Sina Ahmadi | Computer Science | Excellence in Research

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Mr. Sina Ahmadi | Computer Science | Excellence in Research

Scholar at National Coalition of Independent Scholars (NCIS), Canada

Sina Ahmadi is an accomplished management professional with significant experience in cloud infrastructure, software engineering, security optimization, and networking. His extensive career has seen him working in prominent positions, managing complex projects and teams. He is recognized for his ability to design and manage Kubernetes clusters, cloud networking, and optimize service meshes such as Istio for global applications. Sina is known for his strategic vision in aligning technical solutions with business goals, consistently delivering results that exceed client expectations. His work spans across multiple global organizations, including Block, ME Bank, and MYOB, where he played key roles in cloud infrastructure, networking, and security solutions. Sina’s deep technical expertise is matched by his leadership abilities, having mentored teams, facilitated technical discussions, and driven innovative projects that have had a measurable impact on business outcomes. His contributions also extend to the academic sphere, where he regularly contributes as a peer reviewer and has published several influential papers on topics such as cloud security, AI in security, and network defense. With numerous awards, accolades, and professional affiliations, Sina continues to be a thought leader in his field.

Professional Profile

Education:

Sina Ahmadi holds a Master’s degree in Information Technology from the University of Melbourne (2015–2017), where he earned a place on the Dean’s Honors List, showcasing his academic excellence. His undergraduate studies in Computer Science (B.Sc.) were completed at the University of Mazandaran (2005–2010), forming the foundation of his technical expertise. During his time at the University of Melbourne, Sina’s academic focus honed his skills in cloud computing, networking, and security, which would later define his professional career. His education provided him with both a theoretical understanding and practical skills, enabling him to address complex technical challenges in the field of IT infrastructure, cloud architecture, and security. Sina has consistently sought to build on his academic credentials through ongoing professional development, as evidenced by his memberships in leading organizations such as IEEE, ACM, and ACS. These affiliations not only reflect his commitment to staying at the forefront of technological advancements but also contribute to his continuous learning and research in the field. Sina’s educational background, coupled with his professional experience, has empowered him to make significant contributions to cloud security and infrastructure engineering.

Professional Experience:

Sina Ahmadi’s professional journey spans a diverse range of roles in the tech industry, showcasing his ability to lead teams and deliver innovative solutions across various domains such as cloud infrastructure, networking, and security. Currently, as a Senior Staff Engineer at Block, he oversees the global platform and networking infrastructure on AWS, setting the platform’s vision and roadmap to align with business goals. He has played pivotal roles in managing cloud platforms for global companies like Afterpay and Square, where he was responsible for ensuring the seamless operation of network infrastructure and traffic management. Prior to this, as Platform Lead for Infra & Edge Networking at Block, Sina successfully delivered solutions for global app connectivity and edge networking. His experience at ME Bank further solidified his leadership abilities, where he designed and implemented security and network solutions while managing cloud teams. In his earlier roles at MYOB and Rundl, Sina honed his expertise in Kubernetes management, security, and cloud architecture, consistently optimizing system performance and security. His diverse career has allowed him to manage large-scale projects and lead teams that have shaped the digital transformation of major organizations.

Research Interests:

Sina Ahmadi’s research interests primarily lie in the intersection of cloud computing, network security, and artificial intelligence. His focus is on optimizing security measures in cloud environments, particularly in multi-cloud and hybrid cloud infrastructures. He is deeply engaged in exploring innovative solutions for Distributed Denial of Service (DDoS) attack prevention, network intrusion detection, and the application of zero-trust architectures in cloud networks. Sina is also interested in the role of AI and machine learning in enhancing cloud security, specifically in developing next-generation firewalls and intrusion detection systems. His work delves into edge computing security, examining how emerging technologies like edge networks impact the overall security and privacy of cloud infrastructures. In addition to his interest in security, Sina is also passionate about cloud networking, including the implementation of complex service meshes like Istio and Envoy to improve scalability, reliability, and performance in cloud-based applications. His research interests aim to solve critical challenges faced by organizations in securing their cloud and network environments while ensuring seamless and efficient connectivity across distributed platforms.

Research Skills:

Sina Ahmadi possesses a comprehensive set of research skills, with a strong foundation in both theoretical and applied aspects of cloud computing, networking, and security. His proficiency in cloud platforms like AWS, combined with his expertise in Kubernetes and Istio, allows him to tackle complex research challenges in infrastructure optimization and network security. Sina has honed his ability to conduct in-depth research on cloud security, from designing secure cloud architectures to investigating novel solutions for mitigating security threats in cloud environments. He excels in analyzing large datasets, drawing meaningful insights, and applying these insights to solve practical industry problems. His extensive experience as a peer reviewer for journals like IEEE Access and SN Computer Science highlights his analytical skills and ability to assess and critique cutting-edge research in his field. Sina’s research skills are complemented by his hands-on experience in managing multi-region cloud infrastructures, implementing security controls, and developing automation processes for enhanced productivity. His expertise in AI-based security systems and network intrusion detection algorithms further reinforces his capabilities in advanced research areas within cloud and network security.

Awards and Honors:

Sina Ahmadi has received numerous awards and accolades for his exceptional contributions to cloud computing and security. One of his notable recognitions is the “Keep ME Secure” award from ME Bank, acknowledging his outstanding achievement in security. His academic excellence at the University of Melbourne earned him a place on the Dean’s Honors List, further demonstrating his commitment to high standards in both education and professional practice. Additionally, Sina’s role as a reviewer for prestigious journals like IEEE Access and SN Computer Science highlights his standing as a respected thought leader in his field. His continuous contributions to the advancement of cloud security and infrastructure engineering have been instrumental in shaping industry standards, and his work has been widely recognized by both academic and professional communities. These accolades not only reflect his technical expertise but also his leadership in driving innovation in cloud infrastructure, networking, and security.

Conclusion:

Sina Ahmadi is an exemplary professional and researcher whose contributions to the fields of cloud infrastructure, networking, and security have had a significant impact on the industry. His leadership in managing global platforms for major organizations such as Block and ME Bank, combined with his research on cloud security and network defense strategies, showcases his ability to bridge the gap between theory and practice. Sina’s academic background, coupled with his extensive professional experience, positions him as a thought leader in the tech community. His work in optimizing cloud and Kubernetes infrastructures, along with his research on AI-based security systems, contributes to the evolving landscape of cloud technologies. His dedication to continuous learning, mentoring, and collaboration has earned him numerous awards and professional recognitions, affirming his status as an influential figure in cloud computing and network security. As he continues to expand his research and professional contributions, Sina is poised to further shape the future of secure and scalable cloud environments.

Publications Top Notes

  1. Title: A Comprehensive Study on Integration of Big Data and AI in Financial Industry and its Effect on Present and Future Opportunities
    Author: S Ahmadi
    Year: 2024
    Citations: 70
    Journal: International Journal of Current Science Research and Review 7 (1), 66-74
  2. Title: Open AI and its Impact on Fraud Detection in Financial Industry
    Author: S Ahmadi
    Year: 2023
    Citations: 63
    Journal: Journal of Knowledge Learning and Science Technology ISSN, 2959-6386
  3. Title: Optimizing Data Warehousing Performance Through Machine Learning Algorithms in the Cloud
    Author: S Ahmadi
    Year: 2023
    Citations: 48
    Journal: International Journal of Science and Research (IJSR) 12 (12), 1859-1867
  4. Title: Elastic Data Warehousing: Adapting To Fluctuating Workloads With Cloud-Native Technologies
    Author: S Ahmadi
    Year: 2023
    Citations: 40
    Journal: Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)
  5. Title: Next Generation AI-Based Firewalls: A Comparative Study
    Author: S Ahmadi
    Year: 2023
    Citations: 37
    Journal: International Journal of Computer (IJC) 49 (1), 245-262
  6. Title: Zero trust architecture in cloud networks: application, challenges and future opportunities
    Author: S Ahmadi
    Year: 2024
    Citations: 27
    Journal: Journal of Engineering Research and Reports 26 (2), 215-228
  7. Title: Challenges and Solutions in Network Security for Serverless Computing
    Author: S Ahmadi
    Year: 2024
    Citations: 26
    Journal: International Journal of Current Science Research and Review 7 (1), 218-229
  8. Title: Security Implications of Edge Computing in Cloud Networks
    Author: S Ahmadi
    Year: 2024
    Citations: 19
    Journal: Journal of Computer and Communications 12, 26-46
  9. Title: Security And Privacy Challenges in Cloud-Based Data Warehousing: A Comprehensive Review
    Author: S Ahmadi
    Year: 2023
    Citations: 18
    Journal: Journal of Computer Science Trends and Technology 11 (6), 17-27
  10. Title: Cloud Security Metrics and Measurement
    Author: S Ahmadi
    Year: 2023
    Citations: 15
    Journal: Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online)

 

Amal Shaheen | Machine Learning AI | Excellence in Research

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Amal Shaheen | Machine Learning AI | Excellence in Research

Doctrate at UOB, Bahrain.

Amal Shaheen is a distinguished AI Transformation Strategy Leader and Big Data Analytics Expert with over 25 years of experience in government, business, and IT sectors. Renowned for her innovative thinking and strategic vision, she combines practical experience with academic expertise in AI, Machine Learning, and Project Management. Amal excels in driving AI transformation strategies, enhancing organizational efficiency, and overseeing complex projects to achieve impactful outcomes. Her leadership style emphasizes empowerment, collaboration, and resilience, allowing her to navigate dynamic environments effectively. As a current lecturer at the University of Bahrain, she is passionate about guiding students in Project Management and Big Data Analytics, preparing them for successful careers in technology. With a commitment to sustainable growth and continuous improvement, Amal is dedicated to advancing her field and contributing to impactful research and education.

Profile👤

Orcid

Education📝

Amal Shaheen holds a Ph.D. in Computing and Information Technology with a focus on AI and Machine Learning from the University of Bahrain, where she is expected to graduate in December 2024. Her thesis explores novel models in Graph Deep Learning based on Autoencoders, showcasing her commitment to advancing knowledge in the field. She also possesses an MBA in Management Information Systems from the New York Institute of Technology, Bahrain, which complements her technical expertise with essential management skills. Furthermore, her educational background includes a Bachelor’s degree in Computer Science from the University of Qatar. To further enhance her qualifications, Amal has obtained various certifications, including AI Transformation Leader from the United States AI Institute and Professional Co-Active Coach Certified in Leadership. Her diverse education equips her with a strong foundation to excel in both academic and professional environments.

Experience👨‍🏫

Amal Shaheen has amassed extensive experience across various leadership roles, demonstrating her capabilities in both academic and governmental sectors. Currently, she serves as a lecturer at the University of Bahrain, guiding students in Project Management and Big Data Analytics, where she blends practical insights with academic rigor. Previously, she held significant positions at the Civil Service Bureau, including Director of the Management Information Directorate and Acting Director of the Organizational Performance Directorate. In these roles, she managed IT processes, developed strategic business initiatives, and led the transformation of manual services to electronic workflows. Additionally, she spearheaded multiple civil service projects, ensuring their successful implementation and alignment with organizational goals. Her rich background reflects her ability to oversee complex plans, drive innovative solutions, and enhance operational efficiency, establishing her as a prominent leader in her field.

Research Interest🔬 

Amal Shaheen’s research interests lie at the intersection of AI, Big Data Analytics, and Machine Learning, with a focus on developing innovative solutions to real-world challenges. Her current research delves into Graph Deep Learning, exploring novel models that leverage Autoencoders to enhance predictive capabilities and data analysis. Amal is particularly passionate about the application of AI in government and public services, aiming to streamline processes and improve decision-making through data-driven insights. She is also interested in sustainable technology and its role in fostering organizational growth and efficiency. By bridging theoretical knowledge and practical application, Amal aims to contribute significantly to advancing research in AI and data analytics. Her commitment to mentorship and student engagement further enhances her research endeavors, as she encourages the next generation of researchers to explore innovative approaches in their studies and projects.

Awards and Honors🏆

Throughout her illustrious career, Amal Shaheen has received numerous awards and honors in recognition of her contributions to AI, Big Data Analytics, and public service transformation. Among her notable achievements is her designation as an AI Transformation Leader from the United States AI Institute, highlighting her expertise in driving technological advancements. Additionally, she has completed various training programs in leadership, project management, and strategic planning, earning accolades for her commitment to excellence and innovation. Amal’s leadership in spearheading successful civil service initiatives has garnered recognition from government authorities, underscoring her impact on organizational efficiency and effectiveness. Her contributions to education have also been acknowledged, as she continues to inspire students and foster a culture of learning and growth. These accolades reflect her dedication to advancing knowledge and driving positive change within her field.

Skills🛠️

Amal Shaheen possesses a diverse skill set that positions her as a leader in the fields of AI, Big Data Analytics, and Project Management. Her technical skills include proficiency in advanced AI frameworks, Machine Learning models, and data analysis tools such as Spark, Hadoop, Python, and R. Additionally, Amal has strong project management skills, enabling her to guide complex initiatives from conception to execution while ensuring quality and adherence to deadlines. Her leadership abilities are complemented by exceptional interpersonal skills, fostering collaboration and teamwork among colleagues and students. Detail-oriented and adaptable, she thrives in dynamic environments, embracing change and finding innovative solutions to challenges. Furthermore, Amal’s analytical thinking, strategic planning, and problem-solving skills equip her to identify and capitalize on opportunities for improvement and growth within organizations. This well-rounded skill set enables her to drive impactful projects and contribute to advancements in her field.

Conclusion 🔍 

In conclusion, Amal Shaheen exemplifies excellence in her roles as an AI Transformation Strategy Leader, educator, and researcher. With over 25 years of experience, she brings a wealth of knowledge and expertise to the fields of AI, Big Data Analytics, and Project Management. Her innovative mindset, strong leadership skills, and commitment to mentorship position her as a role model for aspiring professionals. Amal’s ongoing research endeavors and dedication to advancing technology for organizational efficiency reflect her passion for creating meaningful impacts in both academic and governmental sectors. As she continues her journey, her contributions to the field of AI and her commitment to nurturing the next generation of leaders are sure to leave a lasting legacy. Amal Shaheen stands poised to drive further innovations and advancements in her field, making her a deserving candidate for recognition in excellence in research.

Publication Top Notes

Title: “Innovative Approaches to Big Data Analytics in Public Sector Applications”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Innovative Approaches to Big Data Analytics in Public Sector Applications. Journal of Government Information, 45(2), 101-115.

Title: “Graph Deep Learning: Novel Models Based on Autoencoder Framework”
Author: Amal Shaheen
Year: 2024
Citation: Shaheen, A. (2024). Graph Deep Learning: Novel Models Based on Autoencoder Framework. International Journal of Artificial Intelligence Research, 12(1), 45-59.

Title: “Transforming HR Processes: The Role of AI in Government Agencies”
Author: Amal Shaheen
Year: 2022
Citation: Shaheen, A. (2022). Transforming HR Processes: The Role of AI in Government Agencies. Journal of Public Administration Research and Theory, 34(3), 375-392.

Title: “AI and Machine Learning in Data-Driven Decision Making”
Author: Amal Shaheen
Year: 2021
Citation: Shaheen, A. (2021). AI and Machine Learning in Data-Driven Decision Making. Computing and Informatics, 40(4), 777-794.

Title: “Project Management Best Practices in AI Implementation”
Author: Amal Shaheen
Year: 2023
Citation: Shaheen, A. (2023). Project Management Best Practices in AI Implementation. Project Management Journal, 54(1), 28-39.

Fahd Alharithi | Artificial Intelligence | Best Researcher Award

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Assoc Prof Dr. Fahd Alharithi | Artificial Intelligence | Best Researcher Award

Department chair at Taif University, Saudi Arabia

Dr. Fahd Saad Alharithi is an accomplished researcher and academic with a Ph.D. in Computer Science from Florida Institute of Technology and extensive experience in both teaching and research. Currently an Assistant Professor at Taif University, his research spans a wide array of topics, including medical data categorization, oil spill detection, COVID-19 diagnosis, and IoT security. Dr. Alharithi has published numerous papers in high-impact journals such as Sensors and Remote Sensing, showcasing his innovative approaches and significant contributions to his field. In addition to his research, he has a strong background in teaching, having served as a lecturer and teaching assistant at various institutions. His involvement in volunteer work and leadership roles further highlights his commitment to community service. While his diverse research and impactful publications are noteworthy, highlighting research grants and awards could strengthen his profile for recognition.

Profile

Education

Dr. Fahd Saad Alharithi completed his educational journey with a strong foundation in Computer Science. He earned his Ph.D. from the Florida Institute of Technology, USA, in 2019, where he focused on advanced topics in the field. Prior to that, he obtained his Master of Science degree in Computer Science from the University of New Haven, USA, in 2013. His academic journey began with a Bachelor of Science degree in Computer Science from Taif University, Saudi Arabia, in 2008. This comprehensive educational background, spanning both international and local institutions, has equipped Dr. Alharithi with a robust theoretical and practical understanding of Computer Science, paving the way for his subsequent research and teaching career. His diverse educational experiences contribute significantly to his expertise and innovative approaches in the field.

Professional Experience

Dr. Fahd Saad Alharithi has garnered extensive experience in academia and education, currently serving as an Assistant Professor in the Computer Science Department at Taif University since 2019. His career began with roles as a Lecturer and Teacher Assistant at Taif University and the University of New Haven, where he honed his teaching and research skills. Dr. Alharithi has also contributed as a Trainer at New Horizons Institute, showcasing his versatility in the field. His professional journey is marked by significant research achievements, including innovative publications in medical data categorization, AI-assisted algorithms, and IoT security. His role extends beyond teaching, encompassing volunteer work with the Hemaya Group and leadership positions like President of the Saudi Student Club. Dr. Alharithi’s career reflects a robust blend of research excellence, educational dedication, and active community involvement.

Research Interest

Dr. Fahd Saad Alharithi’s research interests primarily focus on advancing computational methods and applications across various domains. His work explores medical data categorization using flexible mixture models, oil spill detection through SAR image analysis, and the development of hybrid convolutional neural network models for diagnosing diseases from chest X-ray images. Dr. Alharithi is also deeply involved in enhancing IoT security with AI-assisted bio-inspired algorithms and addressing environmental challenges through intelligent garbage detection systems. His research extends to secure communication protocols and energy-efficient solutions for sensor networks, demonstrating a strong emphasis on both practical and theoretical advancements. By integrating innovative methodologies such as deep learning and AI, Dr. Alharithi aims to address complex problems in medical imaging, environmental monitoring, and network security, reflecting a broad and impactful approach to computational science.

Research Skills

Dr. Fahd Saad Alharithi exhibits a robust set of research skills, underscored by his extensive work in computer science and related fields. His proficiency in advanced methodologies, including deep learning, AI-assisted algorithms, and hybrid models, highlights his capacity for innovative problem-solving. Dr. Alharithi’s experience with diverse data types and applications, such as medical data categorization, oil spill detection, and IoT security, demonstrates his ability to tackle complex, interdisciplinary challenges. His strong analytical skills are evident from his impactful publications in high-impact journals like Sensors and Remote Sensing. Additionally, his adeptness in leveraging various computational techniques and his commitment to exploring novel solutions further underscore his research capabilities. Dr. Alharithi’s contributions reflect a deep understanding of both theoretical and practical aspects of his field, positioning him as a skilled researcher with a significant impact on advancing technology and knowledge.

Award and Recognition

Dr. Fahd Saad Alharithi’s research has garnered considerable recognition within the academic community. He has published extensively in high-impact journals, including Sensors, Remote Sensing, and Computers, Materials & Continua, showcasing his significant contributions to fields such as medical data categorization, oil spill detection, and AI-assisted algorithms. His innovative work, particularly in developing hybrid convolutional neural network models and intelligent systems for garbage detection, underscores his leadership in advancing technology. Although specific awards and formal recognitions are not detailed in his resume, Dr. Alharithi’s influential publications and his role in mentoring and educating future researchers highlight his exceptional impact in computer science. His involvement in volunteer activities and community service further demonstrates his commitment to fostering academic and professional excellence.

Conclusion

Dr. Taimoor Asim is a strong candidate for the Best Researcher Award due to his substantial contributions to Mechanical Engineering, particularly in fluid dynamics and renewable energy systems. His extensive research experience, leadership roles, and professional achievements make him a noteworthy contender. To strengthen his candidacy, he could focus on broadening his research impact, exploring diverse research areas, and enhancing community engagement related to his work. Overall, Dr. Asim’s profile reflects a high level of expertise and dedication, aligning well with the criteria for the Best Researcher Award.

Publications Top Notes

  1. Machine learning approaches for advanced detection of rare genetic disorders in whole-genome sequencing
    • Authors: Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Volume: 106, pp. 582–593
  2. IoT-enabled healthcare systems using blockchain-dependent adaptable services
    • Authors: Arul, R., Alroobaea, R., Tariq, U., Alharithi, F.S., Shoaib, U.
    • Journal: Personal and Ubiquitous Computing
    • Year: 2024
    • Volume: 28(1), pp. 43–57
    • Citations: 13
  3. A comprehensive cost performance analysis for a QoS-based scheme in network mobility (NEMO)
    • Authors: Hussein, L.F., Abass, I.A.M., Aissa, A.B., Alzahrani, A.A., Alharithi, F.S.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 76, pp. 349–360
    • Citations: 1
  4. Performance Analysis of Machine Learning Approaches in Automatic Classification of Arabic Language
    • Authors: Alharithi, F.S.
    • Journal: Information Sciences Letters
    • Year: 2023
    • Volume: 12(3), pp. 1563–1578
    • Citations: 1
  5. A blockchain-based hybrid platform for multimedia data processing in IoT-Healthcare
    • Authors: Taloba, A.I., Elhadad, A., Rayan, A., Alharithi, F.S., Park, C.
    • Journal: Alexandria Engineering Journal
    • Year: 2023
    • Volume: 65, pp. 263–274
    • Citations: 74
  6. Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements
    • Authors: Kumar, P., Swarnkar, N.K., Mahela, O.P., Mazon, J.L.V., Alharithi, F.S.
    • Journal: International Transactions on Electrical Energy Systems
    • Year: 2023
    • Volume: 2023, 6315918
    • Citations: 1
  7. Energy-Aware Live VM Migration Using Ballooning in Cloud Data Center
    • Authors: Gupta, N., Gupta, K., Qahtani, A.M., Singh, A., Goyal, N.
    • Journal: Electronics (Switzerland)
    • Year: 2022
    • Volume: 11(23), 3932
    • Citations: 4
  8. NLP-Based Application for Analyzing Private and Public Banks Stocks Reaction to News Events in the Indian Stock Exchange
    • Authors: Dogra, V., Alharithi, F.S., Álvarez, R.M., Singh, A., Qahtani, A.M.
    • Journal: Systems
    • Year: 2022
    • Volume: 10(6), 233
    • Citations: 7
  9. Deep learned BLSTM for online handwriting modeling simulating the Beta-Elliptic approach
    • Authors: Hamdi, Y., Boubaker, H., Rabhi, B., Dhahri, H., Alimi, A.M.
    • Journal: Engineering Science and Technology, an International Journal
    • Year: 2022
    • Volume: 35, 101215
    • Citations: 6
  10. A software for thorax images analysis based on deep learning
    • Authors: Almulihi, A.H., Alharithi, F.S., Mechti, S., Alroobaea, R., Rubaiee, S.
    • Book Chapter: Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention
    • Year: 2022
    • Pages: 1166–1178