Zhuldyz Tashenova | Computer Science | Innovative Research Award

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Innovative Research Award

Zhuldyz Tashenova
Gumilyov Eurasian National University, Kazakhstan

Zhuldyz Tashenova
Affiliation Gumilyov Eurasian National University
Country Kazakhstan
Scopus ID 55669178600
Documents 15
Citations 26
h-index 3
Subject Area Computer Science
Event International Award and Honors
ORCID 0000-0003-3051-1605

Zhuldyz Tashenova is a researcher in the field of computer science whose scholarly activities encompass cybersecurity, software security assessment, machine learning, computer vision, augmented reality applications, and information protection systems. Her academic output demonstrates an interdisciplinary approach that integrates emerging digital technologies with practical solutions for organizational security and data management. The Innovative Research Award recognizes contributions that support technological advancement and knowledge development through peer-reviewed research and innovation.[1]

Abstract

This article presents an overview of the academic achievements and research contributions of Zhuldyz Tashenova. Her work addresses contemporary challenges in cybersecurity, vulnerability assessment, machine learning, computer vision, and digital transformation. Through peer-reviewed publications, she has contributed to the development of methodologies that enhance security infrastructures, improve predictive analytics, and support innovative educational and technological applications.[2]

Keywords

Cybersecurity, Computer Science, Machine Learning, Computer Vision, Augmented Reality, Vulnerability Detection, Information Security, Data Protection.

Introduction

The growing complexity of digital ecosystems has intensified the need for advanced security mechanisms and intelligent computational solutions. Researchers in computer science increasingly focus on integrating machine learning, software analysis, and secure networking technologies to address evolving threats. Within this context, Zhuldyz Tashenova has contributed to studies that explore both theoretical frameworks and practical implementations across multiple domains of information technology.[3]

Research Profile

According to available scholarly records, Tashenova has authored fifteen indexed publications with twenty-six citations and an h-index of three. Her research profile reflects active engagement in cybersecurity, software vulnerability analysis, agricultural data analytics, and immersive technologies. These areas illustrate a commitment to interdisciplinary research and applied innovation.[1]

Research Contributions

  • Development of a multi-tier security model integrating human factors, identification mechanisms, and secure networking architectures.
  • Creation of SentinelCMS, a framework for proactive vulnerability detection using static taint analysis and bidirectional LSTM methods.
  • Application of machine learning techniques for early crop type classification using seasonal spectral features.
  • Research on augmented reality games supported by computer vision technologies to improve sports motivation.
  • Studies focused on enterprise personal data protection and information security management.

Publications

Representative publications include Design of a Multi-Tier Security Model Encompassing Human Factors, Identification Processes, and Secure Networking (2026), SentinelCMS: Proactive Vulnerability Detection in CMS Plugins Using Static Taint Analysis and Bidirectional LSTM (2026), Early Crop Type Classification Based on Seasonal Spectral Features and Machine Learning Methods (2026), and Development of Computer Vision-enabled Augmented Reality Games to Increase Motivation for Sports (2023). These publications demonstrate research diversity and practical relevance across multiple technological domains.[4]

Research Impact

The impact of Tashenova’s work can be observed through contributions to cybersecurity methodologies, machine learning applications, and digital innovation initiatives. Her studies provide practical frameworks that may support organizations in strengthening security infrastructures while also expanding opportunities for intelligent data-driven decision-making. The integration of emerging technologies across diverse application areas highlights the broader relevance of her scholarly efforts.[5]

Award Suitability

Zhuldyz Tashenova’s research portfolio aligns with the objectives of the Innovative Research Award by demonstrating sustained scholarly productivity, interdisciplinary collaboration, and engagement with contemporary technological challenges. Her contributions to cybersecurity, machine learning, and digital innovation illustrate a commitment to advancing scientific knowledge while addressing practical needs within modern information systems.[6]

Conclusion

The academic record of Zhuldyz Tashenova reflects meaningful contributions to computer science research, particularly in areas related to cybersecurity, machine learning, and digital technologies. Through peer-reviewed publications and applied research initiatives, she has contributed to the advancement of knowledge in fields that remain highly relevant to contemporary scientific and technological development.

References

  1. Elsevier. (n.d.). Scopus author details: Zhuldyz Tashenova, Author ID 55669178600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55669178600
  2. Tashenova, Z. (2026). Design of a Multi-Tier Security Model Encompassing Human Factors, Identification Processes, and Secure Networking.
    DOI: https://doi.org/10.3390/info17060537
  3. Tashenova, Z. (2026). SentinelCMS: Proactive Vulnerability Detection in CMS Plugins Using Static Taint Analysis and Bidirectional LSTM.
    https://doi.org/10.3390/app16115471
  4. Tashenova, Z. (2026). Early Crop Type Classification Based on Seasonal Spectral Features and Machine Learning Methods.
    https://doi.org/10.3390/technologies14040221
  5. Tashenova, Z. (2023). Development of Computer Vision-enabled Augmented Reality Games to Increase Motivation for Sports.
    https://doi.org/10.14569/IJACSA.2023.0140428
  6. Journal of Theoretical and Applied Information Technology. (2022). Research and Development of Personal Data Protection Systems in Enterprises.

Aaron Mangrobang | Information Technology | Best Researcher Award

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Mr. Aaron Mangrobang | Information Technology | Best Researcher Award

Aaron Mangrobang at Pangasinan State University, Philippines.

Mr. Aaron N. Mangrobang is an adaptable ICT educator and practitioner with dual degrees in Information Technology and Hotel & Restaurant Management, and a master’s degree in Information Technology from Saint Louis University. His career blends academic instruction with practical DevOps, software development, and automation skills. Known for his strong communication, critical thinking, and collaborative approach, Aaron effectively bridges academic theory with real-world technology applications. He is passionate about nurturing the next generation of IT professionals while continuously enhancing ICT operations and systems security across institutions.

Professional Profile

Orcid

🎓 Education 

  • Master in Information Technology, Saint Louis University, 2021–2023

  • Bachelor of Science in Information Technology, ABE International Business College of Accountancy, 2017–2019

  • Bachelor of Science in Hotel & Restaurant Management, ABE International Business College of Accountancy, 2008–2012

💼 Experience 

Mr. Aaron N. Mangrobang is an experienced and detail-oriented ICT professional with a strong academic foundation and versatile industry exposure. Currently serving as a BSIT College Instructor and ICT Management Coordinator at Pangasinan State University (2024), he oversees campus ICT infrastructure, facilitates system security, and ensures efficient digital operations across academic and administrative units. He also contributes to curriculum development and student mentorship.

Previously, he worked as a BSIT Instructor at the University of Eastern Pangasinan (2023–2024), where he taught networking, cybersecurity, web development, and programming courses, while also updating course materials to align with modern technologies.

Earlier in his career, Aaron gained practical industry experience as a Full Stack Associate Software Engineer at BlastAsia Inc. (2020), focusing on end-to-end software development, and as an Intern Web Developer at MediSource Inc. (2018–2019), where he resolved client issues and enhanced web functionality based on customer needs.

🔬 Research Interests

  • Web and Mobile Application Development (Android, PHP, JavaScript)

  • DevOps and CI/CD Pipelines (GitHub, GitLab)

  • Network Security and System Automation

  • Backend Development (Firebase, MySQL, Google Cloud)

  • RESTful API Integration

  • Cybersecurity and Shared Hosting Management

  • Educational Technologies in ICT

Conclusion:

Mr. Aaron N. Mangrobang is a highly suitable candidate for the Best Researcher Award in Information Technology, particularly in a practice-driven or applied research category. His blend of academic instruction, real-world ICT implementation, and forward-looking technical interests demonstrate a commitment to impactful technological advancement.

While he would benefit from increased scholarly output and research partnerships, his current portfolio presents a compelling case for recognition as a rising contributor to the evolving ICT research and education landscape in the Philippines.

Kianeh Kandi | Machine Learning | Academic Excellence Award

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Mrs Kianeh Kandi |  Machine Learning |  Academic Excellence Award

Academic Researcher at politechnic of dimadrid,  Spain

Mrs. Kianeh Kandi is an accomplished software developer and researcher with a robust foundation in computer science and a passion for innovative solutions. Currently pursuing her PhD in Software Systems and Computing at the Polytechnic University of Madrid, she has demonstrated expertise in machine learning, data mining, statistical methods, and high-impact research.

Profile:

📚 Education:

  • PhD Candidate in Software Systems and Computing, Polytechnic University of Madrid (2022 – Present)
  • Bachelor and Master of Industrial Management, Azad University of Arak (2004 – 2011)
  • Bachelor of IT (Networking), Arak University (2017 – 2019)

🎯 Research & Professional Experience:

  • Researcher, Polytechnic University of Madrid (2022 – Present):
    Conducting innovative research on credit card risk assessment using machine learning and developing neural network models to predict and mitigate financial risks.
  • Specialist, Dana Insurance Company (2018 – 2022):
    Managed market risk assessments and drove sales operations to enhance revenue growth.
  • Digital Marketing Expert, Aryanik Software Company (2016 – 2017):
    Improved user experience through website design and executed digital marketing strategies.
  • Project Planner, Sala Dairy Company (2010 – 2011):
    Boosted production efficiency and optimized processes using mathematical methods.

🧠 Research Contributions:

  • Thesis: Optimal Scheduling in a Milk Production Line Based on Mixed Integer Linear Programming
  • Publications:
    • Enhancing Performance of Credit Card Models Using LSTM Networks and XGBoost Algorithms
    • Evaluating Deep Convolutional Neural Networks and Support Vector Regression for Creditworthiness Prediction

💡 Key Skills:

  • Programming Languages: Python, Java, C++
  • Machine Learning Tools: TensorFlow, PyTorch
  • Technologies: Docker, large-scale data processing, Power BI, IBM SPSS
  • Research Expertise: Neural networks, statistical data analysis, synthetic data generation

Publication Top Notes:

  • “Optimal Scheduling in a Milk Production Line Based on Mixed Integer Linear Programming”

  • “Enhancing Performance of Credit Card Models by Utilizing LSTM Networks and XGBoost Algorithms”

  • “Evaluating the Performance of Deep Convolutional Neural Networks and Support Vector Regression for Creditworthiness Prediction in the Financial Sector”