications.

Publications

  1. A Comparative Study of DoS Attack Detection and Mitigation Techniques in MANET (2020), Lecture Notes in Networks and Systems.DOI:
    10.1007/978-981-15-2071-6_50
  2. Fixed points results in b-metric spaces (2020), Materials Today: Proceedings.DOI:
    10.1016/j.matpr.2021.05.147
  3. Pattern Based Detection and Mitigation of DoS Attacks in MANET Using SVM-PSO (2020).DOI:
    10.1007/978-3-030-44758-8_16
  4. Detection of DoS attacks in MANET using LIBSVM (2019), International Journal of Engineering and Advanced Technology.
  5. Pattern based detection of DDoS attacks in MANET (2019), International Journal of Innovative Technology and Exploring Engineering.

Research Impact

The available publication record demonstrates continued engagement with contemporary cybersecurity challenges affecting wireless communication networks. Citation activity reflects scholarly visibility, while the combination of journal articles, conference papers, and book chapters indicates dissemination across multiple academic publishing platforms. The research has practical relevance for secure communication systems, intelligent network monitoring, and machine learning-based threat detection.[4]

Award Suitability

Based on the documented publication record, indexed research output, citation performance, and focus on innovative cybersecurity methodologies, Divya Gautam demonstrates characteristics commonly associated with recognition through an Innovative Research Award. Her research emphasizes methodological development, practical applicability, interdisciplinary integration, and contribution to secure wireless networking technologies.[5]

Conclusion

Divya Gautam’s academic portfolio reflects sustained contributions to computer science, particularly in network security and intelligent attack detection for mobile ad hoc networks. Through the integration of machine learning and optimization techniques, her publications support ongoing developments in cybersecurity research while contributing to the broader understanding of resilient wireless communication systems. The documented scholarly record provides a solid foundation for academic recognition within innovation-oriented research awards.

References

  1. Elsevier. (n.d.). Scopus Author Details: Divya Gautam, Author ID 57315556700. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57315556700
  2. Gautam, D., & Tokekar, V. (2020). A Comparative Study of DoS Attack Detection and Mitigation Techniques in MANET. Lecture Notes in Networks and Systems, Springer. DOI: https://doi.org/10.1007/978-981-15-2071-6_50
  3. Gautam, D., & Tokekar, V. (2020). Pattern Based Detection and Mitigation of DoS Attacks in MANET Using SVM-PSO. Intelligent Computing Applications for Sustainable Real-World Systems.DOI: https://doi.org/10.1007/978-3-030-44758-8_16
  4. Gautam, D., & Tokekar, V. (2020). Fixed Points Results in b-Metric Spaces. Materials Today: Proceedings.
    https://doi.org/10.1016/j.matpr.2021.05.147
  5. SVKM’s NMIMS. (n.d.). Faculty Profile: Dr. Divya Gautam, Assistant Professor, Computer Engineering.
    https://indore.nmims.edu/faculty/dr-divya-gautam/

Md Minhajul Amin | Computer Science | Best Innovator Award

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Best Innovator Award

Md Minhajul Amin
Affiliation Intento Analytics
Country United States
Google Scholar 8Cc4X70AAAAJ
Documents 11
Citations 86
h-index 4
Subject Area Computer Science
Event International Academic Achievements & Awards

Md Minhajul Amin
Intento Analytics, United States

Md Minhajul Amin is a data analyst and researcher specializing in business analytics, artificial intelligence, healthcare informatics, project management, and big data applications. His multidisciplinary research integrates predictive analytics, machine learning, digital healthcare, and operational decision-making. Through academic publications, IEEE conference papers, industrial projects, and editorial activities, he has contributed to advancing evidence-based management and intelligent data-driven systems.[1]

Abstract

Md Minhajul Amin has established an interdisciplinary research portfolio connecting artificial intelligence, predictive analytics, healthcare systems, fraud detection, digital communication, and project management. His work emphasizes practical analytical solutions that improve organizational efficiency and support evidence-based decision-making across healthcare and business environments.[2]

Keywords

Business Analytics, Artificial Intelligence, Machine Learning, Healthcare Analytics, Telemedicine, Big Data, Project Management, Data Visualization, Predictive Analytics, Digital Transformation.

Introduction

Holding an M.S. in Information Systems from Central Michigan University, Md Minhajul Amin combines academic research with industry experience in data analytics. His research focuses on solving real-world organizational challenges through statistical analysis, visualization, artificial intelligence, and business intelligence technologies.[3]

Research Profile

  • IEEE conference contributor.
  • Associate Editor at IFR Discovery.
  • Editorial Board Member of The Science Post Journal.

Research Contributions

His publications cover ethical business analytics, AI-powered project management, fraud detection, cancer classification using machine learning, telemedicine implementation, customer segmentation, healthcare dashboards, RF communication systems, and network management technologies. His research demonstrates the practical integration of advanced analytics into healthcare, engineering, and organizational management.[4]

Publications

  • Ethical Challenges in Business Analytics.
  • Developing a Project Management Dashboard for Telehealth.
  • Business Analytics in the Era of Big Data.
  • AI-Powered Personalized Marketing.
  • Classification of Cancer Stages Using Machine Learning.

Research Impact

His scholarly output has attracted citations across business analytics, healthcare informatics, artificial intelligence, and project management disciplines. His professional activities further include patented AI-driven analytical devices and collaborative research addressing practical industry challenges.

Award Suitability

Considering his multidisciplinary research portfolio, peer-reviewed publications, IEEE conference participation, editorial responsibilities, industrial analytics experience, and measurable research impact, Md Minhajul Amin demonstrates qualifications aligned with recognition under an Innovative Research Award category.

Conclusion

Md Minhajul Amin continues contributing to applied research that bridges artificial intelligence, business analytics, healthcare systems, and project management. His academic achievements and industry experience illustrate the growing role of data-driven methodologies in addressing modern organizational and societal challenges.

External Links

References

    1. Amin, M. M., Munmun, Z. S., Atayeva, J., Ahmed, S. W., Shamim, I., & Akter, M. H. (2025).
      Developing a Project Management Dashboard for Telehealth Implementation.
      https://www.researchgate.net/publication/392591167_Developing_a_Project_Management_Dashboard_for_Telehealth_Implementation
    2. Google Scholar. (2026).
      Md Minhajul Amin – Google Scholar Profile.
      https://scholar.google.com/citations?user=8Cc4X70AAAAJ&hl=en
    3. ResearchGate. (2026).
      Md Minhajul Amin – Research Profile.
      https://www.researchgate.net/profile/Md-Minhajul-Amin
    4. LinkedIn. (2026).
      Md Minhajul Amin – Professional Profile.
      https://www.linkedin.com/in/md-minhajul-amin-cmu

Pritha Gupta | Information Security | Best Researcher Award

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Ms. Pritha Gupta | Information Security | Best Researcher Award

Ms. Pritha Gupta | Information Security – Postdoctoral Researcher at Ruhr University Bochum, Germany

Pritha Gupta is a promising early-career researcher in the field of artificial intelligence, with a focus on security, privacy, and automated decision systems. Her growing academic profile reflects a commitment to research that bridges machine learning with practical challenges in trustworthy AI. Having co-authored multiple peer-reviewed articles and collaborated with well-established researchers across Europe, Gupta is positioning herself as an emerging voice in secure AI systems and interpretable machine learning.

Profile Verified:

Google Scholar

Education:

Gupta has pursued a rigorous academic path in computer science and artificial intelligence, culminating in advanced research conducted at Universität Paderborn. Her academic training is complemented by specialized work in machine learning algorithms, statistical modeling, and applied cryptography. Throughout her education, she has maintained a strong theoretical foundation while focusing on problem-driven research that aligns with current industry and academic needs.

Experience:

During her academic and research journey, Gupta has worked alongside leading scientists in computer science and cybersecurity. She has gained practical and research experience through collaborations with senior professors and researchers at Paderborn University, Wuppertal University, and Karlstad University. Her projects span the design of autonomous systems, ranking algorithms, information leakage detection, and AI-based attack modeling. Gupta’s ability to integrate complex AI models with real-world application challenges, such as cryptographic vulnerabilities and privacy breaches, showcases her deep technical expertise and interdisciplinary thinking.

Research Interests:

Her research centers around trustworthy AI, privacy-preserving systems, automated machine learning (AutoML), and explainable AI (XAI). Gupta’s work increasingly emphasizes side-channel attack detection, secure protocol design, and context-dependent learning, making her research highly relevant in today’s AI-driven digital ecosystems. She is particularly drawn to the ethical and technical dimensions of AI, focusing on how to make machine learning both robust and understandable in sensitive applications.

Awards:

Though still early in her career, Gupta’s contributions have been recognized through selection for collaborative international research projects and co-authorship in high-impact workshops and symposia. Her work has garnered citations from both academic and applied communities, reflecting its relevance and originality. With increasing visibility in the AI and cybersecurity research circuits, she is a strong candidate for early-career and emerging researcher recognitions.

Publications 📚:

  • 🛻 “Design and implementation of autonomous car using Raspberry Pi” – International Journal of Computer Applications, 2015 – Cited by: 115
  • 🔄 “Pairwise versus pointwise ranking: A case study” – Schedae Informaticae, 2016 – Cited by: 24
  • 🧠 “Learning Context-Dependent Choice Functions” – International Journal of Approximate Reasoning, 2021 – Cited by: 19
  • 🔓 “Automated Side-Channel Attacks using Black-Box Neural Architecture Search” – ARES Conference, 2023 – Cited by: 9
  • 🕵️‍♀️ “Automated detection of side channels in cryptographic protocols: DROWN the ROBOTs!” – ACM Workshop on AI and Security, 2021 – Cited by: 9
  • 📊 “Meta-learning for automated selection of anomaly detectors for semi-supervised datasets” – International Symposium on Intelligent Data Analysis, 2023 – Cited by: 3
  • 🔐 “Information leakage detection through approximate Bayes-optimal prediction” – arXiv preprint, 2024 – Cited by: 1

Conclusion:

Pritha Gupta exemplifies the attributes of an emerging researcher whose academic rigor, innovative research contributions, and commitment to secure and interpretable AI systems make her an ideal nominee for the Best Researcher Award. Her portfolio combines technical depth, collaborative strength, and real-world relevance, backed by peer recognition through citations and impactful publications. While early in her professional journey, Gupta is steadily building a reputation in AI security and machine learning theory, with a trajectory that strongly indicates future leadership in the field. Her contributions not only advance academic understanding but also address critical societal and technological challenges, making her work valuable across disciplines and sectors. In recognition of her growing impact, innovative thinking, and dedication to responsible AI, she is highly deserving of this honor.

Aitor Brazaola-Vicario | Cybersecurity | Best Researcher Award

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Mr. Aitor Brazaola-Vicario | Cybersecurity | Best Researcher Award

Cybersecurity Researcher | Tecnalia Research & Innovation | Spain

Aitor Brazaola-Vicario is a computer engineer with a focus on cybersecurity and Quantum Communications. Graduating from the University of Deusto in 2016, he has developed a robust career spanning software development and cybersecurity. His professional journey includes significant roles at CERN and ITP Aero, where he contributed to service management and network security. Currently, he is pursuing a PhD in Communications Engineering at the University of the Basque Country, researching innovative applications of Quantum Communications.

Profile

ORCID

Strengths for the Award

  1. Diverse and Relevant Experience:
    • The candidate has a strong background in both software development and cybersecurity, with significant roles at CERN and ITP Aero. This diverse experience highlights their versatility and depth of knowledge in critical areas of technology and security.
  2. Specialized Research Focus:
    • Their current research in Quantum Communications at Tecnalia Research & Innovation shows a commitment to exploring cutting-edge technologies. The focus on integrating quantum technologies into critical societal infrastructure and enhancing security reflects a forward-thinking approach to solving modern challenges.
  3. Notable Achievements:
    • The candidate has received the “Premio al mejor artículo de Transferencia” at the Jornadas Nacionales de Investigación en Seguridad, indicating recognition for their high-quality research and contribution to the field.
  4. Strong Academic and Professional Background:
    • With a Master’s degree and ongoing PhD studies in Computer Engineering and Communications, respectively, the candidate has a solid educational foundation. Their work on influential publications, such as those on IIOT platforms and Quantum Key Distribution, further underscores their research capabilities.
  5. High-impact Publications:
    • Publications in reputable journals like Future Generation Computer Systems and Optics Continuum, along with contributions to conference papers, demonstrate their active engagement and influence in their research area.

Areas for Improvement

  1. Broader Research Impact:
    • While the candidate has notable publications and a significant role in advanced research, increasing the dissemination of their findings through more diverse platforms or collaborations could amplify their impact. Engaging in more interdisciplinary projects might also enhance their visibility in different research communities.
  2. Professional Network Expansion:
    • Building a broader professional network by attending more international conferences or participating in collaborative research projects could provide additional opportunities for recognition and feedback.
  3. Public Engagement:
    • Improving efforts to communicate their research to a non-specialist audience through public talks, popular science articles, or media engagement could enhance the societal impact of their work.

Education

Aitor Brazaola-Vicario holds a Bachelor’s and Master’s degree in Computer Engineering from the University of Deusto. He is currently advancing his academic career as a PhD student at the University of the Basque Country, specializing in Quantum Communications and its integration into critical societal infrastructure.

Experience

Aitor’s professional experience began as a fullstack developer at LIN3S. He later joined CERN as a ServiceNow developer, leading the development of a new service management portal. From 2019 to 2023, he worked at ITP Aero as a cybersecurity engineer, focusing on network security, vulnerability analysis, and information security policies. He is currently a cybersecurity researcher at Fundación Tecnalia Research & Innovation.

Research Interest

Aitor’s research interests are centered on Quantum Communications and their application in enhancing the security of critical infrastructures. His work aims to explore and develop innovative solutions for integrating quantum technologies in high-stakes environments, pushing the boundaries of current cybersecurity practices.

Award

Aitor received the “Premio al mejor artículo de Transferencia” at the Jornadas Nacionales de Investigación en Seguridad (JNIC) in May 2024, recognizing his outstanding contribution to research in cybersecurity.

Publication

“A multi-level IIOT platform for boosting mines digitalisation”
Future Generation Computer Systems
Link to publication
Published: August 2024

“Quantum Key Distribution. A survey on current vulnerability trends and potential implementation risks”
Optics Continuum
Link to publication
Published: July 2024

“Migración de una aplicación industrial a un entorno Quantum Safe: Comunicaciones industriales QKD”
Jornadas Nacionales de Investigación en Ciberseguridad (JNIC)
Link to conference paper
Published: May 2024

Conclusion

The candidate presents a compelling case for the Best Researcher Award due to their extensive experience, specialized focus on Quantum Communications, and notable achievements in cybersecurity and digital technologies. Their research contributions, particularly in advancing quantum technology and securing critical infrastructure, demonstrate a significant commitment to addressing future challenges in the field.

While there are areas for potential growth, such as expanding their professional network and increasing public engagement, their current accomplishments and ongoing research position them as a strong contender for the award. Their innovative approach and proven track record make them a deserving candidate for recognition as a leading researcher in their field.

Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award

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Prof. Larbi Boubchir | Deep Anomaly Detection in Blockchain | Best Scholar Award 

Professor | University of Paris 8 | France

Based on the detailed profile of Prof. Dr. Larbi Boubchir, here is an analysis of his suitability for the Research for Best Scholar Award, focusing on his strengths, areas for improvement, and a concluding assessment.

Strengths

  1. Extensive Research Contributions: Prof. Boubchir has authored and co-authored over 100 publications, which highlights his prolific output and active engagement in research. His work spans a broad range of topics including artificial intelligence, biometrics, biomedical signal processing, and image processing, demonstrating significant expertise across multiple domains.
  2. Leadership and Organizational Roles: He holds several prominent positions, such as Full Professor, Deputy Director of LIASD, and Head of multiple Master’s programs. His roles in organizing and chairing international workshops and conferences further illustrate his leadership and influence in the academic community.
  3. Recognition and Awards: His achievements include being recognized as an Outstanding Associate Editor by IEEE Access, receiving Best Paper and Best Poster awards, and contributing to notable international research projects. These accolades reflect the high quality and impact of his research.
  4. Diverse Teaching Experience: Prof. Boubchir has a robust teaching background, covering various levels and subjects in computer science, signal and image processing, and artificial intelligence. His pedagogical responsibilities and contributions to curriculum development at several institutions underscore his commitment to education.
  5. Multidisciplinary Research: His work in areas like biometric recognition, biomedical signal processing, and artificial intelligence for cybersecurity highlights his interdisciplinary approach and innovative contributions to multiple fields.

Areas for Improvement

  1. Interdisciplinary Collaboration: While Prof. Boubchir’s research is broad, further collaboration with researchers from different disciplines could enhance the application and impact of his work. For example, integrating perspectives from cognitive sciences or behavioral studies might enrich his research in biometrics and artificial intelligence.
  2. Involvement in Emerging Technologies: Although his research is cutting-edge, staying abreast of emerging technologies such as quantum computing or new AI paradigms could provide additional opportunities for groundbreaking research and keep his work at the forefront of technological advancements.
  3. Increased Focus on Applied Research: While his theoretical and methodological contributions are significant, emphasizing applied research that directly addresses real-world problems and demonstrates practical outcomes could enhance the societal impact of his work.

Short Biography

Prof. Dr. Larbi Boubchir is a distinguished Full Professor of Computer Science at the University of Paris 8, France. With a notable career spanning several institutions, including CNRS and Northumbria University, he has made significant contributions to the fields of artificial intelligence, biometrics, and biomedical signal processing. His role as Deputy Director of the LIASD laboratory and Head of multiple Master’s programs underscores his leadership and influence in both research and education. Prof. Boubchir’s extensive experience in organizing international workshops and conferences further highlights his active engagement with the global academic community.

Profile

ORCID

Education

Prof. Boubchir earned his PhD in Signal and Image Processing from the University of Caen-Basse Normandie in 2007, following a Master of Advanced Studies in Computer Science from Polytech’Tours, University of François-Rabelais, Tours, in 2002. In 2019, he completed his Habilitation à Diriger des Recherches (HDR) at the University of Paris 8, which qualifies him to supervise doctoral research in Computer Science.

Experience

Prof. Boubchir has held numerous academic positions throughout his career. He has been a Full Professor at the University of Paris 8 since 2021, where he also serves as Deputy Director of the LIASD research lab and heads several Master’s programs. Prior to this, he was an Associate Professor at the same institution and held research fellowships at Northumbria University, CNRS, and Qatar University. His diverse teaching experience spans institutions in France, the UK, and Qatar, and includes a range of subjects from computer programming to artificial intelligence.

Research Interests

Prof. Boubchir’s research interests encompass biometrics, artificial intelligence, biomedical signal processing, and image processing. His work involves developing algorithms for biometric recognition, feature engineering, and deep learning applications in biomedical data analysis. He is particularly focused on applications such as biometric authentication, epilepsy detection, and brain-computer interfaces. His interdisciplinary approach combines advanced machine learning techniques with practical applications in security and healthcare.

Awards

Prof. Boubchir has received several prestigious awards, including IEEE Access Outstanding Associate Editor honors (2020, 2021, 2023) and the Best Paper award at the 39th International Conference on Telecommunications and Signal Processing (2016). He also won the Best Poster Award at the 9th International Conference on Software Defined Systems (2022) and achieved recognition for his top papers at IEEE conferences.

Publications

Here are some of Prof. Boubchir’s notable publications:

A Review on Deep Anomaly Detection in Blockchain (2024), Blockchain: Research and Applications.

Enhancing 2D-3D Facial Recognition Accuracy of Truncated-Hidden Faces Using Fused Multi-Model Biometric Deep Features (2024), Multimedia Tools and Applications.

Deep Speech Recognition System Based on AutoEncoder-GAN for Biometric Access Control (2023), International Journal of Advanced Computer Science and Applications (IJACSA).

Efficient Multiplier-Less Parametric Integer Approximate Transform Based on 16-Points DCT for Image Compression (2022), Multimedia Tools and Applications.

Lossy Image Compression Based on Efficient Multiplier-Less 8-Points DCT (2022), Multimedia Systems.

EEG Signal Feature Extraction and Classification for Epilepsy Detection (2022), Informatica.

Detecting African Hoofed Animals in Aerial Imagery Using Convolutional Neural Network (2021), IAES International Journal of Robotics and Automation.

Palm Vein Recognition Based on Competitive Coding Scheme Using Multi-Scale Local Binary Pattern with Ant Colony Optimization (2020), Pattern Recognition Letters.

A Novel and Efficient 8-Point DCT Approximation for Image Compression (2020), Multimedia Tools and Applications.

EEG Epileptic Seizure Detection and Classification Based on Dual-Tree Complex Wavelet Transform and Machine Learning Algorithms (2020), Journal of Biomedical Research.

Conclusion

Prof. Dr. Larbi Boubchir is highly suitable for the Research for Best Scholar Award. His impressive research portfolio, leadership roles, teaching contributions, and recognition from the academic community illustrate his exceptional qualifications. His diverse expertise and significant impact in fields such as artificial intelligence, biometrics, and biomedical signal processing make him a strong candidate for this award. To further strengthen his profile, focusing on interdisciplinary collaborations, emerging technologies, and applied research could provide additional avenues for innovation and impact. Overall, Prof. Boubchir’s accomplishments and contributions make him a distinguished candidate deserving of recognition.

Abdulrahman Alzahrani | Cybersecurity | Best Researcher Award

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Dr. Abdulrahman Alzahrani | Cybersecurity | Best Researcher Award 

Assistant professor | University of Hafr Al Batin | Saudi Arabia

Research for Best Researcher Award: Abdulrahman Alzahrani

Strengths for the Award:

  1. Extensive Expertise and Experience: Abdulrahman Alzahrani holds a PhD in Computer Science and Informatics with a specialization in Mobile Security & Privacy, and he has significant experience in related fields such as Information Security, Steganography, Computer Networks, and Operating Systems. His extensive knowledge and experience are evident in his diverse research projects and publications.
  2. Innovative Research Projects: His projects, such as RanDetector and DDefender, showcase innovative approaches to security issues in mobile and web applications. The RanDetector project, for instance, employs machine learning to detect Android ransomware with high efficacy, while DDefender integrates static and dynamic analysis for threat detection. These projects highlight his ability to address current security challenges with cutting-edge solutions.
  3. Contributions to Web and Mobile Security: Alzahrani has made notable contributions to both web and mobile security. His work on evaluating web application security tools and analyzing vulnerabilities is crucial for improving web security standards. His research on Android applications and ransomware detection is particularly relevant given the increasing threats in mobile security.
  4. Leadership and Service: His roles as Dean and Advisor at the University of Hafr Al Batin, along with his involvement in various committees, demonstrate his leadership and commitment to academic and institutional advancement. His service in educational outreach programs further underscores his dedication to promoting computer science education.
  5. Strong Publication Record: Alzahrani has an impressive list of publications in reputable conferences and journals. His work is frequently cited and covers a wide range of topics within his field, reflecting his active contribution to advancing knowledge in computer science and security.

Areas for Improvement:

  1. Broader Interdisciplinary Engagement: While his focus has been on mobile and web security, expanding his research to include interdisciplinary approaches could enhance his impact. For example, integrating insights from fields like data science, artificial intelligence, or behavioral science could provide more comprehensive solutions to security problems.
  2. Increased Collaboration with Industry: Greater collaboration with industry partners could bridge the gap between theoretical research and practical application. Strengthening ties with industry could lead to more applied research opportunities and potentially more substantial impacts on real-world security challenges.
  3. Diversification of Research Topics: Expanding his research portfolio to include emerging areas such as quantum computing security or privacy in emerging technologies could diversify his contributions and keep pace with rapidly evolving technology trends.
  4. Public Engagement and Outreach: Enhancing efforts to communicate his research findings to a broader audience, including the general public and policymakers, could increase the societal impact of his work. This might involve writing popular science articles, participating in public talks, or engaging in science policy discussions.

Short Biography

Dr. Abdulrahman Alzahrani is an accomplished Assistant Professor and Dean of the College of Computer Science and Engineering at the University of Hafr Al Batin, Saudi Arabia. With a PhD in Computer Science and Informatics from Oakland University, his research expertise spans Mobile Security and Privacy, Information Security, Steganography, Computer Networks, and Operating Systems. His innovative contributions to cybersecurity and his leadership roles in academia highlight his significant impact on the field.

Profile

Google Scholar

Education

Dr. Alzahrani earned his PhD in Computer Science & Informatics from Oakland University in August 2019, where he focused on Mobile Security and Privacy. Prior to that, he completed his Master of Science in Computer Science at the University of Bridgeport in December 2014 and his Bachelor of Science in Computer Science from Al-Baha University in June 2010.

Experience

Dr. Alzahrani’s professional experience includes notable positions at the University of Hafr Al Batin as Assistant Professor and Dean of the College of Computer Science and Engineering. He has also served as a Research Assistant, REU Mentor, and Visiting Professor at Oakland University. His earlier roles include leadership in educational camps and IT administration in various Saudi organizations.

Research Interests

Dr. Alzahrani’s research interests are centered on Mobile Security and Privacy, Information Security, Steganography, and Computer Networks. His work involves developing advanced detection systems for malware, analyzing web application vulnerabilities, and exploring privacy issues in autonomous vehicles.

Awards

Dr. Alzahrani’s work has been recognized with various accolades, including best paper awards at international conferences and funding from prestigious organizations such as the National Science Foundation. His innovative research continues to receive acknowledgment within the academic and professional communities.

Publications

Alshahrani, H., Alshehri, A., Alzahrani, A., & Fu, H. (2021). Web-based Malware Detection for Android OS. The 2021 International Conference on Computational Science and Computational Intelligence, Las Vegas, USA.

Alzahrani, A., Alshehri, A., Alshahrani, H., & Fu, H. (2020). Ransomware in Windows and Android Platforms. arXiv preprint arXiv:2005.05571.

Alzahrani, A., Alshahrani, H., Alshehri, A., & Fu, H. (2019). An Intelligent Behavior-Based Ransomware Detection System for Android Platform. The First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications, Los Angeles, CA, USA.

Alzahrani, A., Alshehri, A., Alshahrani, H., Alharthi, R., Fu, H., Liu, A., & Zhu, Y. (2018). RanDroid: Structural Similarity Approach for Detecting Ransomware Applications in Android Platform. 2018 IEEE International Conference on Electro Information Technology, Rochester, Michigan.

Alshehri, A., Marcinek, P., Alzahrani, A., Alshahrani, H., & Fu, H. (2019). PUREDroid: Permission Usage and Risk Estimation for Android Application. The 3rd International Conference on Information System and Data Mining (ICISDM 2019), Houston, TX. (Best paper award).

Conclusion:

Abdulrahman Alzahrani is a highly qualified candidate for the Best Researcher Award. His strengths lie in his extensive research experience, innovative contributions to mobile and web security, and active leadership roles in academia. His significant publications and successful projects further reinforce his suitability for the award.

To maximize his potential and impact, focusing on interdisciplinary research, fostering industry collaborations, and expanding his research topics and public engagement could be beneficial. Overall, Alzahrani’s accomplishments and dedication to advancing computer science make him a strong contender for this prestigious recognition.

Abdallah Houcheimi | Information Systems | Best Researcher Award

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Mr. Abdallah Houcheimi | Information Systems | Best Researcher Award

Doctor Researcher | Åbo Akademi University | Finland

Short Bio 🌟

Abdallah Houcheimi, born on September 22, 1981, is a university instructor and researcher specializing in information systems. With dual addresses in Bekaa, Lebanon, and Turku, Finland, he combines his expertise in business administration and technology to advance academic and practical knowledge in e-commerce, decision analytics, and artificial intelligence solutions. You can reach him via email at Abdallah.Houcheimi@abo.fi or Skype at ahouchimi@gmail.com.

Profile

ORCID

Education 🎓

Abdallah Houcheimi is currently pursuing a D.Sc. in Information Systems, expected to be completed in October 2024, at Åbo Akademi University in Turku, Finland. He holds a Master of Business Administration in International Business, obtained with Merit in 2015 from the University of Liverpool, UK. His foundational education includes a B.S. in Information Technology, earned in 2006 from the Lebanese International University, Lebanon.

Experience 👨‍🏫

Abdallah Houcheimi has a diverse professional background, starting as an Information Technology Support Analyst at Exceed IT Services Company in Abu Dhabi, UAE, and progressing to roles such as IT Project Leader at the Abu Dhabi Investment Authority (ADIA) and Managing IT Projects at Alpha Data. He served as Assistant Dean and instructor at the Lebanese International University and is currently a full-time doctoral researcher at Åbo Akademi University.

Research Interests 🔬

Abdallah’s research focuses on e-commerce, decision analytics, and artificial intelligence applications across various business domains. His work aims to enhance the understanding and implementation of secure online payment systems, online product information, and the role of social media in electronic retailing (e-tailing).

Awards 🏆

Throughout his career, Abdallah Houcheimi has been recognized for his contributions to academia and the field of information systems. His innovative research and commitment to education have earned him respect and accolades within the academic community.

Publications 📚

Abdallah Houcheimi has contributed several notable publications to the field of information systems:

  1. Houcheimi, A., & Mezei, J. (2024). “The Role of Secure Online Payments in Enabling the Development of E-Tailing.” Journal of Organizational Computing and Electronic Commerce. Read here. Cited by articles in leading journals.
  2. Houcheimi, A., & Mezei, J. (2024). “The Role of Online Product Information in Enabling Electronic Retail/E-tailing.” In: Rocha, Á., et al. (eds) Good Practices and New Perspectives in Information Systems and Technologies. Springer, Cham. Read here.
  3. Houcheimi, A. (2022). “The Key E-Tail Opportunities and Challenges in The Lebanese E-Commerce Market.” Journal of Information System and Technology Management, 7(26), 13-31. Read here.
  4. Houcheimi, A. (In Press). “The Role of Social Media Networks in Enabling the Development of Electronic Retail (E-Tailing).” Submitted to Knowledge and Information Systems Journal.

 

 

Wolali Ametepe | Information security | Best Researcher Award

Published on by Academic Achievements

Dr. Wolali Ametepe | Information security | Best Researcher Award

Lecturer and researcher, BlueCrest University College, Ghana

Wolali Ametepe is a seasoned educator and researcher with a diverse background in Information Technology. He holds a PhD in Information Technology from the University of Central Nicaragua and has served as a lecturer and researcher at various institutions globally, including Dominion University and Sikkim Manipal University.

Profile

Google Scholar

 

🎓 Education:

Wolali completed his PhD in Information Technology at the University of Central Nicaragua in December 2021. Prior to this, he earned a Master’s degree from Open University Malaysia and a Bachelor’s degree in Information Communication Technology from the University of Science, Commerce, and Business Administration.

💼 Experience:

He has held teaching and research positions at Dominion University, Sikkim Manipal University, and Accra Institute of Technology, among others. His expertise spans computer networking, e-business, cybersecurity, and artificial intelligence.

🔬 Research Interests:

Wolali’s research interests include data provenance, cybersecurity, cloud computing, and social engineering.

🏆 Awards:

He has been recognized with awards such as the Sino-graduate conference Best Oral Presentation and Best Poster awards, as well as the Jiangsu Presidential Yearly Award.

 publications:

Lightweight Intuitive Provenance (LiP) in a distributed computing environment, International Journal of Computer Applications, Link, 2018

Data provenance collection and security in a distributed environment: a survey, International Journal of Computer Applications, Link, 2018

The impact of social media on the Youth: The Ghanaian perspective, International Journal of Engineering Technology and Sciences, Link, 2016

Dynamic searchable encryption with privacy protection for cloud computing, International Journal of Communication Systems, Link, 2017

Analyzing Customers’ Perception of Service Quality of Ghanaian Telecommunication Industry, Journal of Marketing and Consumer Research, 2015