Naeem Ullah | Computer Science | Best Researcher Award

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Mr. Naeem Ullah | Computer Science | Best Researcher Award

PhD Student at Software Engineering Research Group (SERG-UOM) University of Malakand, Pakistan

Mr. Naeem Ullah is a dedicated academic and researcher currently pursuing a PhD in Computer Science, with a focus on cybersecurity challenges in vehicle-to-vehicle communication from a software engineering perspective. Holding a strong academic record with a CGPA of 3.75/4.00, he has presented his research at international forums, such as the 2nd Annual International Workshop on Software Engineering, where he shared his Multivocal Literature Review (MLR) protocol on cybersecurity culture. Mr. Ullah has also received recognition for his teaching excellence, earning the Best Teacher Award in 2018. His work experience includes roles as a lecturer at the University Model College KPK, part-time tutor at Allama Iqbal Open University, and facilitator for continuous professional development programs for teachers. His research, currently under review, addresses crucial cybersecurity issues in vehicle-to-vehicle communications. Mr. Ullah’s commitment to furthering his knowledge is evident through multiple certifications in data science, networking, and cybersecurity.

Professional Profile 

Education

Mr. Naeem Ullah has a strong educational background in Computer Science. He is currently pursuing a PhD in Computer Science with a focus on cybersecurity challenges in vehicle-to-vehicle communication, maintaining an impressive CGPA of 3.75/4.00. His research aims to develop a mitigation model for cybersecurity issues in connected vehicle systems, reflecting his deep engagement with current technological challenges. Mr. Ullah completed his Master’s degree in Computer Science in 2019, achieving a CGPA of 3.7/4.00, with his thesis titled Software Development Process Improvement Model for Small Pakistani Software Development Companies. He also holds a Bachelor’s degree in Computer Science from 2014, with a CGPA of 3.62/4.00. His final year project, Auction Management System, showcased his ability to apply practical solutions to real-world problems. Mr. Ullah’s academic journey is marked by consistent excellence and a strong commitment to advancing his expertise in the field of computer science.

Professional Experience

Mr. Naeem Ullah has accumulated diverse professional experience in both academic and research roles. He has served as a Lecturer in Computer Science at the University Model College KPK, Peshawar, Pakistan, where he taught and mentored students in various computer science subjects. In addition, he has worked as a part-time tutor for Allama Iqbal Open University, Islamabad, since 2022, focusing on Information and Communication Technologies (ICT). Mr. Ullah has also contributed to teacher development programs, serving as a facilitator for the Continuous Professional Development (CPD) of Primary School Teachers (PSTs) through the Provincial Institute of Teacher Education (PITE) in KPK. His role as a part-time researcher at the Department of Computer Science and IT at the University of Malakand further underscores his involvement in academic research. Earlier in his career, he worked as a Secondary School Teacher at the Elementary and Secondary Education Department, KPK. His experiences reflect a blend of teaching, research, and educational development.

Research Interest

Mr. Naeem Ullah’s research interests primarily focus on cybersecurity, particularly in the context of emerging technologies such as vehicle-to-vehicle (V2V) communication. His PhD research investigates cybersecurity challenges and proposes mitigation models for securing V2V communication systems from a software engineering perspective. This area of research is highly relevant due to the increasing integration of connected vehicles and the need for secure communication protocols to protect sensitive data. Additionally, Mr. Ullah is interested in software engineering, with a particular emphasis on improving software development processes for small software companies in Pakistan, as demonstrated in his Master’s thesis. He has also contributed to the field of cybersecurity culture through his work on a Multivocal Literature Review (MLR) protocol, which identifies cybersecurity challenges and best practices in V2V communication. His research endeavors aim to address critical issues in both cybersecurity and software engineering, contributing to the development of safer, more efficient technologies.

Award and Honor

Mr. Naeem Ullah has received notable recognition for his academic and professional achievements. In 2022, he presented his Multivocal Literature Review (MLR) Protocol at the 2nd Annual International Workshop on Software Engineering (WSE-2022), organized by the Software Engineering Research Group at the University of Malakand. This presentation, focused on Cybersecurity Culture, showcased his expertise and contribution to the field of cybersecurity. Additionally, Mr. Ullah earned the prestigious Best Teacher Award from the Director of Elementary and Secondary Education, KPK, Pakistan, in 2018. This recognition highlights his excellence in teaching and his commitment to fostering the growth and development of his students. These awards and honors reflect Mr. Ullah’s dedication to advancing both his academic research and educational practices, demonstrating his commitment to the fields of computer science and cybersecurity while contributing positively to the educational community.

Conclusion

Naeem Ullah is a promising candidate for the Best Researcher Award, with a solid academic record, a focused and impactful research topic, and a commitment to both education and professional development. His strengths lie in his dedication to advancing cybersecurity research in emerging technologies like vehicle-to-vehicle communication and his capacity for leadership in educational initiatives. To further enhance his candidacy, Naeem could focus on increasing his research output, expanding his research scope, and engaging more in international collaborations to elevate the impact of his work.

Publications Top Noted

  • Title: Solutions to Cybersecurity Challenges in Secure Vehicle-to-Vehicle Communications: A Multivocal Literature Review
    Authors: Naeem Ullah, S.U. Khan, M. Niazi, A.A. Khan, J.A. Nasir
    Journal: Information and Software Technology
    Year: 2025
    Volume: 179
    Article ID: 107639
    Citations: 0
  • Title: Challenges and Their Practices in Adoption of Hybrid Cloud Computing: An Analytical Hierarchy Approach
    Authors: S.U. Khan, H.U. Khan, Naeem Ullah, R.A. Khan
    Journal: Security and Communication Networks
    Year: 2021
    Article ID: 1024139
    Citations: 2
  • Title: Internet of Things for Healthcare Using Effects of Mobile Computing: A Systematic Literature Review
    Authors: S. Nazir, Y. Ali, Naeem Ullah, I. García-Magariño
    Journal: Wireless Communications and Mobile Computing
    Year: 2019
    Article ID: 5931315
    Citations: 138
  • Title: Practices for Clients in the Adoption of Hybrid Cloud
    Authors: S.U. Khan, Naeem Ullah
    Journal: Proceedings of the Pakistan Academy of Sciences: Part A
    Year: 2017
    Volume: 54(1A)
    Pages: 13–32
    Citations: 3

Bader Alsharif | Computer Science | Best Innovation Award

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Dr. Bader Alsharif | Computer Science | Best Innovation Award

Florida Atlantic University, United States

Dr. Bader Alsharif is an accomplished PhD candidate in Computer Engineering with a strong background in teaching, technical support, and curriculum development. He has led innovative projects, including the first CISCO simulation lab in Saudi Arabia, and has managed over 300 devices, optimizing performance and security. With a focus on AI, Cybersecurity, and IoT, particularly in healthcare, Dr. Alsharif has published over 7 peer-reviewed papers. He has demonstrated leadership in both academic and technical spheres, guiding over 200 students and advocating for special needs education, ensuring their academic success. His expertise extends to training professionals, having conducted comprehensive courses for Saudi Telecom employees. Dr. Alsharif has shown a profound commitment to advancing technology and fostering inclusivity, particularly through his work with individuals with special needs. His work bridges technological innovation with social impact, positioning him as a forward-thinking leader in computer engineering and healthcare.

Professional Profile 

Education

Dr. Bader Alsharif has an extensive academic background, beginning with a Bachelor of Science in Computer Engineering from the College of Technology in Riyadh, Saudi Arabia, where he graduated in 2008. He further advanced his studies with a Master of Science in Computer Engineering from the Florida Institute of Technology, completing his degree in 2017. Currently, Dr. Alsharif is pursuing a Doctor of Computer Engineering at Florida Atlantic University in Boca Raton, USA, with an expected graduation date of 2025. His academic journey has been marked by a strong focus on integrating Artificial Intelligence (AI), Cybersecurity, and Internet of Things (IoT) technologies, particularly in healthcare applications. This multidisciplinary education has provided Dr. Alsharif with the expertise to contribute meaningfully to both research and practical innovations in these fields, bridging the gap between technology and real-world healthcare challenges.

Professional Experience

Dr. Bader Alsharif has a diverse professional background with extensive experience in both academia and technical roles. He currently serves as a Teaching Assistant at Florida Atlantic University, where he guides and evaluates over 30 students on engineering design projects and assists more than 200 students with project development and technical issues. Prior to this, Dr. Alsharif held a prominent role as a Lecturer at the Communications and Information College in Riyadh, Saudi Arabia, where he managed and maintained over 300 devices and led the installation of the first CISCO simulation lab in the country. This project, a significant innovation, involved the deployment of over 30 devices and routers. He also trained 100 employees from Saudi Telecom and designed assessments for instructors working with special needs students. Dr. Alsharif’s professional experience reflects a strong blend of technical expertise, leadership, and a commitment to education and inclusivity.

Research Interest

Dr. Bader Alsharif’s research interests lie at the intersection of Artificial Intelligence (AI), Cybersecurity, and the Internet of Things (IoT), with a particular focus on their applications in healthcare. He is deeply committed to exploring how these advanced technologies can be integrated to enhance patient outcomes and improve healthcare systems. His work aims to leverage AI algorithms to optimize medical data analysis, while also addressing critical security concerns in the rapidly growing field of IoT healthcare devices. Dr. Alsharif’s research also extends to the development of innovative solutions for securing healthcare networks and ensuring the privacy of sensitive patient information. With a strong academic foundation and several peer-reviewed publications, he is dedicated to advancing knowledge in these areas and exploring how cutting-edge technologies can be applied to solve real-world challenges in healthcare. His work demonstrates a commitment to both technological innovation and social impact, especially in the realm of health and well-being.

Award and Honor

Dr. Bader Alsharif has received numerous accolades for his contributions to academia and technology. His achievements include successfully leading the installation of the first CISCO simulation lab in Saudi Arabia, which became a groundbreaking project in the region, significantly enhancing the educational infrastructure for telecommunications. In recognition of his exceptional performance in teaching and technical support, he consistently achieved high job performance ratings, including scores no less than 99/100. Dr. Alsharif has also been honored for his commitment to inclusive education, particularly in advocating for and supporting students with special needs, ensuring their academic excellence. His research in AI, Cybersecurity, and IoT, particularly in the healthcare sector, has earned him recognition as a published researcher with over 7 peer-reviewed papers. Through his work, Dr. Alsharif has received recognition from academic institutions and industry professionals for his innovative contributions, leadership, and commitment to fostering technological advancements with social impact.

Conclusion

Bader Alsharif has demonstrated significant innovation across several key areas of AI, Cybersecurity, and IoT, particularly in healthcare. His leadership in education and advocacy for special needs individuals also reflects a deep commitment to both technological advancement and social impact. His ability to lead high-profile projects and publish extensively in relevant fields positions him as a strong candidate for the Best Innovation Award. However, expanding his research impact and involvement in larger-scale, cross-disciplinary projects could further elevate his candidacy. Overall, he has the potential to be an exceptional award recipient based on his innovative contributions and impact.

Publications Top Noted

  • Title: Deep learning technology to recognize American Sign Language alphabet
    Authors: B Alsharif, AS Altaher, A Altaher, M Ilyas, E Alalwany
    Year: 2023
    Citations: 14
  • Title: Internet of things technologies in healthcare for people with hearing impairments
    Authors: B Alsharif, M Ilyas
    Year: 2022
    Citations: 8
  • Title: Deep Learning Technology to Recognize American Sign Language Alphabet Using Multi-Focus Image Fusion Technique
    Authors: B Alsharif, M Alanazi, AS Altaher, A Altaher, M Ilyas
    Year: 2023
    Citations: 6
  • Title: Machine Learning Technology to Recognize American Sign Language Alphabet
    Authors: B Alsharif, M Alanazi, M Ilyas
    Year: 2023
    Citations: 4
  • Title: Enhancing cybersecurity in healthcare: Evaluating ensemble learning models for intrusion detection in the internet of medical things
    Authors: T Alsolami, B Alsharif, M Ilyas
    Year: 2024
    Citations: 3
  • Title: Multi-Dataset Human Activity Recognition: Leveraging Fusion for Enhanced Performance
    Authors: M Alanazi, B Alsharif, AS Altaher, A Altaher, M Ilyas
    Year: 2023
    Citations: 3
  • Title: Transfer learning with YOLOV8 for real-time recognition system of American Sign Language Alphabet
    Authors: B Alsharif, E Alalwany, M Ilyas
    Year: 2024
    Citations: 1
  • Title: Franklin Open
    Authors: B Alsharif, E Alalwany, M Ilyas
    Year: 2024
    Citations: Not available yet

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

Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

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Mrs. Khyati Bhupta | Medicinal Chemistry | Best Researcher Award

Assistant Professor at Dr Subhash University, India

Khyati Bhupta is a highly motivated and accomplished professor specializing in the field of pharmacy. She is dedicated to both teaching and research, with a passion for fostering student development using modern teaching methods and advanced pedagogy. Her work is defined by her dedication to innovation and academic excellence. Her experience and skills, particularly in the pharmaceutical sector, make her a valuable contributor to both academia and the industry.

Professional profile

Education 📚

Khyati holds a PhD in Pharmacy, which she earned in May 2013 from Dr. Subhash University, Gujarat. Prior to her PhD, she completed her Master’s in Pharmacy with a specialization in Quality Assurance from Gujarat Technological University in 2009, and her Bachelor’s in Pharmacy from Sardar Patel University in 2007. Her academic journey reflects a consistent focus on pharmaceutical sciences, with an emphasis on quality and research.

Professional Experience🎓

Over the years, Khyati has built extensive experience as a professor in pharmacy, contributing significantly to both teaching and research. She is skilled in handling pharmaceutical instruments and software, which has been vital in her research and practical work. Her expertise in communication and documentation further enhances her teaching capabilities, making her an effective educator who fosters learning through modern approaches and methodologies.

Research Interest🎓

Khyati’s research primarily focuses on pharmaceutical sciences, with significant work on benzothiazole derivatives, exploring their potential as antidiabetic and antiviral agents. She has published multiple papers on these topics in renowned journals such as MDPI and the Annals of the Romanian Society for Cell Biology. Her work also involves method development for pharmaceutical analysis, including titrimetric methods and RP-HPLC method development for drug estimation, reflecting her deep engagement in pharmaceutical research and innovation.

Awards and Honors 🏆

Khyati has received several recognitions for her contributions to research. In August 2022, she was granted a patent from the Government of India, demonstrating her innovative contributions to pharmaceutical science. Additionally, she received a grant from the SSIP (Student Startup and Innovation Policy) under the Gujarat Government in October 2023 for her work on a startup project, highlighting her potential in translating research into practical applications.

Publications top noted📜

  • BENZOTHIAZOLE: AS AN ANTIDIABETIC AGENT
    • Authors: Khyati Bhupta
    • Journal: Annals of the Romanian Society for Cell Biology
    • Year: 2021
    • Citations: N/A 📊💊
  • BENZOTHIAZOLE MOIETY AND ITS DERIVATIVES AS ANTIVIRAL AGENTS
    • Authors: Khyati Bhupta
    • Journal: MDPI
    • Year: 2021
    • Citations: N/A 🦠🔬
  • Biological Screening and Structure Activity Relationship of Benzothiazole
    • Authors: Khyati Bhupta
    • Journal: Research Journal of Pharmacy and Technology
    • Year: 2022
    • Citations: N/A 🧪📈
  • Development of Titrimetric Method for Estimation of Furosemide Tablets by Using Mixed Co-Solvency Process
    • Authors: Khyati Bhupta
    • Journal: International Journal of Biology, Pharmacy and Allied Sciences
    • Year: 2022
    • Citations: N/A ⚖️💊
  • RP-HPLC Method Development and Validation for Simultaneous Estimation of Ranitidine Hydrochloride and Domperidone in Combination
    • Authors: Khyati Bhupta
    • Journal: International Journal of Pharmacy, Biology and Allied Science
    • Year: 2023
    • Citations: N/A 📊🔬

Ruotao Xu | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

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

Published on by Global Scholar Awards

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 🔋📚