Venus Haghighi | Computer Science | Best Researcher Award

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Mrs. Venus Haghighi | Computer Science | Best Researcher Award

Research Associate | Macquarie University | Australia

Mrs. Venus Haghighi is a final-year PhD candidate in Computer Science at Macquarie University, Sydney, focusing on artificial intelligence, data science, and graph learning techniques for fraud detection in complex networks. She holds a master’s degree in Computer Engineering from Isfahan University of Technology, where she worked on mobile cloud computing, and a bachelor’s degree in Computer Engineering from Shahid Bahonar University of Kerman, where she researched AES cryptography. Her professional experience includes serving as a data science researcher at the Intelligent Computing Laboratory, where she develops advanced graph neural networks, hypergraph models, and large language model enhanced frameworks for detecting camouflaged malicious actors. She has also contributed as a sessional teaching associate in both the School of Computing and the Business School at Macquarie University, teaching subjects such as cybersecurity, data science, and information systems. Her research interests span graph neural networks, hypergraph learning, graph transformer networks, graph representation learning, and the integration of LLMs with graph-based methods for real-world applications. She has published in leading venues such as IEEE ICDM, ACM WSDM, ACM CIKM, IJCAI, and ACM Web Conference, along with journal contributions in IEEE Transactions and IEEE Access. Her achievements include the Google Conference Travel Grant, HDR Research Rising Star Award, 3MT Thesis Competition recognition, DF-CRC PhD Top-Up Scholarship, and the Pro-Vice Chancellor Research Excellence Scholarship. She is skilled in Python, PyTorch, PyTorch Geometric, Deep Graph Library, data visualization, and advanced AI model design. Her research impact is evidenced by 150 citations across 13 documents with an h-index of 4.

Profile: Google Scholar

Featured Publications

1. Soltani, B., Haghighi, V., Mahmood, A., Sheng, Q. Z., & Yao, L. (2022). A survey on participant selection for federated learning in mobile networks. Proceedings of the 17th ACM Workshop on Mobility in the Evolving Internet Architecture (MobiArch).

2. Haghighi, V., & Moayedian, N. S. (2018). An offloading strategy in mobile cloud computing considering energy and delay constraints. IEEE Access, 6, 11849–11861.

3. Shabani, N., Wu, J., Beheshti, A., Sheng, Q. Z., Foo, J., Haghighi, V., Hanif, A., & … (2024). A comprehensive survey on graph summarization with graph neural networks. IEEE Transactions on Artificial Intelligence, 5(8), 3780–3800.

4. Soltani, B., Zhou, Y., Haghighi, V., & Lui, J. (2023). A survey of federated evaluation in federated learning. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI).

5. Shabani, N., Beheshti, A., Jolfaei, A., Wu, J., Haghighi, V., Najafabadi, M. K., & Foo, J. (2024). Attention-based graph summarization for large-scale information retrieval. IEEE Transactions on Consumer Electronics, 70(3), 6224–6235.

Amel Abderrahmane | Computer Science | Best Review Article Award

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Dr. Amel Abderrahmane | Computer Science | Best Review Article Award

Professor at Batna University | Algeria

Dr. Amel Abderrahmane  is a dedicated researcher and educator specializing in computer networks, with a strong academic and professional background in software-defined networking (SDN) and the Internet of Things (IoT). Currently pursuing a PhD in Sécurité des systèmes informatiques et réseaux at Batna University, Algeria, he focuses on advancing modern network infrastructures by solving critical control placement challenges. His academic journey began with a Bachelor’s degree in Computer Science from the University Ferhat Abbas Setif, where he graduated , followed by a Master’s degree in Distributed Systems and Networking at Batna University, earning first-in-class distinction. Alongside his research, he has been serving as a Temporary Professor at Batna University, where he teaches and supervises students in computer science. Abderrahmane has contributed valuable publications to international journals, including IEEE Access, highlighting his commitment to advancing innovative solutions in networking technologies.

Professional Profile

Scopus Profile

Education 

Dr. Amel Abderrahmane  has pursued a distinguished academic path in computer science and networking. He began his studies at the University Ferhat Abbas Setif, Algeria, earning a Bachelor’s degree in Computer Science. His performance and dedication laid a strong foundation for advanced research in distributed computing and networking. He completed his Master’s degree in Distributed Systems and Networking at Batna University, Algeria, where he ranked first in class, demonstrating both academic excellence and technical mastery. Building upon this achievement, he embarked on a PhD in Sécurité des systèmes informatiques et réseaux at Batna University , where his research focuses on optimizing SDN and IoT networks. His education has been marked by a blend of theoretical knowledge and practical applications, equipping him with expertise in network security, control placement, and performance optimization. This progression reflects his commitment to addressing real-world challenges in modern computer networks.

Experience 

Dr. Amel Abderrahmane has been serving as a Temporary Professor in the Computer Science Department at Batna University. In this role, he has gained significant teaching and mentoring experience, instructing undergraduate students in core computer science subjects while also guiding them in research-oriented projects. His responsibilities extend to supervising students in applied research related to SDN controllers, IoT platforms, and network management. Beyond classroom instruction, Abderrahmane actively contributes to collaborative research activities, assisting in projects that address optimization and security challenges in next-generation networks. His dual role as a researcher and educator allows him to integrate cutting-edge research insights into his teaching, creating an engaging learning environment. His academic contributions are reinforced by publications in respected international journals, including IEEE Access, which reflect the practical impact of his work. This experience underscores his ability to combine teaching excellence with meaningful research contributions in computer networking.

Research Interest

Dr. Amel Abderrahmane  research lies at the intersection of software-defined networking (SDN) and the Internet of Things (IoT), with a primary focus on optimizing control placement within distributed network environments. He is particularly interested in addressing scalability, efficiency, and reliability challenges to ensure seamless communication and effective resource allocation in modern infrastructures. His work emphasizes designing innovative frameworks and algorithms that enhance both performance and security in complex SDN-IoT ecosystems. Abderrahmane’s current research also explores how graph-theoretical methods and clustering techniques, such as the Louvain algorithm and betweenness-centrality metrics, can improve controller placement strategies for better network resilience. By tackling these critical issues, his contributions aim to support the development of smart, adaptive, and secure networking systems that are essential for emerging technologies, including smart cities, industrial IoT, and cloud-edge integration. His vision is to create sustainable solutions that can advance the next generation of intelligent and interconnected networks.

Award and Honor

Dr. Amel Abderrahmane  has consistently demonstrated excellence, earning recognition for his outstanding performance. During his Master’s studies in Distributed Systems and Networking at Batna University, he graduated first in class, a distinction that reflects his exceptional technical knowledge, analytical skills, and commitment to research. This achievement set the foundation for his doctoral studies and positioned him as a promising researcher in the fields of SDN and IoT. His scholarly contributions have been further acknowledged through publications in prestigious outlets such as the International Journal of Networked and Distributed Computing and IEEE Access. The acceptance of his research in these high-impact journals highlights the relevance and innovation of his work, serving as a testament to his academic accomplishments. While still at an early stage of his career, Abderrahmane’s academic honors and growing publication record mark him as a rising scholar within the international research community.

Research Skill

Dr. Amel Abderrahmane possesses a diverse set of research skills that strengthen his contributions to SDN and IoT studies. He is proficient in multiple programming languages, including Python, Java, C++, and C#, which enable him to implement and test advanced algorithms for network optimization. His technical expertise also extends to web programming, providing him with the versatility to design and integrate network applications. In addition, he is skilled in using SDN controllers and IoT platforms, tools essential for simulating and evaluating network performance in real-world conditions. Abderrahmane demonstrates strong analytical skills, particularly in applying graph-based techniques and clustering algorithms to solve controller placement challenges. His multilingual abilities in Arabic, French, and English further enhance his capacity to engage with international collaborations and research dissemination. Combined, these skills reflect a balanced profile of theoretical knowledge, practical application, and cross-cultural communication, enabling him to contribute effectively to global research networks.

Publication Top Note

Title:  A Survey of Controller Placement Problem in SDN-IoT Network
Authors: Amel Abderrahmane, Hamza Drid, and Amel Behaz SpringerLink
Journal: International Journal of Networked and Distributed Computing
Citation : 7

Conclusion

Dr. Amel Abderrahmane survey on the Controller Placement Problem (CPP) in SDN-IoT networks highlights its central role in ensuring scalability, reliability, and efficiency in next-generation infrastructures. By examining existing approaches, it becomes evident that optimal controller placement is a multidimensional challenge influenced by latency, fault tolerance, load balancing, and energy efficiency. Traditional models provide a foundation, but they often struggle to adapt to the heterogeneity and dynamic nature of IoT environments. Recent advancements, such as graph-based techniques and clustering algorithms, demonstrate promising results in improving performance and resilience. However, no single method universally addresses all requirements, indicating the need for hybrid and adaptive solutions. Future research should focus on intelligent, AI-driven strategies that can dynamically adjust placement decisions in real time, considering both network conditions and application demands. Ultimately, solving CPP will significantly enhance the effectiveness of SDN-IoT networks, enabling more reliable and sustainable digital ecosystems.

LI Ma | Computer Science | Best Researcher Award

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Prof. LI Ma | Computer Science | Best Researcher Award

Professor at North China University of Technology Beijing, China

Prof. Li Ma  is a distinguished Professor and Dean of the School of Information Science at North China University of Technology, Beijing.  He also serves as a Doctoral Supervisor at Beijing University of Technology. With over three decades of academic and research contributions, Prof. Ma has authored and co-authored more than  journal and conference papers.  His scholarly journey began with a B.S. degree from Beijing Institute of Technology , followed by an M.S. from North University of China , and a Ph.D. from Beijing Institute of Technology . His research spans artificial intelligence, advanced computing, and physical oceanography, integrating interdisciplinary approaches to solve complex challenges.  A recognized leader, he is a Distinguished Member of the China Computer Federation (CCF), and an active member of IoT committees, IEEE-CS, and ACM. Prof. Ma continues to guide innovation while mentoring the next generation of researchers.

Professional Profile

Scopus Profile

Education 

Prof. Li Ma academic foundation is built upon rigorous training at prestigious Chinese institutions.  He earned his B.S. degree from Beijing Institute of Technology, one of China’s leading centers for science and engineering education.  He then pursued his M.S. degree at North University of China, Shaanxi, where he further specialized in computational and information sciences. With a growing passion for advancing artificial intelligence and computing technologies, he returned to Beijing Institute of Technology for doctoral studies, successfully completing his Ph.D. During his doctoral journey, he focused on exploring advanced models and algorithms, setting the stage for his prolific academic career. This educational pathway provided him with a strong balance of theoretical expertise and applied research training, enabling him to later contribute significantly to AI, computational sciences, and interdisciplinary applications in fields such as physical oceanography.

Experience 

Prof. Li Ma professional journey reflects leadership in both academia and research.  Currently, he serves as Professor and Dean of the School of Information Science at North China University of Technology, Beijing, where he oversees academic development, curriculum innovation, and interdisciplinary research.  Additionally, he holds the position of Doctoral Supervisor at Beijing University of Technology, mentoring Ph.D. candidates and guiding cutting-edge projects in artificial intelligence and advanced computing.  His contributions extend beyond teaching and supervision he has authored over research papers, shaping knowledge in AI algorithms, model optimization, and computational sciences.  As an influential figure, he also leads academic innovation teams across Beijing municipal universities, fostering collaborative networks.  Beyond his institutional roles, he actively participates in professional societies such as CCF, IEEE-CS, and ACM, strengthening global research ties. With decades of experience, Prof. Ma continues to bridge science, technology, and education for future advancements.

Research Interest 

Prof. Li Ma research interests are diverse and interdisciplinary, bridging computer science with applied fields.  His core expertise lies in artificial intelligence technology, particularly in developing robust models that enhance accuracy, allocation algorithms, attention mechanisms, and bounding box optimization.  He also explores deep learning applications, focusing on classification head architectures, loss functions, and anchor boxes within image recognition systems, including real-world datasets like COCO.  Another dimension of his research extends to complex computational dependencies and buffer space optimization, enhancing the efficiency of AI-driven systems.  Uniquely, Prof. Ma also applies computational models to physical oceanography, integrating AI with environmental and marine sciences. This interdisciplinary approach highlights his vision of combining data science, machine learning, and computational modeling to solve critical problems across science and technology. His work reflects innovation at the crossroads of advanced computing, AI research, and environmental applications.

Award and Honor

Prof. Li Ma has earned recognition as a leading scholar and academic leader.  He is a Distinguished Member of the China Computer Federation (CCF), a prestigious acknowledgment of his contributions to computer science research and development in China. He is also an active member of IEEE Computer Society and ACM, which reflects his international engagement and commitment to advancing global standards in computing and AI.  Beyond memberships, Prof. Ma leads an Academic Innovation Team supported by Beijing Municipal Colleges and Universities, showcasing his leadership in fostering research excellence and interdisciplinary collaboration.  His roles as Dean and Doctoral Supervisor further illustrate the trust placed in him to shape future researchers and contribute to academic policy.  While specific individual awards were not listed in the available record, his professional honors demonstrate recognition at both national and international levels in AI, computing, and interdisciplinary science.

Research Skill

Prof. Li Ma possesses a broad range of advanced research skills that position him at the forefront of computer science and AI.  His expertise includes algorithm design and optimization, focusing on allocation methods, classification models, and bounding box refinement for image recognition tasks. He has strong command over deep learning frameworks, applying attention mechanisms, anchor boxes, and classification head models to improve accuracy and system performance. Additionally, his skills in large-scale dataset utilization (e.g., COCO dataset) enable him to test, validate, and refine machine learning models effectively.  His computational skills extend into buffer space optimization and handling complex dependencies, key for enhancing efficiency in AI-driven environments. Beyond technical areas, he demonstrates leadership in interdisciplinary applications, especially in using AI for physical oceanography and environmental modeling. These skills, combined with over publications, reflect his ability to merge theory with impactful real-world applications.

Publication Top Notes

Title: FedECP: Enhancing global collaboration and local personalization for personalized federated learning
Journal: Knowledge Based Systems
Year: 2025

Title: A verifiable EVM-based cross-language smart contract implementation scheme for matrix calculation
Journal: Digital Communications and Networks
Year: 2025

Title: Construction of Low-latency Artificial Intelligence of Things for Marine Meteorological Forecasting
Journal: Tien Tzu Hsueh Pao Acta Electronica Sinica
Year: 2025

Title: Blockchain-Based Trust Model for Inter-Domain Routing
Journal: Computers Materials and Continua
Year: 2025

Title: Multivariate Short-Term Marine Meteorological Prediction Model
Journal: IEEE Transactions on Geoscience and Remote Sensing
Year: 2025

Title: A trusted IoT data sharing method based on secure multi-party computation
Journal: Journal of Cloud Computing
Year: 2024

Title: Obstacle Avoidance Method Using DQN to Classify Obstacles in Unmanned Driving
Journal: Jisuanji Gongcheng (Computer Engineering)
Year: 2024

Title: A quantum artificial bee colony algorithm based on quantum walk for the 0-1 knapsack problem
Journal: Physica Scripta
Year: 2024

Title: MIMA: Multi-Feature Interaction Meta-Path Aggregation Heterogeneous Graph Neural Network for Recommendations
Journal: Future Internet
Year: 2024

Conclusion

Prof. Li Ma is an accomplished scholar in computer science, artificial intelligence, and computational technologies, currently serving as Dean of the School of Information Science at North China University of Technology and Doctoral Supervisor at Beijing University of Technology. With over  publications and  citations, his research contributions span AI model optimization, federated learning, blockchain systems, IoT, marine meteorological forecasting, and quantum-inspired algorithms.

Alexios Kaponis | Computer Science | Excellence in Research

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Mr. Alexios Kaponis | Computer Science | Excellence in Research

PhD Candidate,Ionian University , Greece

Alexios Kaponis is a promising researcher with a robust portfolio of work in AI and digital marketing, focused on both technical innovation and ethical implications. His research output, coupled with hands-on project experience and a solid educational foundation, positions him as a dedicated and impactful researcher. He continues to develop expertise that addresses both theoretical and applied challenges in computer science.

Professional Profile

🎓 Educational Background

Alexios Kaponis was born in Patras on August 6, 1987. He earned his diploma in Cultural Management from the Department of Management of Cultural Environment and New Technologies at the University of Ioannina in 2009. Later, he obtained a master’s degree in Technologies and Management from the Department of Information and Communication Systems Engineering at the University of the Aegean in 2017. Currently, Alexios is pursuing a doctoral degree in Computer Science at the University of the Ionian Islands. His PhD research focuses on “Data analysis in digital marketing using machine learning and artificial intelligence techniques, business analysis, practices, and ethical dimensions in e-commerce.”

🧑‍🏫 Professional Experience

Alexios currently works as an Intelligent Software Solutions expert at the National Research Centre for Physical Sciences (NCRS) “Demokritos.” Since April 2024, he has been involved in the WP2 Data Inspection and Generation and WP5 Trustworthy Efficiency & Performance Assessment Framework projects, focusing on advanced machine learning and AI tools to improve risk prediction and fraud detection. His responsibilities include proposing new intelligence tool developments, conducting data analysis, and leveraging big data and cloud-based technologies.

🔬 Research Focus

Alexios’s research primarily centers on the application of machine learning and AI techniques in digital marketing, with a strong emphasis on ethical and legal dimensions in e-commerce. He investigates the use of natural language processing and large-scale data mining for business intelligence and enhanced customer engagement. His ongoing doctoral work explores innovative data analysis methodologies to support decision-making in marketing strategies. Furthermore, he contributes to projects aiming to improve AI reliability and trustworthiness in practical applications, such as fraud detection and chatbot development.

🛠️ Skills and Expertise

Alexios possesses strong expertise in big data, data analytics, artificial intelligence, data management, and cloud computing technologies. He has hands-on experience with machine learning, natural language processing, semantic web technologies, and digital marketing analytics. Additionally, Alexios is proficient in web development tools such as Joomla and WordPress and skilled in Google Analytics. He is fluent in Greek and highly proficient in English, complemented by a computer diploma certified by the University of Ioannina.

🏅 Awards & Honours

Alexios was distinguished by the General Secretariat for Lifelong Learning for his successful completion of a 25-hour seminar dedicated to training teachers in vocational adult education. His active participation as an examiner in national qualification certification examinations highlights his commitment to professional excellence in IT education. He has also presented and published multiple papers at prestigious international conferences, reflecting recognition of his research contributions in artificial intelligence, digital marketing, and assistive technologies.

Publication Top Notes

  1. Assist of AI in a Smart Learning Environment

    • Authors: K.C. Sofianos, Michalis Stefanidakis, Alexios Kaponis, Linas Bukauskas

    • Year: 2024

    • Citation count: 1

  2. Data Analysis in Digital Marketing using Machine Learning and Artificial Intelligence Techniques, Ethical and Legal Dimensions, State of the Art

    • Author: Alexios Kaponis, M. Maragoudakis

    • Year: 2022

    • Citation count: (Not provided, please add if known)

  3. Case Study Analysis of Medical and Pharmaceutical Chatbots in Digital Marketing and Proposal to Create a Reliable Chatbot with Summary Extraction Based on Users’ Keywords

    • Authors: Alexios S. Kaponis, Alexios A. Kaponis, Manolis Maragoudakis

    • Year: 2023

    • Citation count: (Not provided)

  4. Enhancing Disease Diagnosis: A CNN-Based Approach for Automated White Blood Cell Classification

    • Authors: Athanasios Kanavos, Orestis Papadimitriou, Alexios Kaponis, Manolis Maragoudakis

    • Year: 2023

    • Citation count: (Not provided)

Conclusion

Given his achievements and ongoing contributions, Alexios Kaponis is a fitting candidate for the Excellence in Research Award. Recognizing his work would not only honor his past accomplishments but also encourage further advancements in AI-driven research that balances innovation with ethical responsibility. With continued focus on increasing research impact and leadership, Alexios is well poised for future excellence in his field.

Jaecheol Ha | Computer Science | Best Researcher Award

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Prof .  Jaecheol Ha | Computer Science | Best Researcher Award

Professor at Hoseo University , South Korea

Professor Jaecheol Ha is a seasoned academic with a Ph.D. in Electronics Engineering from Kyungpook National University and over 25 years of research and teaching experience. Currently a full professor at Hoseo University, he has also held academic positions at Korea Nazarene University and was a visiting researcher at Purdue University, USA. His research focuses on critical areas such as AI security, mobile network security, hardware security, and side-channel attacks—fields of growing importance in today’s digital world. As the honorary president of the Korea Institute of Information and Cryptography (KIISC), he demonstrates recognized leadership in the cybersecurity research community. While his academic background and research interests are highly relevant, more information on his publication record, research impact, and mentorship contributions would further strengthen his case. Nonetheless, based on the available information, Professor Ha presents a strong and credible profile for the Best Researcher Award, particularly in the domain of cybersecurity.

Professional Profile 

Education🎓

Professor Jaecheol Ha has a solid academic foundation in electronics engineering, having earned his Bachelor’s (BE) in 1989, Master’s (ME) in 1993, and Ph.D. in 1998 from Kyungpook National University in the Republic of Korea. His progression through all three degrees at a single institution reflects a consistent and focused commitment to his field of study. Kyungpook National University is recognized for its strong engineering programs, providing him with a rigorous education and research training environment. His doctoral studies likely laid the groundwork for his later specialization in areas such as AI security and hardware-based cryptographic methods. This strong educational background has supported his successful academic career, enabling him to contribute meaningfully to research and teaching. His education not only equipped him with deep technical knowledge but also prepared him to take on leadership roles in academic and research institutions, both domestically and internationally.

Professional Experience📝

Professor Jaecheol Ha has extensive professional experience spanning over two decades in academia and research. He is currently a full professor in the Division of Computer Engineering at Hoseo University in Asan, Republic of Korea, where he plays a key role in teaching and research. Prior to this, from 1998 to 2006, he served as a professor in the Department of Information and Communication at Korea Nazarene University in Cheonan. His academic career reflects a strong commitment to education and research in the fields of computer engineering and cybersecurity. In 2014, he broadened his international experience by working as a visiting researcher at Purdue University in the United States, further enhancing his global academic perspective. In addition to his teaching and research roles, he currently serves as the honorary president of the Korea Institute of Information and Cryptography (KIISC), a position that highlights his leadership and influence in the Korean cybersecurity research community.

Research Interest🔎

Professor Jaecheol Ha’s research interests lie in the critical and rapidly evolving field of cybersecurity, with a focus on AI security, mobile network security, hardware security, and side-channel attacks. His work addresses some of the most pressing challenges in digital security, particularly as emerging technologies like artificial intelligence and mobile communication continue to expand. By exploring vulnerabilities in hardware and communication systems, as well as developing methods to protect against side-channel attacks, his research contributes to building more resilient and secure digital infrastructures. His interest in AI security reflects a forward-thinking approach, recognizing the increasing integration of AI in sensitive systems and the corresponding need for robust protective measures. Through his work, Professor Ha seeks to bridge theoretical understanding with practical applications, providing solutions that can be implemented in real-world systems. His research not only supports academic advancement but also contributes to national and global efforts to strengthen cybersecurity.

Award and Honor🏆

Professor Jaecheol Ha has received recognition for his contributions to the field of cybersecurity through his leadership role as the honorary president of the Korea Institute of Information and Cryptography (KIISC). This prestigious position reflects his respected status within the academic and research communities, as well as his long-standing commitment to advancing knowledge in information security. While specific awards or honors are not listed, his appointment to such a significant role within a national institute suggests a high level of trust and acknowledgment by his peers. It highlights his influence in shaping research directions and policies in cryptography and cybersecurity in Korea. His professional journey, including his international research collaboration at Purdue University, also indicates recognition of his expertise beyond national boundaries. These honors affirm his impact as a leader and researcher, underscoring his suitability for further accolades such as the Best Researcher Award in his field of specialization.

Research Skill🔬

Professor Jaecheol Ha possesses a wide range of research skills that are crucial for tackling complex problems in the field of cybersecurity. His expertise spans several critical areas, including AI security, mobile network security, hardware security, and side-channel attacks. With a deep understanding of both theoretical and practical aspects of these fields, he is skilled at identifying vulnerabilities in systems and developing innovative solutions to mitigate them. His ability to bridge the gap between cutting-edge research and real-world applications demonstrates his strong problem-solving capabilities. Additionally, his international research experience, particularly as a visiting researcher at Purdue University, indicates a high level of adaptability and collaboration in global research environments. His leadership as honorary president of the Korea Institute of Information and Cryptography (KIISC) further highlights his ability to mentor, guide, and foster collaboration among researchers, strengthening his research skills in both individual and team-based contexts.

Conclusion💡

Professor Jaecheol Ha appears to be a well-qualified and experienced researcher with a strong focus on cybersecurity, leadership experience, and international exposure. These factors support his eligibility for a Best Researcher Award, especially if the focus is on long-term contribution and domain impact.

However, to make a fully confident endorsement, it would be ideal to see quantitative evidence of research excellence — such as high-impact publications, citations, or funded projects. If such data exists and supports the narrative, then he is a strong and suitable candidate for this award.

Publications Top Noted✍

  1. Title: SSIM-Based Autoencoder Modeling to Defeat Adversarial Patch Attacks
    Authors: Seungyeol Lee, Seongwoo Hong, Gwangyeol Kim, Jaecheol Ha
    Year: 2024
    Citations: 1
  2. Title: Implementation of Disassembler on Microcontroller Using Side-Channel Power Consumption Leakage
    Authors: Daehyeon Bae, Jaecheol Ha
    Year: 2022
    Citations: 6
  3. Title: Deep Learning-based Attacks on Masked AES Implementation
    Authors: Daehyeon Bae, Jongbae Hwang, Jaecheol Ha
    Year: 2022
    Citations: 1
  4. Title: Performance Metric for Differential Deep Learning Analysis
    Authors: Daehyeon Bae, Jaecheol Ha
    Year: 2021
    Citations: 26