Siliang Ma | Computer Science | Best Researcher Award

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Dr. Siliang Ma | Computer Science | Best Researcher Award

Senior Algorithm Engineer at School of Computer Science and Engineering, South China University of Technology, China

Dr. Siliang Ma, a Ph.D. candidate at South China University of Technology, is an accomplished researcher specializing in computer science with a focus on image processing and machine learning. With an excellent academic record, including a bachelor’s degree from South China Agricultural University (GPA: 3.99/5), Dr. Ma has made significant contributions to cutting-edge research. His works, published in esteemed journals such as Acta Automatica Sinica and Image and Vision Computing, address topics like calligraphy character recognition, multilingual scene text spotting, and efficient bounding box regression through novel loss functions like MPDIoU and FPDIoU. A skilled programmer proficient in Python, Java, and C#, he has developed robust image processing algorithms and software applications. Dr. Ma also contributes as a reviewer for leading conferences like ICRA and ICASSP, reflecting his commitment to advancing the research community. His innovative and impactful work positions him as a rising talent in computational science.

Professional Profile 

Education

Dr. Siliang Ma has a strong educational background in computer science and engineering. He is currently pursuing a Ph.D. at the South China University of Technology, where he has maintained an excellent GPA of 86.33/100. His doctoral research focuses on cutting-edge topics in image processing, machine learning, and computational algorithms, demonstrating both theoretical depth and practical relevance. Prior to this, Dr. Ma earned his bachelor’s degree from South China Agricultural University, graduating with a remarkable GPA of 3.99/5. His undergraduate studies in mathematics and informatics laid a solid foundation for his advanced research pursuits, equipping him with the analytical and technical skills essential for solving complex computational problems. Through rigorous academic training and dedication, Dr. Ma has excelled in his education, which is further reflected in his extensive publications in high-impact journals and his active engagement in academic conferences and peer reviews.

Professional Experience

Dr. Siliang Ma has gained valuable professional experience through diverse roles in research and industry, complementing his academic achievements. He interned as a Data Analyst at the China Construction Bank Guangdong Branch Technology Center, where he conducted financial data analysis using PostgreSQL, mastering database operations and complex linked table queries. As a Quality Engineer at the China Mobile Guangdong Branch Business Support Center, he developed a JavaWeb-based minimum feature set for user registration, login, and management, and implemented automated quality testing workflows using Jenkins. These roles allowed Dr. Ma to hone his skills in software development, data analysis, and quality assurance, showcasing his ability to translate theoretical knowledge into practical applications. Additionally, his expertise in programming and image processing has led to impactful contributions in academia, particularly in algorithm development. This blend of industrial and research experience positions Dr. Ma as a versatile professional in computer science and engineering.

Research Interest

Dr. Siliang Ma’s research interests lie at the intersection of computer vision, machine learning, and image processing. He is particularly focused on developing innovative algorithms and techniques for efficient and accurate object detection, scene text recognition, and character recognition. His work explores advanced loss functions, such as MPDIoU and FPDIoU, to optimize bounding box regression for both traditional and rotated object detection. Additionally, Dr. Ma has a keen interest in multilingual scene text spotting, where he leverages character-level features and benchmarks to improve the accuracy of text recognition across diverse languages. His research extends to robust graph learning and hypergraph-enhanced self-supervised models for social recommendation systems, showcasing his ability to address complex, real-world challenges. Through his work, Dr. Ma aims to bridge theoretical advancements with practical applications, contributing to the broader fields of artificial intelligence, data analysis, and computational optimization.

Award and Honor

Dr. Siliang Ma has been recognized for his academic and research excellence through various accolades and contributions. As a Ph.D. candidate at South China University of Technology, his consistent high performance, reflected in his impressive GPA, underscores his dedication to academic rigor. Although specific awards or honors are not explicitly listed in his profile, his role as a reviewer for prestigious conferences such as ICRA and ICASSP highlights his esteemed position within the research community. Dr. Ma’s impactful publications in top-tier journals and conferences, including Acta Automatica Sinica and Image and Vision Computing, further demonstrate the high regard in which his work is held. His innovative contributions to image processing and machine learning have earned him recognition as a rising talent in his field. These achievements reflect Dr. Ma’s commitment to advancing computational science and his growing influence in academic and professional circles.

Conclusion

Siliang Ma is a strong candidate for the Best Researcher Award due to his impressive academic record, significant publications, and technical expertise. His contributions to advanced image processing algorithms and innovative loss functions for object detection demonstrate technical ingenuity and research excellence. To further strengthen his profile, he could expand his research impact through interdisciplinary work, mentorship roles, and greater industry engagement.

Publications Top Noted

  • Title: FPDIoU Loss: A loss function for efficient bounding box regression of rotated object detection
    Authors: Siliang Ma, Yong Xu
    Year: 2024
    Citation: Ma, S., & Xu, Y. (2024). FPDIoU Loss: A loss function for efficient bounding box regression of rotated object detection. Image and Vision Computing. https://doi.org/10.1016/j.imavis.2024.105381
  • Title: Rethinking Multilingual Scene Text Spotting: A Novel Benchmark and a Character-Level Feature Based Approach
    Authors: Siliang Ma, Yong Xu
    Year: 2024
    Citation: Ma, S., & Xu, Y. (2024). Rethinking Multilingual Scene Text Spotting: A Novel Benchmark and a Character-Level Feature Based Approach. American Journal of Computer Science and Technology. https://doi.org/10.11648/j.ajcst.20240703.12

Peixian Zhuang | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Peixian Zhuang | Computer Science | Best Researcher Award

Associate Professor at University of Science and Technology Beijing, China 

Assoc. Prof. Dr. Peixian Zhuang is a distinguished researcher in computer vision, machine learning, and underwater image processing. Currently an Associate Professor at the University of Science and Technology Beijing, he earned his Ph.D. from Xiamen University in 2016. With over 50 published papers, including 9 ESI Highly Cited/Hot Papers and over 2800 Google Scholar citations, his work has garnered significant academic influence. Dr. Zhuang has led four national projects, holds six patents, and authored a book, showcasing his commitment to advancing technological innovation. His contributions have been recognized globally, as he was listed among the “World’s Top 2% Scientists” in 2023 and 2024. In addition to his research, he serves as an editor for various esteemed journals and has reviewed over 100 international journals and conferences. His collaborations with institutions like Tsinghua University further underscore his dedication to expanding the boundaries of AI and image processing.

Professional profile

Education

Assoc. Prof. Dr. Peixian Zhuang completed his Ph.D. in 2016 at Xiamen University, where he laid the foundation for his research expertise in computer vision, underwater image processing, and machine learning. Following his doctoral studies, he began his academic career as a Lecturer at Nanjing University of Information Science & Technology (2017-2020), where he further honed his skills and contributed to his fields of study. To deepen his research, Dr. Zhuang undertook postdoctoral training at Tsinghua University (2020-2022), engaging in advanced projects and expanding his expertise in innovative AI technologies. His educational journey has been marked by significant contributions to his field, earning him recognition as a “World’s Top 2% Scientist” in recent years. Dr. Zhuang’s robust academic background has established him as a leading researcher and educator, influencing both national and international advancements in machine learning and image processing.

Professional Experience

Assoc. Prof. Dr. Peixian Zhuang has a diverse professional background in academia and research. Currently serving as an Associate Professor at the University of Science and Technology Beijing, he has made significant contributions to the fields of underwater image processing and machine learning. Prior to this role, he was a Lecturer at Nanjing University of Information Science & Technology from 2017 to 2020, where he developed and delivered courses while conducting impactful research. Following this, Dr. Zhuang completed a postdoctoral fellowship at Tsinghua University (2020-2022), where he engaged in advanced research projects and collaborations with leading scientists. He has led four national research projects and has authored over 50 papers, showcasing his commitment to scientific advancement. In addition to his academic roles, he serves as an area editor and guest editor for various reputable journals, reflecting his expertise and active engagement in the global research community.

Research Interest

Assoc. Prof. Dr. Peixian Zhuang specializes in several cutting-edge areas within the fields of computer vision and machine learning. His primary research interests include underwater image processing, where he focuses on improving the quality and usability of images captured in challenging underwater environments. He employs advanced algorithms and techniques to enhance image clarity and object recognition. Additionally, Dr. Zhuang is deeply invested in Bayesian machine learning, exploring probabilistic models that can improve decision-making processes in uncertain environments. His work on signal sparse representation and deep neural networks further highlights his commitment to developing innovative solutions for complex problems in artificial intelligence. By integrating these methodologies, Dr. Zhuang aims to advance the understanding and application of AI in real-world scenarios. His research not only contributes to theoretical advancements but also has practical implications in fields such as marine science, environmental monitoring, and robotics, making a significant impact on technology and research.

Awards and Honors

Assoc. Prof. Dr. Peixian Zhuang has received numerous awards and honors throughout his academic career, reflecting his significant contributions to research and innovation. He was recognized as one of the “World’s Top 2% Scientists” in both 2023 and 2024, an accolade that highlights his impact and influence in the field of computer vision and machine learning. In 2023, he received the IFAC EAAI Paper Prize Award, underscoring the excellence of his research publications. Additionally, his doctoral dissertation was awarded the Outstanding Doctoral Dissertations of Fujian Province in 2017, recognizing the quality and originality of his work during his Ph.D. studies. Dr. Zhuang has also been involved in various editorial roles for reputable journals, enhancing his recognition as a leading researcher in his field. These awards and honors reflect his dedication to advancing scientific knowledge and his commitment to excellence in research and education.

Conclusion

Peixian Zhuang’s profile makes him a strong candidate for the Best Researcher Award. His influential research, substantial publication record, recognition in global scientific rankings, and engagement in scholarly activities demonstrate his commitment and impact in the field of computer vision and underwater image processing. Addressing the outlined areas of improvement could enhance his profile further, positioning him as a leading researcher capable of impacting both academia and industry.

Publications top noted📜
  • Title: A retinex-based enhancing approach for single underwater image
    Authors: X Fu, P Zhuang, Y Huang, Y Liao, XP Zhang, X Ding
    Year: 2014
    Citations: 566
  • Title: Underwater image enhancement using a multiscale dense generative adversarial network
    Authors: Y Guo, H Li, P Zhuang
    Year: 2019
    Citations: 420
  • Title: Underwater image enhancement via minimal color loss and locally adaptive contrast enhancement
    Authors: W Zhang, P Zhuang, HH Sun, G Li, S Kwong, C Li
    Year: 2022
    Citations: 373
  • Title: Bayesian retinex underwater image enhancement
    Authors: P Zhuang, C Li, J Wu
    Year: 2021
    Citations: 255
  • Title: Underwater image enhancement with hyper-laplacian reflectance priors
    Authors: P Zhuang, J Wu, F Porikli, C Li
    Year: 2022
    Citations: 250
  • Title: Underwater image enhancement using an edge-preserving filtering retinex algorithm
    Authors: P Zhuang, X Ding
    Year: 2020
    Citations: 93
  • Title: Underwater image enhancement via weighted wavelet visual perception fusion
    Authors: W Zhang, L Zhou, P Zhuang, G Li, X Pan, W Zhao, C Li
    Year: 2023
    Citations: 86
  • Title: Removing stripe noise from infrared cloud images via deep convolutional networks
    Authors: P Xiao, Y Guo, P Zhuang
    Year: 2018
    Citations: 80
  • Title: Underwater image enhancement via piecewise color correction and dual prior optimized contrast enhancement
    Authors: W Zhang, S Jin, P Zhuang, Z Liang, C Li
    Year: 2023
    Citations: 77
  • Title: Non-uniform illumination underwater image restoration via illumination channel sparsity prior
    Authors: G Hou, N Li, P Zhuang, K Li, H Sun, C Li
    Year: 2023
    Citations: 54
  • Title: CVANet: Cascaded visual attention network for single image super-resolution
    Authors: W Zhang, W Zhao, J Li, P Zhuang, H Sun, Y Xu, C Li
    Year: 2024
    Citations: 49
  • Title: DewaterNet: A fusion adversarial real underwater image enhancement network
    Authors: H Li, P Zhuang
    Year: 2021
    Citations: 49
  • Title: SSTNet: Spatial, spectral, and texture aware attention network using hyperspectral image for corn variety identification
    Authors: W Zhang, Z Li, HH Sun, Q Zhang, P Zhuang, C Li
    Year: 2022
    Citations: 45
  • Title: Bayesian pan-sharpening with multiorder gradient-based deep network constraints
    Authors: P Guo, P Zhuang, Y Guo
    Year: 2020
    Citations: 41
  • Title: GIFM: An image restoration method with generalized image formation model for poor visible conditions
    Authors: Z Liang, W Zhang, R Ruan, P Zhuang, C Li
    Year: 2022
    Citations: 37

Imtiaz Ahmad | Computer Science | Best Researcher Award

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Mr. Imtiaz Ahmad | Computer Science | Best Researcher Award

Visiting lecturer at Hazara University Mansehra, Pakistan

Imtiaz Ahmad, a dedicated researcher and educator from Pakistan, holds a Master’s degree in Computer Science from Hazara University, with a focus on wireless sensor networks. His thesis, titled “Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Networks,” reflects his expertise in optimizing data transmission for modern networks. Imtiaz has published research in reputable journals, including Knowledge-Based Systems and VFAST Transactions on Software, focusing on wireless sensor networks and mobile edge computing. With several years of teaching experience at institutions like Hazara University, he has mentored students and contributed to academic growth. His achievements include the Best Researcher Award and several student accolades. Additionally, he holds certifications like Microsoft Office Specialist and vocational training in computers. Imtiaz is a promising researcher with strengths in data aggregation, mobile computing, and teaching, and he continues to make valuable contributions to the field of computer science.

Professional profile

Education

Imtiaz Ahmad holds a Master’s degree in Computer Science from Hazara University Mansehra, which he completed in March 2021 with a commendable CGPA of 3.71/4.00. His master’s thesis focused on developing an “Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Networks,” showcasing his expertise in advanced computing concepts. Prior to this, he earned a Bachelor of Science in Information Technology from the University of Malakand in March 2015, achieving a CGPA of 2.95/4.00. His undergraduate thesis was centered on creating an “Online Hospital Management System,” which streamlined patient reservations and record management. Imtiaz also gained valuable experience through an internship at Hazara University, where he addressed technical issues related to system and application software. His educational background reflects a strong foundation in computer science and information technology, emphasizing both theoretical knowledge and practical application.

Professional Experience

Mr. Imtiaz Ahmad has accumulated valuable professional experience in academia and technical roles. Currently, he serves as a Visiting Lecturer at Hazara University Mansehra, where he is responsible for planning and delivering lectures, supervising final year projects, and assessing student progress. Previously, he held positions as a Computer Science Lecturer at Abaseen Public School and College and New Shaheen College of Commerce, where he implemented computer education programs and provided hands-on training in programming languages.

Additionally, during his internship at Hazara University, he gained practical experience in resolving technical issues, installing software, and setting up multimedia for national conferences. His diverse roles demonstrate his commitment to education and his ability to convey complex concepts to students, while also highlighting his technical skills in information technology. This blend of teaching and technical expertise positions him as a promising educator and researcher in the field of computer science.

Research Interest

Mr. Imtiaz Ahmad’s research interests lie primarily in the fields of wireless sensor networks, mobile edge computing, and data aggregation methodologies. His work focuses on developing adaptive and priority-based models that enhance the efficiency and reliability of data transmission in sensor networks. By optimizing scheduling techniques, Imtiaz aims to improve the performance of wireless systems, making them more resilient to data loss and delays. He is also interested in mobility prediction and task migration within mobile edge computing environments, exploring innovative solutions that facilitate seamless connectivity and resource management. Through his research, Imtiaz seeks to contribute to the advancement of smart technologies and the Internet of Things (IoT), addressing critical challenges in data management and network performance. His commitment to applying theoretical knowledge to real-world applications underscores his desire to drive impactful innovations in computer science.

Awards and Honors

Mr. Imtiaz Ahmad, a dedicated researcher and educator in computer science, has garnered several prestigious awards and honors throughout his academic journey. In 2024, he received the Best Researcher Award at the International Academic Awards, recognizing his impactful research on adaptive data aggregation models in wireless sensor networks. Previously, in 2020, he was honored with the Best Student Researcher Award from the Department of Computer Science at Hazara University, highlighting his exceptional contributions during his studies. Additionally, he was named the Student of the Year at Hazara University in 2019, further showcasing his academic excellence. Imtiaz was also awarded a laptop under the Prime Minister’s Laptop Scheme for High Achievers by the Higher Education Commission of Pakistan in 2018. These accolades reflect his commitment to research and education, marking him as a prominent figure in his field.

Conclusion

Imtiaz Ahmad has demonstrated a solid academic and research profile with notable strengths in computer science, particularly in wireless sensor networks and mobile edge computing. His publications in respected journals, combined with his teaching and professional certifications, make him a strong contender for the Best Researcher Award. However, to further solidify his candidacy, he could focus on enhancing the visibility and impact of his research through broader collaborations and more high-impact publications. Overall, his achievements suggest that he is well-suited for the award and poised to make significant contributions to his field in the future.

Publications top noted📜
  • Title: Adaptive and Priority-Based Data Aggregation and Scheduling Model for Wireless Sensor Networks
    Authors: Imtiaz Ahmad, Muhammad Adnan, Noor ul Amin, Asif Umer, Adnan Khurshid, Khursheed Aurangzeb, Muhammad Gulistan
    Journal: Knowledge-Based Systems
    Year: 2024
    DOI: 10.1016/j.knosys.2024.112393
    ISSN: 0950-7051
  • Title: A Mobility Prediction-Based Adaptive Task Migration in Mobile Edge Computing
    Authors: Jawad Arshed, Mehtab Afzal, Muhammad Hashim, Imtiaz Ahmad, Hasnat Ali, Ghulam Hussain
    Journal: VFAST Transactions on Software Engineering
    Year: 2024
    DOI: 10.21015/vtse.v12i2.1768
    ISSN: 2309-3978, 2411-6246

Ruotao Xu | Computer Science | Best Researcher Award

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Dr. Ruotao Xu | Computer Science | Best Researcher Award

Associate Researcher at Institute of Super Robotics(Huangpu), China 

Ruotao Xu is a dedicated researcher specializing in robotics, computer vision, and image processing. As a Postdoctoral Researcher and Associate Researcher, he is at the forefront of exploring advanced techniques in deep learning and image analysis. 🚀

Professional profile

Education📚

Ruotao Xu earned his Ph.D. in Electrical Engineering, where he focused on image processing and robotics. His educational background provides a solid foundation for his research endeavors and contributions to the field. 🎓📚

Professional Experience🏛️

Currently serving as a Postdoctoral Researcher at the Institute of Robotics and Automatic Information Systems, Xu has led several significant research projects. His role includes managing projects funded by national and provincial science foundations and contributing to various high-impact publications. 🛠️📈

Research Interest🌐

Xu’s research interests lie in deep learning, image processing, defocus deblurring, image inpainting, and texture representation. He is particularly focused on developing innovative solutions and technologies in these areas to advance the field of computer vision. 🧠🔍

Awards and Honors🎓
  • Principal Investigator for multiple high-profile projects funded by the National Natural Science Foundation of China. 🏆
  • Contributor to leading journals such as IEEE Transactions on Image Processing and IEEE/CVF International Conference on Computer Vision. 🥇📜
Achievements🏅
  • Principal Investigator for multiple high-profile projects funded by the National Natural Science Foundation of China. 🏆
  • Lead Author on influential papers in top journals such as IEEE Transactions on Image Processing and IEEE/CVF International Conference on Computer Vision. 📜
  • Innovator in Image Processing with a focus on deep learning, defocus deblurring, image inpainting, and texture representation. 🧠
  • Received Grants from provincial and national science foundations for cutting-edge research projects. 💵
  • Contributed to High-Impact Publications with significant citations, reflecting the impact of research on the field. 📚
  • Collaborated with Leading Researchers and institutions, enhancing the reach and application of his research findings. 🤝
Publications top noted📜
  • “Multi-view 3D shape recognition via correspondence-aware deep learning”
    Authors: Y Xu, C Zheng, R Xu, Y Quan, H Ling
    Journal: IEEE Transactions on Image Processing
    Year: 2021
    Citations: 40 📈
  • “Structure-texture image decomposition using discriminative patch recurrence”
    Authors: R Xu, Y Xu, Y Quan
    Journal: IEEE Transactions on Image Processing
    Year: 2020
    Citations: 20 📈
  • “Attention with structure regularization for action recognition”
    Authors: Y Quan, Y Chen, R Xu, H Ji
    Journal: Computer Vision and Image Understanding
    Year: 2019
    Citations: 19 📈
  • “Removing reflection from a single image with ghosting effect”
    Authors: Y Huang, Y Quan, Y Xu, R Xu, H Ji
    Journal: IEEE Transactions on Computational Imaging
    Year: 2019
    Citations: 19 📈
  • “Factorized tensor dictionary learning for visual tensor data completion”
    Authors: R Xu, Y Xu, Y Quan
    Journal: IEEE Transactions on Multimedia
    Year: 2021
    Citations: 17 📈
  • “Image quality assessment using kernel sparse coding”
    Authors: Z Zhou, J Li, Y Quan, R Xu
    Journal: IEEE Transactions on Multimedia
    Year: 2020
    Citations: 13 📈
  • “Cartoon-texture image decomposition using orientation characteristics in patch recurrence”
    Authors: R Xu, Y Xu, Y Quan, H Ji
    Journal: SIAM Journal on Imaging Sciences
    Year: 2020
    Citations: 10 📈
  • “Deep scale-aware image smoothing”
    Authors: J Li, K Qin, R Xu, H Ji
    Conference: ICASSP 2022
    Year: 2022
    Citations: 7 📈
  • “Enhancing texture representation with deep tracing pattern encoding”
    Authors: Z Chen, Y Quan, R Xu, L Jin, Y Xu
    Journal: Pattern Recognition
    Year: 2024
    Citations: 6 📈
  • “No-reference image quality assessment using dynamic complex-valued neural model”
    Authors: Z Zhou, Y Xu, R Xu, Y Quan
    Conference: 30th ACM International Conference on Multimedia
    Year: 2022
    Citations: 4 📈
  • “Deeply exploiting long-term view dependency for 3D shape recognition”
    Authors: Y Xu, C Zheng, R Xu, Y Quan
    Journal: IEEE Access
    Year: 2019
    Citations: 4 📈
  • “Deep blind image quality assessment using dual-order statistics”
    Authors: Z Zhou, Y Xu, Y Quan, R Xu
    Conference: IEEE International Conference on Multimedia and Expo (ICME)
    Year: 2022
    Citations: 3 📈
  • “Wavelet analysis model inspired convolutional neural networks for image denoising”
    Authors: R Xu, Y Xu, X Yang, H Huang, Z Lei, Y Quan
    Journal: Applied Mathematical Modelling
    Year: 2024
    Citations: 2 📈

Fouzia Elazzaby | Computer Science | Best Researcher Award

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Ms. Fouzia Elazzaby | Computer Science | Best Researcher Award

Docteur at Universite ibn tofail, Morocco

Fouzia Elazzaby is a dedicated and accomplished academic with a passion for computer science and its applications. Based in Fes, Morocco, she has made significant strides in her field through teaching, research, and practical projects. Known for her strong organizational skills, teamwork, and commitment to continuous learning, she is a valuable contributor to both the academic and professional communities. 🌍📚

Professional profile

Education📚

Fouzia holds a Doctorate in Informatics from FSK UIT, Kénitra, completed in May 2023. She also has a Master’s degree in Informatics, Graphics, and Imaging (M3I) from FSDM, Fes, obtained in July 2012, and a Bachelor’s degree in Mathematics and Computer Science from the same institution, earned in July 2008. Her academic journey started with a Baccalaureate in Experimental Sciences in 2004. 🎓💻

Professional Experience🏛️

With over a decade of teaching experience, Fouzia has been an educator at the Office of Vocational Training and Employment Promotion since 2009. Additionally, she has served as a visiting professor at the Ecole Normale Supérieure de Fès and the Ecole Nationale des Sciences Appliquées de Fès. She also worked as a trainer at Atlas Engineering & Consulting Society, where she contributed her expertise in 2022-2023. 🧑‍🏫🏢

Research Interest🌐

Fouzia’s research interests lie primarily in the field of image encryption and the application of chaotic systems in computer science. She has published several papers on innovative encryption schemes, using complex mathematical theories like the Heisenberg group and Zigzag transformations. Her work contributes to advancing security in digital imaging, making her a key player in her area of expertise. 🔒🖼️

Achievements🏅
  • 🏅 Doctorate in Informatics: Earned in May 2023 from FSK UIT, Kénitra.
  • 🖥️ Master’s Degree in Informatics, Graphics, and Imaging (M3I): Completed in July 2012 from FSDM, Fes.
  • 📜 Bachelor’s Degree in Mathematics and Computer Science: Obtained in July 2008 from FSDM, Fes.
  • 🧑‍🏫 Over a Decade of Teaching Experience: Teaching at the Office of Vocational Training and Employment Promotion since 2009.
  • 🎓 Visiting Professor: Held positions at Ecole Normale Supérieure de Fès and Ecole Nationale des Sciences Appliquées de Fès.
  • 🔐 Published Multiple Research Papers: Authored articles in reputable journals and conferences, focusing on advanced image encryption techniques.
  • 📚 Contributed to Book Chapters: Co-authored chapters on encryption algorithms in well-regarded publications.
  • 🗣️ Oral Presentations at International Conferences: Presented research findings at several prestigious conferences in Morocco and abroad.
  • 💼 Trainer at Atlas Engineering & Consulting Society: Provided professional training in 2022-2023.
  • 🌍 Multilingual: Fluent in Arabic, French, and English, enabling effective communication and collaboration across different regions.
Publications top noted📜
  • 📝 A New Encryption Scheme for RGB Color Images by Coupling 4D Chaotic Laser Systems and the Heisenberg Group
    • Authors: Elazzaby, F., Akkad, N.E., Sabour, K., Kabbaj, S.
    • Year: 2024
    • Journal: Multimedia Tools and Applications
    • Citations: 4
  • 📝 The Coupling of a Multiplicative Group and the Theory of Chaos in the Encryptions of Images
    • Authors: Elazzaby, F., Elakkad, N., Sabour, K.
    • Year: 2024
    • Journal: International Arab Journal of Information Technology
    • Citations: 1
  • 📝 Color Image Encryption Using a Zigzag Transformation and Sine–Cosine Maps
    • Authors: Elazzaby, F., Sabour, K.H., Elakkad, N., Torki, A., Rajkumar, S.R.
    • Year: 2023
    • Journal: Scientific African
    • Citations: 1
  • 📝 A New Contribution of Image Encryption Based on Chaotic Maps and the Z/nZ Group
    • Authors: Elazzaby, F., Akkad, N.E., Sabour, K., Kabbaj, S.
    • Year: 2023
    • Journal: Journal of Theoretical and Applied Information Technology
    • Citations: 2
  • 📝 An RGB Image Encryption Algorithm Based on Clifford Attractors with a Bilinear Transformation
    • Authors: Elazzaby, F., Akkad, N.E., Sabour, K., Kabbaj, S.
    • Year: 2022
    • Conference: Lecture Notes in Networks and Systems
    • Citations: 4
  • 📝 Advanced Encryption of Image Based on S-Box and Chaos 2D (LSMCL)
    • Authors: Elazzaby, F., Akkad, N.E., Kabbaj, S.
    • Year: 2020
    • Conference: 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)
    • Citations: 9
  • 📝 A New Encryption Approach Based on Four-Square and Zigzag Encryption (C4CZ)
    • Authors: Elazzaby, F., El Akkad, N., Kabbaj, S.
    • Year: 2020
    • Conference: Advances in Intelligent Systems and Computing
    • Citations: 13

Sachin Kumar Verma | Computer Science | Best Researcher Award

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Mr. Sachin Kumar Verma | Computer Science | Best Researcher Award

Senior Executive and Researcher at Samsung SDS, India

Sachin Kumar Verma is a highly skilled researcher and developer with a robust educational background in Computer Science and Engineering. Holding an M.Tech from IIITDM Jabalpur and a B.Tech from NIET Gr. Noida, Verma has demonstrated a strong grasp of advanced topics such as Machine Learning and IoT. His technical proficiency spans programming languages, hardware integration, and dynamic problem-solving. 🌟

Professional profile

Education📚

Sachin Kumar Verma has a solid educational foundation in Computer Science and Engineering. He completed his M.Tech from IIITDM Jabalpur with a CGPA of 7.7 and his B.Tech from NIET Gr. Noida with a CGPA of 7.14. This educational background provides him with a strong theoretical and practical understanding of the field, which is crucial for research excellence.

Professional Experience🏛️

Sachin’s experience at Samsung SDS as a Senior Executive and Software Developer Intern showcases his practical expertise in software development, specifically in ABAP, SAP S/4 HANA, and SAP Hybris Marketing. His role involved advanced programming and project work, which enhances his research and problem-solving skills. Additionally, his position as a Teaching Assistant at IIITDM Jabalpur allowed him to impart knowledge on data structures and algorithms, further enriching his research skills through teaching.

Research Interest🌐

During his tenure at IIITDM Jabalpur, Verma worked on a significant research project related to mitigating DAO Insider Attacks in RPL-based IoT Networks. This work, published in the IEEE Region 10 Symposium, reflects his ability to address complex problems in IoT networks. This research demonstrates his capability to contribute to the field of computer science and engineering through practical and theoretical advancements.

Awards and Honors🏆

Sachin Kumar Verma has been recognized for his contributions to the field through notable awards and achievements. He secured 1st prize at a Hackathon held at Sharda University in 2019 and played a key role in the Smart India Hackathon (SIH) 2019 as a volunteer. 🏆 His research work, particularly on mitigating DAO Insider Attacks in IoT networks, has been published in prestigious IEEE conferences, showcasing his dedication to addressing complex technological challenges. 📜

Achievements🏅

His project on S-MAV (Smart Vehicle) utilized a range of technologies and tools, demonstrating his ability to apply theoretical knowledge to real-world problems. Winning 1st prize in a Hackathon and volunteering for the Smart India Hackathon further illustrate his commitment to innovation and problem-solving in technology.

Publications top noted📜

Yiren Chen | Computer Science | Best Researcher Award

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Dr Yiren Chen | Computer Science | Best Researcher Award

research associate at Institute of Information Engineering, Chinese Academy of Sciences, China

Dr. Yiren Chen, a PhD student at the Institute of Information Engineering, Chinese Academy of Sciences, specializes in cyberspace security. He has contributed to various projects, including Internet of Vehicles security management (2022), robot simulation control (2021), and the development of a white flow filtering system (2021). Currently, he is focusing on the application of large language models in cyberspace security (2023-present). Dr. Chen has published two SCI-indexed papers, one EI-indexed conference paper, and a book. His notable work includes the paper “A Survey of Large Language Models for Cyber Threat Detection,” published in the journal Computers & Security in 2024. This paper highlights the significant advancements and key issues in network threat detection using large language models and proposes future research directions. Dr. Chen’s ongoing research and practical contributions to cybersecurity have been instrumental in developing products applied in national security projects.

Professional profile

Education and Qualifications

Dr. Yiren Chen is a PhD student at the Institute of Information Engineering, Chinese Academy of Sciences. His specialization is in Cyberspace Security, particularly in Cyberspace Security Situation Awareness. His educational background and current academic pursuits demonstrate a strong foundation in a highly relevant and specialized area.

Research Experience and Projects

Dr. Chen has participated in various significant research projects, including:

  • Internet of Vehicles security management (2022)
  • Robot simulation control and white flow filtering system development (2021)
  • Application research of large language models on cyberspace security (2023-present)

His involvement in these projects highlights his practical and theoretical contributions to the field of cybersecurity.

Publications and Academic Achievements

Dr. Chen has published two SCI-indexed papers, one EI-indexed conference paper, and authored a book. This publication record is impressive for a PhD student and indicates active and successful engagement in research. Notably, his paper titled “A Survey of Large Language Models for Cyber Threat Detection” has been published in a recognized journal, reflecting the relevance and impact of his work.

Contributions to Research and Development

Dr. Chen’s research focuses on applying large language models like GPT and BERT to cybersecurity challenges. His contributions include developing practical products for national security projects and publishing research papers that explore the application and potential of these models in cyber threat detection. His work is forward-looking and addresses key issues in the field, making significant strides in both theoretical and practical aspects of cybersecurity.

Conclusion

Considering Dr. Chen’s strong educational background, active research involvement, notable publications, and contributions to cybersecurity, he appears to be a highly deserving candidate for the “Best Researcher Award.” His work not only advances the academic field but also has practical implications for national security, highlighting his comprehensive impact on the discipline.

Publications top noted📜
  • Article
    • Topic: A survey of large language models for cyber threat detection
    • Year: 2024
    • Journal: Computers and Security 🖥️🔒
  • Conference Paper
    • Topic: Towards the Digital Twin Model of Li-Ion Batteries: State-of-Health (SoH) Prediction
    • Year: 2023
    • Journal: Lecture Notes in Electrical Engineering 🔋📘
  • Conference Paper (Open Access)
    • Topic: The Scheme for SOC Estimation of Lithium-ion Batteries based on EQ-OCV-Ah-EKF
    • Year: 2023
    • Journal: Journal of Physics: Conference Series 🔋📚

Ritika Ladha | Computer Science | Best Researcher Award

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Assist Prof Dr. Ritika Ladha | Computer Science | Best Researcher Award

Associate Professor of Adani University, India

Dr. Ritika Vivek Ladha is an esteemed academic and researcher currently serving as an Assistant Professor in the Department of Information and Communication Technology at Adani University. She completed her Ph.D. in Information and Communication Technology from Nirma University in 2022, following a Master’s in Information and Network Security and a Bachelor’s in Computer Science and Engineering.

Professional profile

Education📚

Dr. Ritika Vivek Ladha earned her Ph.D. in Information and Communication Technology from Nirma University in 2022. She completed her M.Tech. in Information and Network Security at Nirma University in 2015, with a CGPA of 8.42. Her undergraduate studies were conducted at A.D Patel Institute of Technology, where she obtained a B.E. in Computer Science and Engineering in 2013, achieving a CPI of 8.14.

Professional Experience🏛️

Dr. Ladha’s dedication to her field is further evidenced by her various professional recognitions and roles. She has received certifications in Cyber Security from IBM and is a member of the ACM. Her role as the Membership Chair for the Adani ACM-W Student Chapter and her involvement in conferences and professional organizations underscore her active engagement with the academic and research community.

Research Interest🌐

Dr. Ladha’s research interests span several cutting-edge areas, including deep learning, machine learning, recommender systems, network security, intrusion detection systems, and the Internet of Things (IoT). Her work has significantly contributed to advancing these fields, addressing key issues such as cybersecurity threats, feature selection, and machine learning-based intrusion detection.

Her contributions are well-documented through her publications in prestigious journals and conferences. Notable papers include reviews on phishing attack risk assessment and advancements in intrusion detection systems. Dr. Ladha’s work has garnered substantial recognition, with a Google Scholar citation count of 1,229, an h-index of 11, and an i10-index of 11, reflecting the impactful nature of her research.

Awards and Honors🏆

Dr. Ladha has received notable recognitions such as ACM Professional Membership, certification in Cyber Security from IBM, and participation in significant conferences. These achievements highlight her commitment to staying at the forefront of her field and her active engagement with professional communities.

Achievements🏅

Dr. Ladha’s achievements include earning a Certificate in Developing Enterprise Applications from NIIT in 2012 and becoming a Red Hat Certified System Administrator in 2018. In 2020, she was recognized for having articles in the 25 most downloaded papers of the Swarm and Evolutionary Journal. She is a member of ACM (2023) and has been endorsed by IBM with a Skill Build Course on Cyber Security Fundamentals and Artificial Intelligence in 2024. Additionally, she has been actively involved in academic and professional communities, including serving as the Membership Chair of the Adani ACM-W Student Chapter in 2023.

Publications top noted📜
  • “A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges”
    Authors: A. Thakkar, R. Lohiya
    Journal: Archives of Computational Methods in Engineering
    Year: 2021
    Citations: 📚 259
  • “A Review of the Advancement in Intrusion Detection Datasets”
    Authors: A. Thakkar, R. Lohiya
    Journal: Procedia Computer Science
    Year: 2020
    Citations: 📚 228
  • “A Survey on Intrusion Detection System: Feature Selection, Model, Performance Measures, Application Perspective, Challenges, and Future Research Directions”
    Authors: A. Thakkar, R. Lohiya
    Journal: Artificial Intelligence Review
    Year: 2022
    Citations: 📚 185
  • “Attack Classification Using Feature Selection Techniques: A Comparative Study”
    Authors: A. Thakkar, R. Lohiya
    Journal: Journal of Ambient Intelligence and Humanized Computing
    Year: 2021
    Citations: 📚 128
  • “Fusion of Statistical Importance for Feature Selection in Deep Neural Network-Based Intrusion Detection System”
    Authors: A. Thakkar, R. Lohiya
    Journal: Information Fusion
    Year: 2023
    Citations: 📚 114
  • “Application Domains, Evaluation Data Sets, and Research Challenges of IoT: A Systematic Review”
    Authors: R. Lohiya, A. Thakkar
    Journal: IEEE Internet of Things Journal
    Year: 2020
    Citations: 📚 84
  • “Role of Swarm and Evolutionary Algorithms for Intrusion Detection System: A Survey”
    Authors: A. Thakkar, R. Lohiya
    Journal: Swarm and Evolutionary Computation
    Year: 2020
    Citations: 📚 81
  • “Attack Classification of Imbalanced Intrusion Data for IoT Network Using Ensemble-Learning-Based Deep Neural Network”
    Authors: A. Thakkar, R. Lohiya
    Journal: IEEE Internet of Things Journal
    Year: 2023
    Citations: 📚 54
  • “Intrusion Detection Using Deep Neural Network with Anti-Rectifier Layer”
    Authors: R. Lohiya, A. Thakkar
    Journal: Applied Soft Computing and Communication Networks: Proceedings of ACN 2020
    Year: 2021
    Citations: 📚 36
  • “Analyzing Fusion of Regularization Techniques in the Deep Learning-Based Intrusion Detection System”
    Authors: A. Thakkar, R. Lohiya
    Journal: International Journal of Intelligent Systems
    Year: 2021
    Citations: 📚 28
  • “Survey on Mobile Forensics”
    Authors: R. Lohiya, P. John, P. Shah
    Journal: International Journal of Computer Applications
    Year: 2015
    Citations: 📚 28
  • “A Review on Challenges and Future Research Directions for Machine Learning-Based Intrusion Detection System”
    Authors: A. Thakkar, R. Lohiya
    Journal: Archives of Computational Methods in Engineering
    Year: 2023
    Citations: 📚 10

Rahul Chaurasia | Computer Science | Best Researcher Award

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Dr. Rahul Chaurasia | Computer Science | Best Researcher Award

Postdoc Researcher of IIT Indore , India

Rahul Chaurasia, Ph.D., is a distinguished post-doctoral researcher in the Department of Computer Science & Engineering at the Indian Institute of Technology Indore. With a Ph.D. in Computer Science & Engineering from IIT Indore, his research expertise lies in hardware security, hardware co-processor designs for machine learning applications, hardware acceleration, intellectual property protection (IPP), and computer architecture. His doctoral thesis, focused on IP core protection and detective control of data-intensive IPs against piracy, addresses crucial challenges in modern integrated circuit design, particularly safeguarding against IP piracy, fraudulent ownership claims, and reverse engineering.

Professional profile

Education📚

Rahul Chaurasia holds a Ph.D. in Computer Science & Engineering from the Indian Institute of Technology Indore, which is renowned for its rigorous academic standards. His thesis, focused on IP core protection and control against data-intensive IP piracy, demonstrates his deep expertise in a crucial area of hardware security. Additionally, his strong academic performance, reflected in his CGPA during both his M.Tech. and B.E. studies, further underscores his solid educational foundation.

Professional Experience🏛️

Chaurasia’s role as a Post-Doc Researcher with the Translational Research Fellowship at IIT Indore, combined with his experience as a teaching assistant, reflects his commitment to both research and education. His involvement in various conferences, as well as his service as a reviewer for prominent journals, indicates a high level of professional engagement and peer recognition.

Research Interest🌐

Chaurasia’s research in hardware security, particularly his development of solutions using biometrics and obfuscation, addresses significant challenges in intellectual property protection. His work on secure hardware designs for machine learning and multimedia applications has made noteworthy contributions to the field. The emphasis on practical and innovative solutions, such as hardware security approaches with minimal overhead, positions his research as highly relevant and impactful.

Awards and Honors🏆

Chaurasia’s role as a Post-Doc Researcher with the Translational Research Fellowship at IIT Indore, combined with his experience as a teaching assistant, reflects his commitment to both research and education. His involvement in various conferences, as well as his service as a reviewer for prominent journals, indicates a high level of professional engagement and peer recognition.

Achievements🏅

Rahul Chaurasia has made significant contributions to the field of hardware security, as evidenced by his multiple publications in high-impact journals such as IEEE Transactions on Consumer Electronics. His research has been recognized with several prestigious awards, including the Young Scientist Award in Computer Science Engineering and Information Technology from the M.P. Council of Science and Technology and the First Prize-Best Paper Award at the IEEE-iSES 2022 symposium. He has also been awarded the Translational Research Fellowship for his post-doctoral work at IIT Indore and has received fellowships from MHRD and AICTE during his Ph.D. and M.Tech. programs, respectively. His achievements reflect his dedication to advancing the field of computer science and his potential as a leading researcher in hardware security.

Publications top noted📜
  • Contact-less Palmprint Biometric for Securing DSP Coprocessors used in CE systems
    👨‍🔬 Anirban Sengupta, Rahul Chaurasia, Tarun Reddy
    📰 IEEE Transactions on Consumer Electronics 67 (3), 202-213
    📅 2021
    📑 Citations: 15
  • Secured Convolutional Layer IP Core in Convolutional Neural Network Using Facial Biometric
    👨‍🔬 Anirban Sengupta, Rahul Chaurasia
    📰 IEEE Transactions on Consumer Electronics 68 (3), 291-306
    📅 2022
    📑 Citations: 11
  • Securing IP Cores for DSP Applications Using Structural Obfuscation and Chromosomal DNA Impression
    👨‍🔬 Anirban Sengupta, Rahul Chaurasia
    📰 IEEE Access 10, 50903-50913
    📅 2022
    📑 Citations: 9
  • Robust Security of Hardware Accelerators Using Protein Molecular Biometric Signature and Facial Biometric Encryption Key
    👨‍🔬 Anirban Sengupta, Rahul Chaurasia, Aditya Anshul
    📰 IEEE Transactions on Very Large Scale Integration (VLSI) Systems
    📅 2023
    📑 Citations: 6
  • Quadruple Phase Watermarking during High Level Synthesis for Securing Reusable Hardware Intellectual Property Cores
    👨‍🔬 Mahendra Rathor, Aditya Anshul, K Bharath, Rahul Chaurasia, Anirban Sengupta
    📰 Computers and Electrical Engineering 105, 108476
    📅 2023
    📑 Citations: 4
  • Exploring Handwritten Signature Image Features for Hardware Security
    👨‍🔬 Mahendra Rathor, Anirban Sengupta, Rahul Chaurasia, Aditya Anshul
    📰 IEEE Transactions on Dependable and Secure Computing
    📅 2022
    📑 Citations: 4
  • Palmprint Biometric Versus Encrypted Hash Based Digital Signature for Securing DSP Cores used in CE Systems
    👨‍🔬 R Chaurasia, A Anshul, A Sengupta, S Gupta
    📰 IEEE Consumer Electronics Magazine 11 (5), 73-80
    📅 2022
    📑 Citations: 4
  • Blockchain Based Pharmaceutical Supply Chain and its Challenges: A Review and Proposed Solution
    👨‍🔬 UK Sahu, A Jain, R Chaurasia, KK Hiran
    📰 2023 IEEE International Conference on ICT in Business Industry & Government
    📅 2023
    📑 Citations: 3
  • Retinal Biometric for Securing JPEG Codec Hardware IP Core for CE Systems
    👨‍🔬 Rahul Chaurasia, Anirban Sengupta
    📰 IEEE Transactions on Consumer Electronics
    📅 2023
    📑 Citations: 3
  • Symmetrical Protection of Ownership Rights for IP Buyer and IP Vendor using Facial Biometric Pairing
    👨‍🔬 Rahul Chaurasia, Anirban Sengupta
    📰 2022 IEEE International Symposium on Smart Electronic Systems (iSES), 272-277
    📅 2022
    📑 Citations: 3
  • Security Vs Design Cost of Signature Driven Security Methodologies for Reusable Hardware IP Core
    👨‍🔬 Rahul Chaurasia, Anirban Sengupta
    📰 2022 IEEE International Symposium on Smart Electronic Systems (iSES), 283-288
    📅 2022
    📑 Citations: 1

Taher Al-Shehari | Computer Science | Best Researcher Award

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Dr. Taher Al-Shehari | Computer Science | Best Researcher Award

Senior Lecturer and Researcher of King Saud University, Saudi Arabia

Taher Ali Al-Shehari is a dedicated cybersecurity professional and educator with a robust background in computer science. Holding a Bachelor’s degree from King Khalid University and a Master’s degree from King Fahd University of Petroleum and Minerals, Taher has demonstrated exceptional academic performance and a commitment to the field. His career spans various roles, from technical support and research assistant to full-time lecturer and researcher at King Saud University. His objective is to advance cybersecurity research and education through innovative practices, contributing significantly to his institution and the broader academic community.

Professional profile

Education📚

Taher’s educational background is exemplary. He graduated with honors from King Khalid University with a Bachelor in Computer Science, boasting an impressive GPA of 4.7/5. He continued to excel academically, earning a Master’s in Computer Science from King Fahd University of Petroleum and Minerals with a GPA of 3.348/4. His strong educational foundation in computer science positions him as a knowledgeable and capable researcher in his field.

Professional Experience🏛️

Taher’s extensive professional experience underscores his capability and versatility. He has held various roles, from technical support and customer services to research assistant and data analyst, and now serves as a full-time lecturer and researcher at King Saud University. His responsibilities have included teaching numerous technical courses, conducting specialized training programs, and participating in curriculum development. His involvement in a research group at the Deanship of Scientific Research further solidifies his research credentials.

Research Interest🌐

Taher has contributed significantly to the field of cybersecurity through various research projects and publications. His research interests include text plagiarism detection, code similarity detection, geographic information systems, and information security. He has published several impactful papers, often serving as the corresponding author, indicating his leading role in these studies

Awards and Honors🏆

Taher’s achievements have been recognized through numerous awards and honors. These include appreciation certificates from various institutions for his contributions to data analysis, academic progression, question bank development, and technical course offerings. Notably, he won an award for designing the best Information Security technical syllabus, showcasing his expertise and innovative approach in the field of cybersecurity education.

Achievements🏅

Taher Ali Al-Shehari’s achievements reflect his expertise and dedication in cybersecurity. He has received numerous accolades, including appreciation certificates for his contributions to data analysis, academic progression, and curriculum development. Notably, he won an award for designing the best Information Security technical syllabus at King Saud University. His research contributions are significant, with publications in reputable journals and conferences on topics such as operating system fingerprinting, insider threat detection, and web browser security. His work has been widely recognized, underscoring his impact and leadership in the field. 📚🔐🏆

Publications top noted📜
  • “An Insider Data Leakage Detection Using One-Hot Encoding, Synthetic Minority Oversampling and Machine Learning Techniques”
    Year: 2021
    Journal: Entropy
    Citations: 117 📊
  • “A Multi-Tiered Framework for Insider Threat Prevention”
    Year: 2021
    Journal: Electronics
    Citations: 36 🛡️
  • “Empirical Detection Techniques of Insider Threat Incidents”
    Year: 2020
    Journal: IEEE Access
    Citations: 35 🔍
  • “Improving Operating System Fingerprinting Using Machine Learning Techniques”
    Year: 2014
    Journal: International Journal of Computer Theory and Engineering
    Citations: 29 💻
  • “Techniques and Countermeasures for Preventing Insider Threats”
    Year: 2022
    Journal: PeerJ Computer Science
    Citations: 16 🚫
  • “An Empirical Study of Web Browsers’ Resistance to Traffic Analysis and Website Fingerprinting Attacks”
    Year: 2018
    Journal: Cluster Computing Journal
    Citations: 14 🌐
  • “SCBC: Smart City Monitoring with Blockchain Using Internet of Things for and Neuro Fuzzy Procedures”
    Year: 2023
    Journal: Mathematical Biosciences and Engineering
    Citations: 12 🏙️
  • “Wireless Video Streaming Over Data Distribution Service Middleware”
    Year: 2012
    Conference: IEEE International Conference on Computer Science and Automation Engineering
    Citations: 9 📺
  • “Random Resampling Algorithms for Addressing the Imbalanced Dataset Classes in Insider Threat Detection”
    Year: 2023
    Journal: International Journal of Information Security
    Citations: 6 📉
  • “Insider Threat Detection Model Using Anomaly-Based Isolation Forest Algorithm”
    Year: 2023
    Journal: IEEE Access
    Citations: 4 🌲
  • “Enhancing Insider Threat Detection in Imbalanced Cybersecurity Settings Using the Density-Based Local Outlier Factor Algorithm”
    Year: 2024
    Journal: IEEE Access
    Citations: 1 🧩
  • “Insider Threat Detection in Cyber-Physical Systems: A Systematic Literature Review”
    Year: 2024
    Journal: Computers and Electrical Engineering
    Citations: — 📚
  • “TumorGANet: A Transfer Learning and Generative Adversarial Network-Based Data Augmentation Model for Brain Tumor Classification”
    Year: 2024
    Journal: IEEE Access
    Citations: — 🧠
  • “S2DN: Design of Robust Authentication Protocol with Session Key Establishment in Multi-Controller Based Software-Defined VANETs”
    Year: 2024
    Journal: Vehicular Communications
    Citations: — 🚗
  • “Mining the Opinions of Software Developers for Improved Project Insights: Harnessing the Power of Transfer Learning”
    Year: 2024
    Journal: IEEE Access
    Citations: — 🔄