Parisasadat Shojaei | Cybersecurity and Privacy | Distinguished Scientist Award

Ms Parisasadat Shojaei | Cybersecurity and Privacy | Distinguished Scientist Award

PhD Candidate, University of Wollongong, Australia.ย 

Parisasadat Shojaei is a PhD candidate in Computer Science at the University of Wollongong, Australia. Her interdisciplinary expertise bridges computer engineering, privacy-enhancing technologies, and AI-driven health informatics. With over a decade of teaching and industry experience in Iran and Australia, Parisa has mentored students, led IT projects, and contributed to cross-functional research in data privacy and cybersecurity. Her PhD research explores user-centric privacy frameworks in mobile health (mHealth) applications. She has worked on high-impact projects, including data analysis in DEI initiatives and cloud security practices. With a solid background in both academia and industry, Parisa combines practical software development skills with academic rigor. She has published several peer-reviewed papers, presented at international conferences, and earned multiple awards for academic excellence and research contributions. Passionate about ethical AI and inclusive technologies, she continues to bridge the gap between secure system design and user trust.

Profile

google scholar

๐Ÿ“˜ Educationย 

Parisa holds a Bachelor and Master of Science in Computer Engineering โ€“ Software from Islamic Azad University, Iran, where she earned accolades such as the Best Graduate Student Award. She is currently pursuing a PhD in Computer Science (Information Science) at the University of Wollongong, Australia. Her thesis, “Developing Effective Privacy-Enhancing Guidelines for Designing mHealth Applications,” is supervised by Dr. Elena Vlahu-Gjorgievska and A/Prof. Casey Chow. Her education blends deep technical skills in software engineering with specialized training in data privacy, health informatics, and cybersecurity. In addition to her formal education, Parisa has earned numerous certifications from institutions like HarvardX, CIW, and TsinghuaX, covering topics such as Python for Research, AI, Data Science, and Web Development. Her continued education through workshops and online learning platforms reflects a dedication to lifelong learning and staying current with emerging technologies.

๐Ÿง‘โ€๐Ÿ’ป Experienceย 

Parisa brings a robust mix of academic, industrial, and research experience. She is currently a PhD candidate and demonstrator at the University of Wollongong, teaching subjects like Web Development, Cryptography, AI, and Cybersecurity. Professionally, she has served as a web developer and data analyst in Australia, working with Cultural Infusion and Metallum Fabrication Pty Ltd, where she applied her skills in GDPR compliance, AWS security, and data visualization. Previously in Iran, she held roles as a software developer, web designer, and lecturer across several universities and tech institutes. She led research in AI, machine learning, and cybersecurity, contributing to numerous publications and national conferences. Her leadership includes mentoring PhD students, managing research projects, and coordinating industrial collaborations. Parisa excels in interdisciplinary teamwork, cloud computing, and privacy-enhancing technologies, seamlessly integrating theoretical research with practical implementations.

๐Ÿ”ฌ Research Focusย 

Parisaโ€™s research is deeply rooted in the intersection of privacy, cybersecurity, and digital health technologies. Her PhD research is centered on creating privacy-enhancing guidelines for the design of mHealth (mobile health) applications, integrating user-centric design principles with secure architecture. She investigates how privacy perceptions influence user behavior and trust in digital health systems. Her previous research includes evolutionary algorithms, task scheduling in cloud computing, fuzzy systems for intrusion detection, and AI-driven optimization models. Recently, her work has expanded to data ethics, cloud-based privacy-preserving technologies, and GDPR-compliant frameworks in DEI data management. Her approach combines quantitative methods, machine learning models, and empirical user studies. Parisa is particularly interested in bridging the gap between theoretical privacy models and real-world application usability, contributing toward more ethical and secure tech ecosystems. Her contributions aim to support inclusive, transparent, and user-trusted digital infrastructures in healthcare and education sectors.

๐Ÿ“š Publication Top Notes

  1. ๐Ÿง ๐Ÿ“ฑ Enhancing Privacy in mHealth Applications: A User-Centric Model Identifying Key Factors Influencing Privacy-Related Behaviours

  2. ๐Ÿ”’๐Ÿ“Š Security and Privacy of Technologies in Health Information Systems: A Systematic Literature Review

  3. ๐ŸŒŒ๐Ÿ‘ฉโ€๐Ÿผ Developing and Testing a Mobile Application for Breastfeeding Support: The Milky Way Application

  4. ๐Ÿงฎโ˜๏ธ An Approach to Optimized Imperialist Competitive Algorithm for Task Scheduling in Cloud Computing

  5. ๐Ÿโฑ๏ธ A Hybrid Particle Swarm Optimization for Task Scheduling in Cloud Computing

  6. ๐Ÿงฌ๐Ÿ“ฆ An Approach to Optimized Genetic Algorithm for Task Scheduling in Cloud Computing

  7. ๐ŸŽฏ๐Ÿšฆ Threshold Acceptance Approach for Task Scheduling in Cloud Computing

  8. ๐Ÿœ๐Ÿ” A Hybrid Algorithm for Task Scheduling Based on Ant Colony Optimization and Local Neighborhood Search

  9. ๐Ÿ›ก๏ธ๐Ÿง  Intelligent Intrusion Detection Using Fuzzy Imperialist Competitive Algorithm

  10. ๐Ÿงฟ๐Ÿ“˜ A Hybrid Algorithm for Task Scheduling Based on Binary Particle Swarm Optimization and Local Neighborhood Search

 

 

Umar Islam | Computer Science | Best Researcher Award

Mr. Umar Islam | Computer Science | Best Researcher Award

Senior Lecturer, IQRA National University Swat Campus, Pakistan

Mr. Umar Islam is a passionate and accomplished educator and researcher in the field of Computer Science, currently serving as a Lecturer at Iqra National University (INU) Swat Campus, Pakistan. With an impressive academic background spanning 18 years in Computer Science, Mr. Islam has become a recognized expert in AI, machine learning, blockchain security, IoT, bioinformatics, and financial analytics. His work has been published in over 15 research articles, including several in top-tier journals. A dedicated researcher, he focuses on real-time AI solutions, particularly in healthcare and cybersecurity. Mr. Islam is also a committed mentor, providing supervision and guidance to students in advanced topics such as Python programming, machine learning, and AI applications. His contributions to the academic community and his research endeavors demonstrate his commitment to pushing the boundaries of knowledge and solving real-world problems.

Profile

Education

Mr. Umar Islam has an extensive academic journey, earning 18 years of education in Computer Science. His academic path began with a Bachelor’s degree in Computer Science, followed by a Masterโ€™s degree, where he built the foundation of his knowledge in various aspects of computing. Mr. Islamโ€™s thirst for knowledge and his passion for research led him to pursue advanced studies in areas like AI, machine learning, IoT, and cybersecurity, with a strong focus on applying these technologies to solve real-world challenges. His educational journey has equipped him with the skills to lead cutting-edge research projects and to innovate in fields like bioinformatics and financial analytics. Currently, he is working toward a PhD, which will further deepen his understanding and expertise in these areas. Through his education, Mr. Islam has gained a comprehensive understanding of theoretical and applied Computer Science, which he integrates into both his teaching and research.

Experience

With six years of teaching experience at the higher education level, Mr. Umar Islam has played a pivotal role in shaping the future of numerous students at Iqra National University (INU) Swat Campus. As a lecturer, he has delivered comprehensive lessons in Computer Science topics such as AI, machine learning, and cybersecurity. His commitment to academic excellence is reflected in his success as a supervisor, guiding students through complex topics like Python programming, e-learning analytics, and AI-driven applications. In addition to teaching, Mr. Islam has gained four years of extensive research experience, with a focus on AI applications in healthcare, cybersecurity, and blockchain security. He has led multiple research projects, producing groundbreaking results, and has contributed significantly to the academic community with over 15 published research articles. His academic experience extends beyond teaching, positioning him as a thought leader in his field.

Research Focus

Mr. Umar Islam’s research is deeply focused on the intersection of artificial intelligence (AI), cybersecurity, healthcare, and financial analytics. One of his key research areas includes AI-driven solutions in healthcare, particularly the development of federated learning-based intrusion detection systems and epileptic seizure prediction models. He is also actively exploring AI in cybersecurity, specifically in blockchain security, to mitigate data tampering risks. His work in financial analytics uses AI and machine learning to predict market trends, including cryptocurrency values, demonstrating his interdisciplinary approach to solving real-world problems. In addition to these topics, Mr. Islam is involved in pioneering research in IoT security and bioinformatics. His research aims to address key global challenges such as healthcare delivery, data security, and economic stability through cutting-edge AI applications. His innovative contributions to various fields have resulted in multiple published articles in prestigious journals, demonstrating the far-reaching impact of his work.

Publication Top Notes

  • Detection of distributed denial of service (DDoS) attacks in IoT-based monitoring system of banking sector using machine learning models ๐ŸŒ๐Ÿ”๐Ÿ“Š
  • IOTA-Based Mobile Crowd Sensing: Detection of Fake Sensing Using Logit-Boosted Machine Learning Algorithms ๐Ÿค–๐Ÿ“ฑ๐Ÿ’ก
  • Real-time detection schemes for memory DoS (M-DoS) attacks on cloud computing applications โ˜๏ธ๐Ÿ’ป๐Ÿ›ก๏ธ
  • Detection of renal cell hydronephrosis in ultrasound kidney images: a study on the efficacy of deep convolutional neural networks ๐Ÿฅ๐Ÿง ๐Ÿ“ธ
  • A novel anomaly detection system on the internet of railways using extended neural networks ๐Ÿš†๐Ÿ”โš™๏ธ
  • NeuroHealth guardian: A novel hybrid approach for precision brain stroke prediction and healthcare analytics ๐Ÿง ๐Ÿ’“๐Ÿ“ˆ
  • An intelligent approach for preserving the privacy and security of a smart home based on IoT using LogitBoost techniques ๐Ÿ ๐Ÿ”๐Ÿ’ก
  • Enhancing Economic Stability with Innovative Crude Oil Price Prediction and Policy Uncertainty Mitigation in USD Energy Stock Markets ๐Ÿ’ฐ๐Ÿ“Š๐Ÿ“‰
  • Investigating the Effectiveness of Novel Support Vector Neural Network for Anomaly Detection in Digital Forensics Data ๐Ÿ’พ๐Ÿ”Ž๐Ÿ‘จโ€๐Ÿ’ป
  • Empowering global ethereum price prediction with EtherVoyant: a state-of-the-art time series forecasting model โ›“๏ธ๐Ÿ’น๐Ÿ”ฎ