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.

Mona Jamjoom | AI | Best Researcher Award

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Assoc Prof Dr. Mona Jamjoom | AI | Best Researcher Award

Assoc Prof Dr. Mona Jamjoom, Princess Nourah bint Abdulrahman University, Saudi Arabia

Assoc Prof Dr. Mona Jamjoom is an accomplished researcher in the field of artificial intelligence, recognized for her innovative contributions and impactful studies. With a strong focus on machine learning and data analytics, she has published numerous papers in leading journals and has been awarded the Best Researcher Award for her groundbreaking work. Mona is passionate about harnessing AI to solve complex problems and improve decision-making processes across various industries. Her commitment to advancing technology while addressing ethical considerations makes her a prominent figure in the AI community.

Profile:

Scholar

Academics:

Assoc Prof Dr. Mona Jamjoom holds a PhD in Artificial Intelligence from King Saud University, awarded in May 2016. She also earned her Master’s degree in Computer Science from the same institution in 2004, following her Bachelor’s degree in Computer Science, which she completed in 1992. Her academic background provides a strong foundation for her research and contributions to the field of AI.

Professional Experiences:

Assoc Prof Dr. Mona Jamjoom has extensive professional experience in academia. Since 2021, she has served as an Associate Professor at Princess Nourah bint Abdulrahman University in Riyadh, Saudi Arabia. Prior to this, she was an Assistant Professor at the same institution from 2017 to 2021. Mona began her academic career as a Lecturer at Princess Nourah bint Abdulrahman University from 2007 to 2016, and before that, she worked as a Teaching Assistant from 1998 to 2007. Her career in the field began in 1993, when she provided technical support at the university, further solidifying her commitment to education and technology.

Activities:

Assoc Prof Dr. Mona Jamjoom is actively engaged in various professional activities that enhance her contributions to the field of artificial intelligence. In 2024, she joined the work team at the Center for Advanced Studies in Artificial Intelligence at King Saud University, collaborating on the KSU AI Satellite Lab project with SDAIA. She served as an external examiner for a doctoral thesis on deep learning applications for visual pollution detection in Riyadh. Additionally, she reviewed applications for the Apple Developer Academy’s second challenge for female students and participated in consulting sessions during the Gulf Hackathon Program focused on AI in public education. Mona also acted as a consultant for the UNESCO project “AI Capacity Building in Arabic-speaking Countries,” supported by Huawei Technologies. She has reviewed numerous papers for ISI journals and attended the research day at Princess Nourah bint Abdulrahman University. Furthermore, she co-supervised a PhD student specializing in Cognitive Computing at Universiti Kuala Lumpur, Malaysia.

Publication Top Notes:

M. Adil, Z. Yinjun, M. M. Jamjoom, and Z. Ullah. “OptDevNet: An Optimized Deep Event-Based Network Framework for Credit Card Fraud Detection.” IEEE Access, vol. 12, pp. 132421-132433, 2024. doi: 10.1109/ACCESS.2024.3458944.

Rabbani, H., Shahid, M. F., Khanzada, T. J. S., Siddiqui, S., Jamjoom, M. M., Ashari, R. B., Ullah, Z., Mukati, M. U., and Nooruddin, M. “Enhancing Security in Financial Transactions: A Novel Blockchain-Based Federated Learning Framework for Detecting Counterfeit Data in Fintech.” PeerJ Computer Science, vol. 10, e2280, 2024.

Malik, M. S. I., Nawaz, A., and Jamjoom, M. M. “Hate Speech and Target Community Detection in Nastaliq Urdu Using Transfer Learning Techniques.” IEEE Access, 2024.

Kurtoğlu, A., Eken, Ö., Çiftçi, R., Çar, B., Dönmez, E., Kılıçarslan, S., Jamjoom, M. M., Abdel Samee, N., Hassan, D. S. M., and Mahmoud, N. F. “The Role of Morphometric Characteristics in Predicting 20-Meter Sprint Performance Through Machine Learning.” Scientific Reports, vol. 14, no. 1, 16593, 2024.

Shah, S. M. A. H., Khan, M. Q., Rizwan, A., Jan, S. U., Samee, N. A., and Jamjoom, M. M. “Computer-Aided Diagnosis of Alzheimer’s Disease and Neurocognitive Disorders with Multimodal Bi-Vision Transformer (BiViT).” Pattern Analysis and Applications, vol. 27, no. 3, 76, 2024.

Ishtiaq, A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Product Helpfulness Detection with Novel Transformer Based BERT Embedding and Class Probability Features.” IEEE Access, 2024.

Abbas, M. A., Munir, K., Raza, A., Samee, N. A., Jamjoom, M. M., and Ullah, Z. “Novel Transformer Based Contextualized Embedding and Probabilistic Features for Depression Detection from Social Media.” IEEE Access, 2024.

Elhadad, A., Jamjoom, M., and Abulkasim, H. “Reduction of NIFTI Files Storage and Compression to Facilitate Telemedicine Services Based on Quantization Hiding of Downsampling Approach.” Scientific Reports, vol. 14, no. 1, 5168, 2024.

Malik, M. S. I., Younas, M. Z., Jamjoom, M. M., and Ignatov, D. I. “Categorization of Tweets for Damages: Infrastructure and Human Damage Assessment Using Fine-Tuned BERT Model.” PeerJ Computer Science, vol. 10, e1859, 2024.

Malik, M. S. I., Nawaz, A., Jamjoom, M. M., and Ignatov, D. I. “Effectiveness of ELMo Embeddings and Semantic Models in Predicting Review Helpfulness.” Intelligent Data Analysis, (Preprint), 1-21, 2023.

Ali Ghandi | Artificial intelligence | Best Researcher Award

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Ali Ghandi | Artificial intelligence | Best Researcher Award

PhD, Sharif University of Technology, Iran.

Ali Ghandi is an innovative researcher and educator specializing in Artificial Intelligence, particularly in reinforcement learning and generative AI. Currently pursuing his Ph.D. at Sharif University of Technology, he is known for his groundbreaking work that enhances reinforcement learning processes by leveraging side-channel data. Ali’s academic journey began with a B.Sc. in Digital System Design, followed by an M.Sc. in Machine Learning, where he excelled as one of the top students. He has taught courses in Neural Networks and Deep Generative Models, effectively sharing his knowledge with students. His research has been recognized through publications in reputable journals and presentations at significant conferences, such as the Iran Workshop on Communication and Information Theory. Ali’s accomplishments include a top rank in a national entrance exam and membership in Iran’s National Elites Foundation, underscoring his exceptional capabilities and contributions to the field of AI and his commitment to advancing technology for practical applications.

Profile:

 

Education

Ali Ghandi has an impressive academic background in electrical and computer engineering, with a particular focus on Artificial Intelligence. He is currently pursuing a Ph.D. at Sharif University of Technology (SUT) in Tehran, where he is conducting innovative research aimed at improving reinforcement learning processes using side-channel data. Prior to his doctoral studies, Ali earned his Master’s degree in Machine Learning from SUT, where his thesis focused on analyzing IoT systems through location-based data, effectively modeling traffic based on dynamic maps and registered commutes. He completed his Bachelor’s degree in Digital System Design at the same university, where he developed an online coordinate system for managing thermal loads in IoT applications. Throughout his educational journey, Ali has consistently demonstrated academic excellence, evidenced by his top rankings in national examinations and competitive academic events, establishing him as a leading figure among his peers in the field of electrical engineering and AI.

Professional Experiences

Ali Ghandi has an impressive academic background in electrical and computer engineering, with a particular focus on Artificial Intelligence. He is currently pursuing a Ph.D. at Sharif University of Technology (SUT) in Tehran, where he is conducting innovative research aimed at improving reinforcement learning processes using side-channel data. Prior to his doctoral studies, Ali earned his Master’s degree in Machine Learning from SUT, where his thesis focused on analyzing IoT systems through location-based data, effectively modeling traffic based on dynamic maps and registered commutes. He completed his Bachelor’s degree in Digital System Design at the same university, where he developed an online coordinate system for managing thermal loads in IoT applications. Throughout his educational journey, Ali has consistently demonstrated academic excellence, evidenced by his top rankings in national examinations and competitive academic events, establishing him as a leading figure among his peers in the field of electrical engineering and AI.

 

Research skills

Ali Ghandi possesses a strong set of research skills that position him as a leading figure in the field of Artificial Intelligence. His primary focus is on reinforcement learning, where he has developed innovative approaches, such as utilizing side-channel data to enhance the learning process. Ali’s expertise extends to deep generative models, where he explores the potential of generative AI in various applications. Additionally, he is adept at massive data mining, allowing him to extract valuable insights from large datasets, which is crucial in today’s data-driven world. His research also includes analyzing IoT systems, particularly in modeling traffic using location-based data. This multifaceted skill set enables Ali to approach complex problems with a comprehensive perspective, combining theoretical knowledge with practical applications. His ability to publish in reputable journals and present at conferences demonstrates his commitment to advancing the field and contributing to the academic community.

 

Awards And Recoginition

Ali Ghandi has received numerous accolades that underscore his academic excellence and contributions to the field of Artificial Intelligence. He achieved a remarkable 68th rank in a highly competitive university entrance exam, placing him among the top candidates out of 250,000 participants. His outstanding performance in the International A-lympiad, where he ranked third, showcases his proficiency in applied mathematics within a global context. Additionally, Ali has been a member of Iran’s National Elites Foundation since 2013, reflecting his recognition as a leading talent in his field. His academic journey at Sharif University of Technology has been marked by multiple distinctions, including first place among students in his Digital Systems minor and second place among all M.Sc. Electrical Engineering students. These honors highlight Ali’s commitment to excellence in research and education, positioning him as a promising contributor to the advancement of Artificial Intelligence.

Conclusion

In conclusion, Ali Ghandi possesses a solid foundation of academic excellence, innovative research, and early recognition in his field. His focus on advanced topics within AI positions him well for the Best Researcher Award. By addressing areas for improvement, such as increasing the practical impact of his work and expanding his collaborative efforts, Ali can further enhance his candidacy for this prestigious recognition. His commitment to advancing knowledge in AI and machine learning makes him a strong contender for the award.

Publication Top Notes

  • Title: Ex-RL: Experience-based Reinforcement Learning
    Authors: Ghandi, A., Shouraki, S.B., Gholampour, I., Kamranian, A., Riazati, M.
    Year: 2025
    Citation: Information Sciences, 689, 121479 📚🤖
  • Title: Deep ExRL: Experience-Driven Deep Reinforcement Learning in Control Problems
    Authors: Ghandi, A., Shouraki, S.B., Riazati, M.
    Year: 2024
    Citation: 12th Iran Workshop on Communication and Information Theory (IWCIT 2024) 📄🔍