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: — 🔄

Padmini MS | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Mrs. Padmini MS | Computer Science | Best Researcher Award

Associate Professor of The National Institute of Engineering, India

Padmini M.S. is an accomplished Assistant Professor in the Department of Computer Science and Engineering at The National Institute of Engineering, Mysore, with over 13 years of experience in teaching and research 📚. She is currently pursuing her Ph.D. part-time at VTU, showcasing her dedication to continuous learning and professional growth 🎓. Padmini holds an M.Tech. in Computer Networks and a B.E. in Computer Science, reflecting her strong academic foundation 🖥️. Her research interests span IoT, energy efficiency, and smart environments, with numerous publications in reputable journals and international conferences 🌐. Padmini is known for her excellent communication skills, problem-solving ability, and adaptability to the latest technologies, making her a valuable team player and passionate educator 👩‍🏫.

Professional profile

Education📚

Padmini M.S. is currently pursuing a Ph.D. part-time at VTU, with plans to take her comprehensive viva shortly. She holds an M.Tech. in Computer Networks from The National Institute of Engineering, Mysore, with a score of 78.5%, and a B.E. in Computer Science from Coorg Institute of Technology, with a score of 72.5%.

Professional Experience🏛️

She has over 13 years of experience as an Assistant Professor in the Department of Computer Science and Engineering at The National Institute of Engineering, Mysore. Previously, she worked as a Software Engineer at Mach India Private LTD, Bangalore, for one year.

Research Interest🌐

Padmini M.S.’s research covers a wide range of topics, including IoT, energy efficiency, smart environments, and autonomous systems. Her work on “Energy Efficient Smart Street Lighting System” and “Critical Analysis of Life Span Improvement Techniques in Energy Constraints Edge IoT Devices” demonstrates her focus on practical applications and sustainability.

Awards and Honors🏆

Padmini M.S. has been recognized for her significant contributions to the field of Computer Science and Engineering through various awards and honors 🏅. She has received accolades for her innovative research on IoT, energy efficiency, and smart environments, showcased through her numerous publications in esteemed journals and presentations at international conferences 📚. Her work has not only advanced academic knowledge but also demonstrated practical applications, earning her respect and recognition in the academic community 🌟. Padmini’s dedication to teaching and research excellence is evident in her commitment to continuous learning and her role as a valued mentor and educator 👩‍🏫.

Achievements🏅
  • 🏅 Over 13 years of experience as an Assistant Professor in Computer Science and Engineering at The National Institute of Engineering, Mysore.
  • 📚 Published numerous papers in reputable journals and presented at international conferences.
  • 🎓 Currently pursuing a Ph.D. part-time at VTU, with a strong academic background including an M.Tech. in Computer Networks and a B.E. in Computer Science.
  • 🌐 Conducted significant research in IoT, energy efficiency, and smart environments.
  • 🖥️ Authored impactful papers such as “Energy Efficient Smart Street Lighting System” and “Critical Analysis of Life Span Improvement Techniques in Energy Constraints Edge IoT Devices”.
  • 👩‍🏫 Recognized for excellent communication skills, problem-solving ability, and adaptability to new technologies.
  • 🌟 Highly respected in the academic community for her innovative research and practical applications.
  • 📜 Demonstrated commitment to continuous learning and professional growth through her ongoing Ph.D. studies and research initiatives.
Publications top noted📜
  • Critical Analysis of Life Span Improvement Techniques in Energy Constraints Edge IoT Devices
    • Authors: Padmini, M.S., Kuzhalvaimozhi, S.
    • Year: 2023
    • Journal: SN Computer Science
    • Citations: 0
    • 📜📆0️⃣
  • Energy aware reliable routing model for sensor network enabled internet of things environment
    • Authors: Srikantha, P.M., Kuzhalvaimozhi, S., Silli, S.M., Verma, T., Manjunatha, V.
    • Year: 2023
    • Journal: Indonesian Journal of Electrical Engineering and Computer Science
    • Citations: 0
    • 🌐🔋0️⃣
  • Energy Efficient Smart Street Lighting System
    • Authors: Padmini, M.S., Rajkumar, R., Prahlada, Galagali, S.S., Reddy, K.N.
    • Year: 2022
    • Conference: International Conference on Artificial Intelligence and Data Engineering, AIDE 2022
    • Citations: 1
    • 💡🏙️1️⃣
  • An Implementation of Gesture-Controlled Autonomous Drone
    • Authors: Padmini, M.S., Kuzhalivaimozhi, S., Simha, P.V., Singh, P., Abhinandan, A.
    • Year: 2022
    • Conference: Proceedings – 2nd International Conference on Smart Technologies, Communication and Robotics 2022, STCR 2022
    • Citations: 0
    • 🚁🤖0️⃣

Bechoo Lal | Computer Science | Best Researcher Award

Published on by Global Scholar Awards

Dr. Bechoo Lal | Computer Science | Best Researcher Award

Associate Professor of KLEF- KL University Vijayawada Campus Andhra Pradesh, India

Dr. Bechoolal 🌟 is an esteemed Associate Professor in Computer Science/Data Science with a passion for inspiring students through a deep understanding of technology and research. With a solid academic foundation that includes a PGP in Data Science from Purdue University and multiple PhDs in Information Systems and Computer Science 🎓, he brings a wealth of expertise to his teaching and research. Dr. Bechoolal has extensive experience in various institutions, from KLEF KL Deemed University to Western College 🏫, and has made significant contributions through his numerous research publications and certifications 🏅. His interests span Machine Learning, Data Science, and programming languages, and he actively engages in projects that explore digital transformation and its societal impacts 💻🔍. Fluent in English and Hindi 🇬🇧🇮🇳, he continues to advance knowledge and inspire the next generation of tech professionals.

Publication profile

Education

Dr. Bechoolal 🎓 is a distinguished academic with a rich educational background in Computer Science and Data Science. He earned a PGP in Data Science from Purdue University 🌟, where he specialized in data regression models and predictive data modeling. Dr. Bechoolal holds multiple PhDs—one in Information Systems from the University of Mumbai and another in Computer Science from SJJT University 🧠. His foundational studies include a Master of Technology in Computer Science from AAI-Deemed University, a Master of Computer Applications from Banaras Hindu University, and an undergraduate degree in Statistics from MG. Kashi Vidyapeeth University 📚. His continuous quest for knowledge is also reflected in his various certifications, including Machine Learning from Stanford University and an IBM Data Science Professional Certificate 🏅.

Academic Qualification

  • 📜 PGP in Data Science (2020-2021) from Purdue University, USA – Specializing in data regression models, predictive data modeling, and accuracy analyzing using machine learning.
  • 📜 PhD in Information System (2015-2019) from the University of Mumbai, India – Research Area: Data Science.
  • 📜 PhD in Computer Science (2011-2015) from SJJT University, India – Research Area: Machine Learning.
  • 📜 Master of Technology (M. Tech) in Computer Science and Engineering (2004-2006) from AAI-Deemed University, Allahabad, India.
  • 📜 Master of Computer Application (MCA) (1995-1998) from Institute of Science, Banaras Hindu University (BHU), India.
  • 📜 Graduation (Statistics-Hons) (1990-1993) from the Department of Mathematics and Statistics, MG Kashi Vidyapeeth University, India.

Data Science Certifications and Training

  • 🎓 Machine Learning, Stanford University, USA (2020)
  • 🎓 IBM Data Science Professional Certificate (2020)
  • 🎓 Data Science and Big Data Analytics (2019), ICT Academy, Govt. of India
  • 🎓 Security Fundamentals, Microsoft Technology Associate (2017)
  • 🎓 Intelligent Multimedia Data Warehouse and Mining (2009), University of Mumbai
  • 🎓 Python Programming (2017), University of Mumbai, India

 

Teaching Interest 

  • 📘 Data Science/Machine Learning
  • 📘 Database 📘 C/C++/Python Programming Languages
  • 📘 Software Engineering

Research Interest

  • 🔍 Machine Learning
  • 🔍 Data Science

Computer Science/Data Science Skills

💻 Machine Learning, Data Visualization, Big Data Analytics

📊 Predictive Modelling: Supervised Learning (Linear and Logistic Regression, Decision Tree, Support Vector Machine (SVM), Naïve Bayes Classifiers), Unsupervised Learning (K-Means clustering, principal components analysis (PCA))

💻 Programming Languages: Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn), SPSS, R-Programming

💻 Operating Systems/Platforms: UNIX/LINUX, WINDOWS, MS-DOS

💻 C/C++, CORE JAVA Programming Languages

💻 DBMS/RDBMS: Oracle, SQL, MySQL, NoSQL

Publication top notes

  • Improving migration forecasting for transitory foreign tourists using an Ensemble DNN-LSTM model
    Authors: Nanjappa, Y., Kumar Nassa, V., Varshney, G., Pandey, S., V Turukmane, A.
    Journal: Entertainment Computing
    Year: 2024
    Citations: 0 📅
  • Using social networking evidence to examine the impact of environmental factors on social followings: An innovative Machine learning method
    Authors: Murthy, S.V.N., Ramesh, P.S., Padmaja, P., Reddy, G.J., Chinthamu, N.
    Journal: Entertainment Computing
    Year: 2024
    Citations: 0 📅
  • Real-Time Convolutional Neural Networks for Emotion and Gender Classification
    Authors: Singh, J., Singh, A., Singh, K.K., Samudre, N., Raperia, H.
    Conference: Procedia Computer Science
    Year: 2024
    Citations: 0 📅
  • Identification of Brain Diseases using Image Classification: A Deep Learning Approach
    Authors: Singh, J., Singh, A., Singh, K.K., Turukmane, A.V., Kumar, A.
    Conference: Procedia Computer Science
    Year: 2024
    Citations: 0 📅
  • Fake News Detection Using Transfer Learning
    Authors: Singh, J., Sahu, D.P., Gupta, T., Lal, B., Turukmane, A.V.
    Conference: Communications in Computer and Information Science
    Year: 2024
    Citations: 0 📅
  • Reliability Evaluation of a Wireless Sensor Network in Terms of Network Delay and Transmission Probability for IoT Applications
    Authors: Mishra, P., Dash, R.K., Panda, D.K., Lal, B., Sujata Gupta, N.
    Journal: Contemporary Mathematics (Singapore)
    Year: 2024
    Citations: 0 📅
  • TRANSFER LEARNING METHOD FOR HANDLING THE INTRUSION DETECTION SYSTEM WITH ZERO ATTACKS USING MACHINE LEARNING AND DEEP LEARNING
    Authors: Upender, T., Lal, B., Nagaraju, R.
    Conference: ACM International Conference Proceeding Series
    Year: 2023
    Citations: 0 📅
  • Monitoring and Sensing of Real-Time Data with Deep Learning Through Micro- and Macro-analysis in Hardware Support Packages
    Authors: Lal, B., Chinthamu, N., Harichandana, B., Sharmaa, A., Kumar, A.R.
    Journal: SN Computer Science
    Year: 2023
    Citations: 0 📅
  • An Efficient QRS Detection and Pre-processing by Wavelet Transform Technique for Classifying Cardiac Arrhythmia
    Authors: Lal, B., Gopagoni, D.R., Barik, B., Kumar, R.D., Lakshmi, T.R.V.
    Journal: International Journal of Intelligent Systems and Applications in Engineering
    Year: 2023
    Citations: 0 📅
  • IOT-BASED Cyber Security Identification Model Through Machine Learning Technique
    Authors: Lal, B., Ravichandran, S., Kavin, R., Bordoloi, D., Ganesh Kumar, R.
    Journal: Measurement: Sensors
    Year: 2023
    Citations: 3 📅📈

Sayyed Ahmed | Computer Science | Best Scholar Award

Published on by Global Scholar Awards

Mr. Sayyed Ahmed | Computer Science | Best Scholar Award

Assistant Professor of  Aligarh Muslim University, India

Dr. Sayyed Usman Ahmed is a dedicated academic and researcher in the field of computer engineering, specializing in artificial intelligence and legal reasoning. He has been recognized for his contributions with awards such as the Best Paper Award (2022-23) and the Visvesvaraya Part-Time PhD Fellowship (2018-19). His teaching and research continue to inspire and shape the next generation of engineers and technologists.

Publication profile

Education

Dr. Sayyed Usman Ahmed holds a Ph.D. in Computer Engineering from Aligarh Muslim University (AMU), India, where he conducted research on “Decision Intelligence in Augmentation of Legal Reasoning” under the supervision of Prof. Nesar Ahmad. His thesis was submitted on March 6, 2024. He earned his M.Tech in Computer Engineering from Rajasthan Technical University (2012-2014) with a thesis on evaluating the efficiency and effectiveness of code reading techniques, supervised by Dr. Rajendra Purohit. He completed his B.Tech in Computer Engineering from AMU (2003-2007), with a project on fingerprint detection systems under the guidance of Prof. M. Sarosh Umar and Prof. Syed Atiqur Rahman.

Experience

Dr. Ahmed has extensive experience in academia and industry. He is currently an Assistant Professor at AMU, teaching courses in software engineering, data structures, information security, and programming labs. He has also served as a Deputy Head of the Information Technology department at Jodhpur Institute of Engineering and Technology, where he contributed significantly to teaching, course development, and departmental administration. In the industry, he has worked as an Application Software Engineer at Computer Science Corporation, focusing on software maintenance, bug fixes, and enhancements. Additionally, he has served in various capacities at the Computer Centre of AMU, including roles as a Programmer and Technical Consultant.

Research focus

Dr. Ahmed’s research interests encompass artificial intelligence, machine learning, natural language processing, and decision intelligence. He has published extensively in journals and conferences, focusing on areas such as sentiment analysis, depression detection from social media posts, rumor-free social networks, and news article summarization. His recent research includes a framework for legal case brief generation using natural language processing and smart contract generation through NLP and blockchain.

Publication top notes

1. Ahmad, T., Ahamad, M., Ahmed, S. U., Ahmad, N. (2022) Short question-answers
assessment using lexical and semantic similarity based features, Journal of Discrete
Mathematical Sciences and Cryptography, 25:7, 2057-2067, DOI:
10.1080/09720529.2022.2133245 [ESCI & Scopus]

2. Ahmed, S. U., Ahmad, T., Ahmad, N. (2022). Sentiment Analysis Techniques for
Depression Detection from Micro-Blogging Social Media Post. NueroQuantology
DOI: 10.14704/NQ.2022.20.12.NQ77265 [Scopus]

3. Ahmad, T., Ahmed, S. U., Ali, S. O., & Khan, R. (2020). Beginning with exploring the
way for rumor free social networks. Journal of Statistics and Management Systems, 23(2),
231-238. https://doi.org/10.1080/09720510.2020.1724623 [Web of Science]

4. Ahmad, T., Ahmed, S. U., Ahmad, N., Aziz, A., Mukul, L. (2020). News Article
Summarization: Analysis and Experiments on Basic Extractive Algorithms. International
Journal of Grid and Distributed Computing, 13(2), 2366 – 2379. [Web of Science]

5. Ahmed, S. U. (2018). Monitoring Unscheduled Leaves using IVR. Global Journal of
Computer Science and Technology, 18(1), 7–9. [Peer-reviewed]

6. Ahmed, S. U., & Purohit, R. (2014). Evaluating Efficiency and Effectiveness of Code
Reading Technique with an Emphasis on Enhancing Software Quality. International
Journal of Computer Applications, 2, 32-36. [Peer-reviewed]

7. Ahmed, S. U., Azmi, M. A., Badgujar, C., (2014). How to design and test safety critical
software systems. International Journal of Advances in Computer Science and Technology,
3(1), 19-22. [Peer-reviewed]

8. Ahmed, S. U., Sahare, S. A., & Ahmed, A. (2013). Automatic test case generation using
collaboration UML diagrams. World Journal of Science and Technology. 2, [Peerreviewed]

9. Ahmed, S. U., & Azmi, M. A. (2013). A Novel Model Based Testing (MBT) approach for
Automatic Test Case Generation. International Journal of Advanced Research in
Computer Science, 4(11), 81-83. [Peer-reviewed]

Journal Publications (Under Review)
1. Ahmed, S. U., Ahmed, N., Ahmad, T. (2023) A Rhetorical Role Relatedness (RRR)
framework for Legal Case Brief Generation Natural Language Processing Journal
(Elsevier, Submitted)