Sina Ahmadi | Computer Science | Excellence in Research

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)

 

Farhad Soleimanian Gharehchopogh | Artificial Intelligent | Best Researcher Award

Assoc. Prof. Dr. Farhad Soleimanian Gharehchopogh | Artificial Intelligent | Best Researcher Award

Dean of Faculty at Urmia Branch, Islamic Azad University, Iran

Dr. Farhad Soleimanian Gharehchopogh is a distinguished academic with a profound background in computer science and software engineering. He is renowned for his contributions to machine learning, artificial intelligence, and computational intelligence. His research focuses on solving complex problems using evolutionary algorithms and optimization techniques. Dr. Soleimanian is also an active participant in academic circles, serving on the editorial boards of several prestigious journals and regularly presenting his findings at international conferences. With numerous publications in high-impact journals, he has significantly influenced his field. His dedication to research and education has earned him accolades, making him a respected figure among peers and students alike.

Professional Profile

Education

Dr. Farhad Soleimanian Gharehchopogh holds a Ph.D. in Computer Science, specializing in Software Engineering from Urmia University, Iran. His doctoral research focused on advanced optimization techniques and their applications in artificial intelligence. Prior to his Ph.D., he completed a Master of Science in Software Engineering at Islamic Azad University, Tabriz Branch, where he developed a strong foundation in programming, data structures, and algorithm design. He earned his Bachelor of Science in Computer Science from Islamic Azad University, Urmia Branch, where he first explored his interest in computational intelligence. His academic journey has been characterized by a consistent focus on deepening his understanding of complex computational systems.

Professional Experience

Dr. Farhad Soleimanian Gharehchopogh has held various academic positions throughout his career, contributing to the growth of computer science education and research. He has served as an Assistant Professor at Islamic Azad University, Urmia Branch, where he taught undergraduate and graduate courses in software engineering and computer science. In addition to teaching, he has supervised numerous master’s and Ph.D. students, guiding their research in areas like machine learning and optimization algorithms. He has also collaborated with international researchers on various projects, aiming to solve real-world problems using advanced computational methods. His professional experience is marked by a commitment to fostering innovation in both academic and practical applications of computer science.

Research Interest

Dr. Soleimanian’s research interests are centered around machine learning, artificial intelligence, and computational optimization. He is particularly interested in developing new algorithms for data mining, evolutionary computing, and swarm intelligence. His work often explores how optimization techniques, such as genetic algorithms, particle swarm optimization, and ant colony optimization, can be applied to solve complex problems in various fields. Additionally, he is passionate about deep learning and its applications in pattern recognition, natural language processing, and image analysis. Dr. Soleimanian continually seeks to advance the field through innovative research, aiming to bridge the gap between theoretical concepts and practical implementations.

Research Skills

Dr. Farhad Soleimanian Gharehchopogh possesses a wide array of research skills that make him a leader in computational intelligence and software engineering. He has extensive experience in developing and implementing optimization algorithms, leveraging his expertise in evolutionary computing and metaheuristics. Proficient in programming languages such as Python, MATLAB, and C++, he applies these skills to simulate and analyze complex models. Dr. Soleimanian is also skilled in statistical analysis and data visualization, enabling him to derive meaningful insights from large datasets. His ability to collaborate effectively with other researchers and his strong analytical mindset have allowed him to make significant contributions to his field.

Awards and Honors

Dr. Soleimanian’s excellence in research and education has been recognized with several awards and honors throughout his career. He has received accolades for his high-quality research papers presented at international conferences and published in peer-reviewed journals. His contributions to the field have been acknowledged with best paper awards and recognition from academic societies. He has also been honored for his outstanding teaching and mentoring, guiding students towards academic and professional success. Dr. Soleimanian’s dedication to advancing computer science and his commitment to academic excellence have made him a recipient of numerous prestigious awards, highlighting his impact in both research and education.

Conclusion

Dr. Farhad Soleimanian Gharehchopogh is a strong candidate for the Best Researcher Award, given his extensive research output, mentorship of graduate students, and recognition among the top-cited scientists globally. His consistent contributions to the academic and research community, particularly in computer engineering, make him well-suited for this award. Addressing the minor areas for improvement, such as updating student mentorship records and highlighting recent publications, would further solidify his application.

Publications Top Notes

  • Recent applications and advances of African Vultures Optimization Algorithm
    Authors: AG Hussien, FS Gharehchopogh, A Bouaouda, S Kumar, G Hu
    Journal: Artificial Intelligence Review 57 (12), 1-51
    Year: 2024
    Citations: Not specified
  • An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer
    Authors: FA Özbay, E Özbay, FS Gharehchopogh
    Journal: CMES-Computer Modeling in Engineering & Sciences 141 (2)
    Year: 2024
    Citations: Not specified
  • Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems
    Authors: M Abdel-Salam, G Hu, E Çelik, FS Gharehchopogh, IM El-Hasnony
    Journal: Computers in Biology and Medicine 179, 108803
    Year: 2024
    Citations: 6
  • A hybrid principal label space transformation-based ridge regression and decision tree for multi-label classification
    Authors: SHS Ebrahimi, K Majidzadeh, FS Gharehchopogh
    Journal: Evolving Systems, 1-37
    Year: 2024
    Citations: Not specified
  • Multifeature Fusion Method with Metaheuristic Optimization for Automated Voice Pathology Detection
    Authors: E Özbay, FA Özbay, N Khodadadi, FS Gharehchopogh, S Mirjalili
    Journal: Journal of Voice
    Year: 2024
    Citations: Not specified
  • A Quasi-Oppositional Learning-based Fox Optimizer for QoS-aware Web Service Composition in Mobile Edge Computing
    Authors: RH Sharif, M Masdari, A Ghaffari, FS Gharehchopogh
    Journal: Journal of Grid Computing 22 (3), 64
    Year: 2024
    Citations: Not specified
  • A novel offloading strategy for multi-user optimization in blockchain-enabled Mobile Edge Computing networks for improved Internet of Things performance
    Authors: AM Rahmani, J Tanveer, FS Gharehchopogh, S Rajabi, M Hosseinzadeh
    Journal: Computers and Electrical Engineering 119, 109514
    Year: 2024
    Citations: 5
  • An Intrusion Detection System on The Internet of Things Using Deep Learning and Multi-objective Enhanced Gorilla Troops Optimizer
    Authors: H Asgharzadeh, A Ghaffari, M Masdari, FS Gharehchopogh
    Journal: Journal of Bionic Engineering 21 (5), 2658-2684
    Year: 2024
    Citations: 2
  • Visualization and classification of mushroom species with multi-feature fusion of metaheuristics-based convolutional neural network model
    Authors: E Özbay, FA Özbay, FS Gharehchopogh
    Journal: Applied Soft Computing 164, 111936
    Year: 2024
    Citations: 1
  • A software defect prediction method using binary gray wolf optimizer and machine learning algorithms
    Authors: H Wang, B Arasteh, K Arasteh, FS Gharehchopogh, A Rouhi
    Journal: Computers and Electrical Engineering 118, 109336
    Year: 2024
    Citations: 1

Praveen Naik | Artificial Intelligence Award | Best Researcher Award

Mr. Praveen Naik | Artificial Intelligence Award | Best Researcher Award

Researcher at Meru University of Science and Technology, Kenya

Mr. Erick Mutwiri Kirimi is a dedicated and accomplished individual with a strong background in mathematics. With a Bachelor’s degree in Education Science and ongoing PhD studies in Computational and Applied Mathematics, he has developed a deep understanding of mathematical concepts and their practical applications. Mr. Kirimi’s academic journey includes serving as a part-time lecturer at several universities, where he imparts his knowledge to students. He has also gained valuable teaching experience as a mathematics and chemistry teacher, including serving as the Head of the Mathematics Department. His academic achievements are further highlighted by scholarships, including a full scholarship for his PhD studies in Computational Mathematics and a partial scholarship for his PhD studies in Applied Mathematics. These scholarships reflect his commitment to academic excellence and his potential to make significant contributions to the field of mathematics. Mr. Kirimi’s research skills, teaching abilities, leadership qualities, computer proficiency, and strong communication and interpersonal skills make him a well-rounded individual poised for success in his academic and professional endeavors.

Professional Profiles:

Professional Experience:

Praveen Naik has been a Research Fellow at the National Institute of Technology Karnataka, Surathkal since 2020. In this role, he has conducted research on “Investigation of Arecanut Images for Grading through Non-Destructive Methods.” His contributions to the project include dataset curation, the development of a lightweight and efficient model, implementation of an Adaptive Genetic-Based Model Optimization, introduction of a non-destructive methodology, and successful resolution of Arecanut grading challenges. Prior to his current position, Praveen Naik served as a Senior Assistant Professor at Shri Madhwa Vadiraja Institute of Technology and Management from 2013 to 2020. During this time, he managed a variety of subjects, crafted compelling curricula, and conducted impactful lectures. He also provided mentorship to students, collaborated seamlessly with peers, and efficiently managed administrative responsibilities within the academic setting. From 2010 to 2011, Praveen Naik worked as a Software Programmer at SouthCan Software, where he played a pivotal role in the Milk Dairy Project. His responsibilities included supervising day-to-day dairy operations, overseeing tasks such as data entry, manipulation, and transactions. He also contributed to report customization using SQL-Server Reporting Service, thereby enhancing reporting functionalities for the organization.

Academic:

Since 2020, Praveen Naik has been pursuing a Ph.D. in Information Technology at the National Institute of Technology Karnataka, Surathkal. Prior to this, he completed his M.Tech in Computer Science and Engineering from Atria Institute of Technology, Bengaluru, from 2011 to 2013. Praveen’s academic journey began with a Bachelor’s degree in Information Science and Engineering from Nitte Mahalinga Adyanthaya Memorial Institute of Technology, Nitte, which he completed from 2006 to 2010.

Areas of Specialization:

Praveen Naik has specialized expertise in Object Detection, Model Optimization, and Deep Learning, with a focus on YOLOv5. His experience includes extensive work in Dataset Curation, ensuring high-quality data inputs for machine learning models.

Achievements:

Praveen Naik has demonstrated his academic prowess by qualifying in several prestigious examinations. He cleared the GATE (Graduate Aptitude Test in Engineering) in 2020, showcasing his proficiency in engineering concepts. Additionally, he achieved qualification in the UGC-NET (University Grants Commission – National Eligibility Test) in 2020, indicating his in-depth knowledge and understanding of his field. Furthermore, he passed the K-SET (Karnataka State Eligibility Test) in 2019, demonstrating his expertise and competence in the field of education.

Publications:

  1. Flower Phenotype Recognition and Analysis using YoloV5 Models
    • Authors: PM Naik, B Rudra
    • Year: 2022
    • Journal: Grenze International Journal of Engineering & Technology (GIJET)
    • Volume: 8
    • Issue: 2
    • Citations: 3
  2. Deep learning-based arecanut detection for X-ray radiography: improving performance and efficiency for automated classification and quality control
    • Authors: PM Naik, B Rudra
    • Year: 2024
    • Journal: Nondestructive Testing and Evaluation
    • Pages: 1-21
  3. Classification of Arecanut X-Ray Images for Quality Assessment Using Adaptive Genetic Algorithm and Deep Learning
    • Authors: PM Naik, B Rudra
    • Year: 2023
    • Journal: IEEE Access
    • Volume: 11
    • Pages: 127619-127636
  4. Prevention of Webshell Attack using Machine Learning Techniques
    • Authors: S YC, PM Naik, B Rudra
    • Year: 2021
    • Journal: Grenze International Journal of Engineering & Technology (GIJET)
    • Volume: 7
    • Issue: 1