Basim abed | Cybersecurity | Best Researcher Award

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Mr. Basim abed | Cybersecurity | Best Researcher Award

Mr. Basim abed, Tabriz University, Iran

Mr. Basim Najim Al-Din Abed is an experienced academic professional in Computer Science with a specialization in Data Security and Cybersecurity. Currently pursuing a Ph.D. in Cybersecurity at Tabriz University, Iran (expected 2025), he holds an M.Sc. in Computer Science from Yarmouk University, Jordan, and dual bachelor’s degrees in Mathematics and Computer Science. With over 10 years of teaching and research experience, Mr. Abed has authored 19 peer-reviewed publications in international journals and conferences, focusing on encryption techniques, cybersecurity models, and deepfake detection. His research interests include cyber threats, cryptography, network security, blockchain, and privacy protection. He is proficient in Python, Java, C++, and tools such as Wireshark, Kali Linux, and Metasploit, with expertise in RSA, AES, and SHA-256 algorithms. Mr. Abed’s work demonstrates a strong commitment to advancing cybersecurity research through innovative mathematical and technical solutions to emerging digital threats.

Publication Profile

Orcid

🎓 Educational Background

Mr. Basim Najim Al-Din Abed possesses a strong and diverse academic foundation in the fields of computer science and mathematics. He is currently pursuing a Ph.D. in Cybersecurity at Tabriz University in Iran, with an expected graduation year of 2025. This advanced academic endeavor builds upon his Master of Science in Computer Science, with a specialization in Data Security, which he earned from Yarmouk University in Irbid, Jordan, in 2015. His multidisciplinary expertise is further supported by two bachelor’s degrees: one in Mathematics Science, completed in 2008, and another in Computer Science, earned in 1996. This comprehensive educational progression showcases Mr. Abed’s deep commitment to advancing his knowledge in both theoretical and applied sciences. His academic journey, spanning over two decades, has provided a solid foundation for his research in cybersecurity, encryption, and data protection, enabling him to contribute meaningfully to both academic and practical domains in the digital security landscape.

🔍 Research Interests

Mr. Basim Najim Al-Din Abed has developed a focused and forward-looking research portfolio in the dynamic field of cybersecurity. His primary research interests include cybersecurity and the analysis of emerging cyber threats, where he explores strategies to safeguard digital infrastructure. He is particularly invested in data privacy and encryption techniques, aiming to enhance the confidentiality and integrity of sensitive information. Mr. Abed also delves into network security and intrusion detection systems, working on advanced methods to detect and prevent unauthorized access. His work in cryptography and secure communication contributes to building robust protocols against digital attacks. Additionally, he investigates the integration of blockchain technology to strengthen cybersecurity frameworks and supports innovations in decentralized systems. Recently, he has expanded his focus to the detection and prevention of deepfakes, addressing one of the most pressing challenges in modern digital forensics and media security.

Publication Top Notes

  • Encrypting Text Messages via Iris Recognition and Gaze Tracking Technology, 2025, Mesopotamian Journal of CyberSecurity, DOI: [10.58496/MJCS/2025/007],

  • Lossless Encoding Method Based on a Mathematical Model and Mapping Pixel Technique for Healthcare Applications, 2024, Iraqi Journal of Science, DOI: [10.24996/ijs.2024.65.12.32], Cited by: Scopus – 1 citation

  • A Deep Fake Detection System Using Diffusion Model Based on Graph Based Image Segmentation, 2023, Frontiers in Artificial Intelligence and Applications, DOI: [10.3233/FAIA230776], Cited by: Scopus – 3 citations

  • A New Mathematical Model to Improve Encryption Process Using Taylor Expansion, 2020, IEEE IT-ELA Conference, DOI: [10.1109/IT-ELA50150.2020.9253084], Cited by: Scopus – 5 citations

  • A Novel Approach by Using a New Algorithm: Wolf Algorithm as a New Technique in Cryptography, 2020, Webology, DOI: [10.14704/WEB/V17I2/WEB17069], Cited by: Scopus – 2 citations

  • Using Cardano’s Method for Solving Cubic Equation in the Cryptosystem to Protect Data Security Against Cyber Attack, 2020, AiCIS Conference, DOI: [10.1109/AiCIS51645.2020.00030], Cited by: Scopus – 4 citations

  • McLaurin Series as a New Technique to Improve Encryption Process, 2019, Journal of Physics: Conference Series, DOI: [10.1088/1742-6596/1294/4/042008], Cited by: Scopus – 6 citations

  • Mapping Private Keys into One Public Key Using Binary Matrices and Masonic Cipher: Caesar Cipher as a Case Study, 2016, Security and Communication Networks, DOI: [10.1002/sec.1431], Cited by: Scopus – 12 citations

Conclusion

Mr. Basim Najim Al-Din Abed is a strong and deserving candidate for the Research for Best Researcher Award, particularly in the domain of Cybersecurity and Data Protection. His innovative research, technical expertise, and consistent academic contribution make him well-suited for recognition at this level. With further emphasis on international visibility, research leadership, and recognition, Mr. Abed’s profile can evolve from commendable to exceptional.

Lisandra Díaz de la Paz | Data Science | Best Researcher Award

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Assoc. Prof. Dr. Lisandra Díaz de la Paz | Data Science | Best Researcher Award

Assoc. Prof. Dr. Lisandra Díaz de la Paz, Central University “Marta Abreu” of Las Villas, Cuba

Assoc. Prof. Dr. Lisandra Díaz de la Paz is a Cuban computer scientist and academic with a Ph.D. in Technical Sciences (2023), a Master’s (2011), and a Bachelor’s (2008) in Computer Science from the Central University “Marta Abreu” of Las Villas (UCLV). She serves as an Associate Professor and researcher specializing in databases, decision-support systems, data integration, metadata management, and artificial intelligence. With over 15 years of teaching experience, she has instructed various undergraduate and postgraduate courses in computer science and related fields. Dr. Díaz de la Paz has completed extensive postgraduate training in areas such as software engineering, machine learning, and data science. She currently leads the Information Systems discipline and serves as Vice Dean of Research and Postgraduate Studies at the MFC Faculty, UCLV. Her research focuses on data quality models, big data, Python programming, semantic web, LLMs, and generative AI. She is an active contributor to Cuba’s technological advancement.

Publication Profile

Orcid

Google Scholar

Academic Background

Assoc. Prof. Dr. Lisandra Díaz de la Paz is a distinguished academic in the field of Computer Science with a robust educational foundation acquired from the Central University “Marta Abreu” of Las Villas (UCLV), Cuba. She earned her Bachelor’s degree in Computer Science in July 2008, followed by a Master’s degree in the same field in December 2011. Demonstrating a continuous commitment to academic excellence and research, she completed her Doctorate in Technical Sciences in November 2023. This progression reflects her deepening expertise and scholarly dedication within computing and technical disciplines. Her academic journey at UCLV has equipped her with strong theoretical and practical knowledge, forming the basis for her professional contributions as a university professor, researcher, and academic leader. Dr. Díaz de la Paz’s qualifications underpin her role in advancing research in artificial intelligence, databases, and data systems while mentoring the next generation of computing professionals in Cuba and beyond.

Professional Role and Academic Specialization

Assoc. Prof. Dr. Lisandra Díaz de la Paz is a dedicated professor and researcher with a strong focus on the field of Computer Science. Currently holding the academic rank of Associate Professor, she plays a vital role in higher education by teaching, mentoring, and guiding students across multiple levels of university instruction. Her primary specialization lies in computing, where she has developed expertise in areas such as databases, data quality, artificial intelligence, decision-support systems, and big data technologies. As both an educator and researcher, she combines theoretical knowledge with practical applications, contributing to academic excellence and technological advancement. Her position as a faculty member enables her to engage in curriculum development, academic leadership, and innovative research initiatives. Dr. Díaz de la Paz’s dual role as a professor and researcher allows her to bridge the gap between knowledge creation and dissemination, making her an influential figure in the Cuban academic and scientific community.

Awards and Recognitions

Assoc. Prof. Dr. Lisandra Díaz de la Paz has received multiple prestigious awards in recognition of her contributions to computing and educational technologies. She was a co-author of the project “Algorithms and Tools for the Library Management System,” which earned the 2024 Provincial CITMA Award in Villa Clara. In 2021, she received the Provincial CITMA Award for her work on improving the accuracy and completeness of bibliographic records in MARC 21 format. In 2019, she received the Annual Award from the Minister of Higher Education for her research in database systems and computing. Her 2018 work on the ABCD Library Management System implementation across Cuban higher education institutions was recognized for its scientific and educational impact. She also received CITMA awards in 2016 and 2012 for her innovative contributions to active database rule maintenance and business rule implementation in relational databases, respectively—highlighting her sustained excellence in research and technical innovation.

Research Focus

Assoc. Prof. Dr. Lisandra Díaz de la Paz focuses her research primarily on data quality, metadata management, bibliographic systems, and decision support through data-driven computing. Her work encompasses key areas such as the completeness and accuracy of bibliographic records in MARC 21 format, ETL process optimization, metadata profiling, and author name disambiguation using ontologies and deep learning. She has also explored big data integration with NoSQL systems, MapReduce techniques for anomaly detection, and frameworks for metadata quality evaluation in the context of open science. Her contributions have practical applications in library science, digital repositories, and institutional decision-making, particularly within educational and academic information systems. Additionally, her interdisciplinary approach blends artificial intelligence, machine learning, semantic web technologies, and business intelligence, supporting national and international collaboration for improving data infrastructure. These efforts position her as a leading researcher in data-centric computing, database technologies, and intelligent information systems.

Publication Top Notes

  • 📘 Algorithm to correct instance-level anomalies in large data using MapReduce – Cited by 7 – 2016

  • 📗 Data quality analysis in ABCD suite sources – Cited by 7 – 2015

  • 📕 Techniques to capture changes and maintain updated data warehouse – Cited by 5 – 2015

  • 📙 Data market for decision-making on teaching/research staff at UCLV – Cited by 5 – 2013

  • 📒 Techniques to capture data changes (extended version) – Cited by 4 – 2015

  • 📓 Automation of data loading processes in HR data market at UCLV – Cited by 4 – 2014

  • 📘 Weights estimation in completeness measurement of bibliographic metadata – Cited by 3 – 2021

  • 🧠 Author name disambiguation using ontology & deep learning – Cited by 1 – 2022

  • 📊 CompMARC tool for measuring completeness in MARC 21 – Cited by 1 – 2016

  • 📚 Model for metadata quality evaluation: Proposal for open science – Published – 2024

  • 📝 Accuracy measurement of author names in MARC 21 records – Published – 2018

  • 📈 Optimal weight estimation for completeness in MARC 21 metadata – Published – 2017

  • 🔍 Metadata profiling tool in MARC 21 PMMarc v2.0 – Published – 2017

  • 💾 Method for selecting data model and NoSQL system in big data – Published – 2017

  • 🛠 Procedure to improve completeness in MARC 21 records – Published – 2017

Jamshed AliShaikh | Cybersecurity | Best Researcher Award

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Dr. Jamshed AliShaikh | Cybersecurity | Best Researcher Award

Dr. Jamshed AliShaikh at Chongqing University, China

Jamshed Ali  is a Ph.D. candidate in Computer Science & Technology at Chongqing University, China 🇨🇳, with over 7 years of research experience and 4+ years of industry and academic roles. His work bridges AI 🤖, cybersecurity 🔐, and healthcare technologies 🏥. He has contributed to high-impact projects funded by Chinese research councils and has published multiple Q1-ranked journal articles 📚. Jamshed is known for his collaborative spirit, technical versatility, and commitment to using AI for societal benefit 🌍. He is fluent in programming and simulation tools and is a recognized young researcher from Pakistan 🇵🇰.

Publication Profile

Google Scholar

Academic Background

Jamshed Ali earned his Ph.D. in Computer Science & Technology (2020–2025) from Chongqing University, focusing on intelligent intrusion detection for IoMT healthcare networks 🛡️🏥. He completed his MS in Electrical Engineering (2018–2020) at the same university, working on AI-based optimization in smart grids ⚡ using fuzzy logic and control systems. He holds a BS in Electronics (2010–2014) from the University of Sindh, Pakistan, where he explored smart robotics 🤖 for disaster response. His academic path reflects a strong foundation in electronics, AI, and system-level problem-solving 💡 across interdisciplinary domains.

Professional Background

Jamshed Ali has over 4 years and 5 months of professional experience 🧠💻, including work as a Lecturer and IT In-Charge 👨‍🏫 at HIMAS-CON (3+ years), where he taught computer science and led IT operations. He worked as a PHP Developer 💻 at Geeks of Kolachi, managing web development projects. During his internship at Chongqing Kaixinderui, he gained practical experience in engineering teamwork and cultural integration 🤝🇨🇳. Alongside his academic research, these roles reflect a hands-on approach to both technical development and educational leadership in IT and cybersecurity domains 🔐🧑‍🏫.

Awards and Honors

Jamshed Ali received a fully funded 🎓 Chinese Government Scholarship for both his MS and Ph.D. studies in 2018 and 2020 🇨🇳. He was named the “Outstanding Student of the Year” 🥇 in 2020 at Chongqing University for academic excellence and leadership. He also won “Best Speaker” 🎤 at the China-Pakistan Culture and Technology Conference, where he presented on AI’s transformative role across healthcare, education, and manufacturing 🚀. These accolades reflect his academic impact, communication skills, and international recognition 🌍 in the field of intelligent systems and research innovation 🧪.

Research Focus

Jamshed’s research centers on cybersecurity in IoMT and Industrial IoT 🌐, with a focus on machine learning and deep learning 🔍 for intrusion detection, especially detecting zero-day attacks 🚨. He explores federated learning, edge/cloud computing ☁️, secure communication protocols, and medical image processing 🖼️ to enhance healthcare data security 🛡️. His work contributes to intelligent, privacy-preserving healthcare systems, backed by publications in high-impact journals 📘. Jamshed combines theory and application, building intelligent systems that respond to real-world threats while pushing the boundaries of AI in digital health and critical infrastructure 💡🧠.

Publication Top Notes

🔋 Voltage Stability Index using new single-port equivalent based on component peculiarity and sensitivity persistence
Year: 2021 | 📖 Cited by: 11

🌡️ Temperature field simulation and ampacity optimization of 500kV HVDC submarine transmission cable
Year: 2021 | 📖 Cited by: 10

🛰️ A UAV-Assisted Stackelberg Game Model for Securing IoMT Healthcare Networks
Year: 2023 | 📖 Cited by: 9

🌞 A Reliable Approach to Protect and Control of Wind Solar Hybrid DC Microgrids
 Year: 2019 | 📖 Cited by: 9

Conclusion

Based on his outstanding academic record, impactful research in cybersecurity and IoMT, high-quality publications in Q1 journals, and significant involvement in both funded research projects and technical roles, Jamshed Ali stands out as a highly deserving candidate for the Best Researcher Award. His work on intelligent intrusion detection systems using AI and deep learning contributes to a critical and emerging field, particularly in healthcare network security. Coupled with his strong technical proficiency, 7 years of research experience, multiple honors—including CSC scholarships and recognition as an outstanding student and speaker—Jamshed Ali exemplifies excellence in early-career research and innovation.

Wanxiu Xu | Data law | Best Researcher Award

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Ms. Wanxiu Xu | Data law | Best Researcher Award

Ms. Wanxiu Xu, University of science and technology of china, China

Wanxiu Xu is a dedicated Ph.D. candidate in Business Administration at the University of Science and Technology of China, focusing on data security governance and cross-border data flow. She holds a Master’s in Law and has served as a visiting scholar at Nanyang Technological University, Singapore. Wanxiu has contributed to multiple publications on data protection and cybersecurity, and she has played a pivotal role in developing national standards for data security in China. Additionally, she has been involved in key research projects and legislative efforts, demonstrating her commitment to enhancing data governance. 📚🔒🌏📊

 

Publication profile

Scopus

Educational Background

Ms. Wanxiu Xu is currently pursuing her Ph.D. in Business Administration at the University of Science and Technology of China, following her master’s degree in Law. Her academic journey has equipped her with a unique interdisciplinary perspective, particularly in data security governance and cross-border data flow. This foundation positions her well for conducting impactful research in an increasingly globalized digital landscape.

Research Contributions

Ms. Xu has made significant contributions to the field through her research and publications. With several articles accepted in high-impact journals, including a JCR Q1 publication, her work addresses critical issues surrounding global data governance, particularly the regulatory frameworks influencing China-U.S. data flows. Her focus on practical implications, such as suggestions for strengthening certification systems and legal analyses of data protection measures, demonstrates her commitment to bridging theory and practice.

Conclusion

Ms. Wanxiu Xu exemplifies the qualities sought in a recipient of the Best Researcher Award. Her academic excellence, coupled with her extensive research contributions and involvement in national initiatives, positions her as a leading figure in her field. Her work not only advances academic knowledge but also informs critical policy developments, making her a deserving candidate for this prestigious recognition.

Publication Top Notes

  • Exploring Abnormal Brain Functional Connectivity in Healthy Adults, Depressive Disorder, and Generalized Anxiety Disorder through EEG Signals: A Machine Learning Approach for Triple Classification (2024) 📊 – 0 citations
  • Rapid detection of liver metastasis risk in colorectal cancer patients through blood test indicators (2024) 🩺 – 0 citations
  • Impact of different drying methods on physicochemical characteristics and nutritional compositions of bee larvae (2024) 🍯 – 7 citations
  • Neuroimaging Study of Brain Functional Differences in Generalized Anxiety Disorder and Depressive Disorder (2023) 🧠 – 3 citations
  • Online Machine Vision-Based Modeling during Cantaloupe Microwave Drying Utilizing Extreme Learning Machine and Artificial Neural Network (2023) 🍉 – 2 citations
  • Altered Functional Brain Network Structure between Patients with High and Low Generalized Anxiety Disorder (2023) 🔍 – 7 citations
  • Self-Regulation Phenomenon Emerged During Prolonged Fatigue Driving: An EEG Connectivity Study (2023) 🚗 – 4 citations
  • Driving Fatigue Detection with Three Prefrontal EEG Channels and Deep Learning Model (2023) ⏳ – 1 citation
  • An improvement of far-infrared drying for ginger slices with computer vision and fuzzy logic control (2022) 🍃 – 2 citations
  • Effect of far infrared and far infrared combined with hot air drying on the drying kinetics, bioactives, aromas, physicochemical qualities of Anoectochilus roxburghii (Wall.) Lindl. (2022) 🌱 – 13 citations