Dugki Min | Machine Learning and AI Applications | Best Researcher Award

Prof Dr. Dugki Min | Machine Learning and AI Applications | Best Researcher Award

Konkuk University | South Korea

Prof. Dr. Dugki Min is a distinguished academic and thought leader in the field of computer science and artificial intelligence. Currently serving as a Full Professor at the Department of Computer Science and Engineering, College of Engineering, and Department Head of Artificial Intelligence at the General Graduate School of Konkuk University, Seoul, South Korea, he has dedicated nearly three decades to education, research, and innovation. His multidisciplinary expertise, encompassing software engineering, intelligent systems, distributed computing, and AI-based smart city applications, positions him as a pioneer in shaping Korea’s digital transformation and global technology collaborations.

Professional Profiles

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Education

Prof. Min holds a Ph.D. and M.S. in Computer Science from Michigan State University, USA, where he developed a strong foundation in systems architecture and distributed computing. He completed his undergraduate studies in Industrial Engineering at Korea University. His education spans both technical and applied domains, enabling a balanced approach to both theoretical advancements and practical innovations.

Experience

Since joining Konkuk University in 1995, Prof. Min has held several leadership roles, including Research Director of the Distributed Multimedia Lab and Department Head for multiple programs in both the College of Engineering and the General Graduate School. His international academic footprint includes appointments as Visiting Professor at Pacific State University, USA, and Vanderbilt University. Beyond academia, he has significantly influenced industry practices through advisory roles at Samsung Electronics, national IT committees, and standardization bodies such as OASIS and the National Information Society Agency. His longstanding contributions to Korea’s software and simulation societies have solidified his reputation as a key figure in technological policymaking and industry collaboration.

Research Interest

Prof. Min’s research focuses on secure, intelligent, and scalable computing systems. His work spans artificial intelligence, distributed multimedia systems, digital twin technologies, edge-cloud computing, disaster-resilient smart cities, and cyber-physical systems. He leads major government-funded projects including AI-based public safety frameworks and digital twin applications for smart urban air mobility (UAM). His current projects emphasize the convergence of AI, bio-inspired frameworks, and real-time urban analytics to develop resilient, adaptive systems for modern cities. He has also delved into IPFS, blockchain, and biometric authentication, driving forward novel approaches in cybersecurity and information infrastructure.

Awards and Recognition

Prof. Min’s contributions have been recognized through numerous research grants and leadership roles in prestigious international conferences, including the International Conference on IT Promotion in Asia and the International Semantic Web Conference. His role as Program Chair and Steering Committee Member across multiple academic and government platforms highlights his global impact. Additionally, his collaborations with government ministries such as the Ministry of Science and ICT have resulted in pivotal national R&D programs, affirming his status as a trusted thought leader in AI and future mobility solutions.

Publications

Enhancing data harvesting systems: Performance quantification of Cloud–Edge-sensor networks using queueing theory

Authors: Jose Wanderlei Rocha, Eder Gomes, Vandirleya Barbosa, Arthur Sabino, Luiz Nelson Lima, Gustavo Callou, Francisco Airton Silva, Eunmi Choi, Tuan Anh Nguyen, Dugki Min et al.
Journal: ICT Express
Year: 2025

DDS-P: Stochastic models based performance of IoT disaster detection systems across multiple geographic areas

Authors: Israel Araújo, Luis Guilherme Silva, Carlos Brito, Dugki Min, Jae-Woo Lee, Tuan Anh Nguyen, Erico Leão, Francisco A. Silva
Journal: ICT Express
Year: 2025

Transactional dynamics in hyperledger fabric: A stochastic modeling and performance evaluation of permissioned blockchains

Authors: Carlos Melo, Glauber Gonçalves, Francisco Airton Silva, Iure Fé, Ericksulino Moura, André Soares, Eunmi Choi, Dugki Min, Jae-Woo Lee, Tuan Anh Nguyen
Journal: ICT Express
Year: 2025

Multi-head Fusion-based Actor-Critic Deep Reinforcement Learning with Memory Contextualisation for End-to-End Autonomous Navigation

Authors: Seunghyeop Nam, Tuan Anh Nguyen, Eunmi Choi, Dugki Min
Journal: TechRxiv (Preprint)
Year: 2025

Aerial computing: Enhancing mobile cloud computing with unmanned aerial vehicles as data bridges—A Markov chain based dependability quantification

Authors: Francisco A. Silva, Iure Fé, Carlos Brito, G. Araujo, L. Feitosa, Tuan Anh Nguyen, K. Jeon, J.-W. Lee, Dugki Min, Eunmi Choi
Journal: ICT Express
Year: 2024

Deep learning methods for high-level control using object tracking

Authors: Kanmani P., Yuvaraj N., Karthic S., Sri Preethaa K.R., Dugki Min
Journal: Book Chapter in Urban Air Mobility: Intelligent, Safe and Sustainable Systems for Future Transportation
Year: 2024

Efficient Strategies for Unmanned Aerial Vehicle Flights: Analyzing Battery Life and Operational Performance in Delivery Services using Stochastic Models

Authors: Francisco A. Silva, Vandirleya Barbosa, Luiz Nelson Lima, Arthur Sabino, Paulo Rego, Luciano F. Bittencourt, J. Lee, Dugki Min, Tuan Anh Nguyen
Journal: IEEE Access
Year: 2024

Energy Consumption in Microservices Architectures: A Systematic Literature Review

Authors: Gabriel Araújo, Vandirleya Barbosa, Luiz Nelson Lima, Arthur Sabino, Carlos Brito, Iure Fé, Paulo Rego, Eunmi Choi, Dugki Min, Tuan Anh Nguyen et al.
Journal: IEEE Access
Year: 2024

Conclusion

Prof. Dr. Dugki Min exemplifies academic excellence, innovative research, and impactful leadership in computer science and artificial intelligence. His ability to merge theory with application has led to the creation of intelligent systems that address real-world challenges—from traffic prediction and public safety to accessibility and secure computing. With a prolific record of publications, patents, and technology transfer initiatives, he continues to push the boundaries of smart system design and AI integration in urban and industrial ecosystems. His forward-thinking vision, combined with strong collaboration across academia, government, and industry, ensures his enduring influence in Korea and beyond.

Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Mr. Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Jamia Millia Islamia | India

Author Profile

Google Scholar

Mr. Mohammad Zahid

Junior Research Fellow | Ph.D. Scholar in Computer Science | Cybersecurity & AI Researcher

Summary

Mohammad Zahid is a motivated and research-focused computer science professional currently pursuing a Ph.D. in Computer Science at Jamia Millia Islamia, New Delhi. He is working as a Junior Research Fellow (JRF) with a specialization in IoT security, machine learning, deep learning, and federated learning. With strong analytical and technical skills, he is actively engaged in AI-driven cybersecurity research, aiming to develop intelligent systems for threat detection. Zahid is passionate about contributing to innovative and interdisciplinary projects in both academia and the tech industry.

Education

Mr. Zahid is currently enrolled in a Ph.D. program at Jamia Millia Islamia (Central University), New Delhi, with a research focus in computer science and AI. He holds a Master of Computer Applications (MCA) from Maulana Azad National Urdu University (MANUU), Hyderabad, where he graduated with an excellent academic record (87.6%). He also completed a Bachelor of Science (Hons) in Chemistry, Mathematics, and Physics from Aligarh Muslim University (AMU), Aligarh.

Professional Experience

As a Junior Research Fellow, Mr. Zahid is engaged in cutting-edge research related to cybersecurity and artificial intelligence. During his postgraduate studies, he developed a web-based fraud detection system that utilized machine learning algorithms to identify and visualize suspicious banking transactions. His hands-on experience includes technologies such as Java, MySQL, JavaScript, and HTML/CSS, with a strong foundation in data preprocessing and anomaly detection.

Research Interests

Mr. Zahid’s research interests span across IoT security, federated learning, machine learning, and deep learning. His current Ph.D. research is centered on AI-based cybersecurity frameworks, especially for detecting and mitigating threats in decentralized and IoT-based environments. He is particularly interested in applying federated learning models to preserve data privacy while improving detection efficiency in real-world systems.

Honors and Awards

Mr. Zahid was awarded the UGC Junior Research Fellowship (JRF) in Computer Science by the National Testing Agency (NTA) in March 2022, recognizing him among the top national-level researchers eligible for academic and research roles across Indian universities. He also received the Merit-cum-Means Scholarship for Professional Courses from the Ministry of Minority Affairs, Government of India, during his MCA studies (2018–2021), in acknowledgment of his academic performance and financial need.

Publications

 Empowering IoT Networks

Author: M Zahid, TS Bharati

Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Enhancing Cybersecurity in IoT Systems: A Hybrid Deep Learning Approach for Real-Time Attack Detection

Author: M Zahid, TS Bharati
Journal: Discover Internet of Things, Volume 5(1), Page 73
Year: 2025

 Comprehensive Review of IoT Attack Detection Using Machine Learning and Deep Learning Techniques

Author: M Zahid, TS Bharati
Journal: 2024 Second International Conference on Advanced Computing & Communication
Year: 2024

Empowering IoT Networks: A Study on Machine Learning and Deep Learning for DDoS Attack

Author: M Zahid, TS Bharati
Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Zlatko Kopecki – Innovation in Data Analysis – Best Researcher Award 

Dr. Zlatko Kopecki - Innovation in Data Analysis - Best Researcher Award 

University of South Australia - Australia

Author Profile

Early Academic Pursuits

Dr. Zlatko Kopecki's academic journey began with his role as a Technical Officer in Histopathology at Clinpath Laboratories from 2003 to 2005, followed by a position as a Medical Scientist in Histopathology at Adelaide Pathology Partners from 2005 to 2011. During this period, he honed his skills in laboratory medicine, culminating in earning the Terumo Prize for Excellence in Laboratory Medicine with Honours from the University of South Australia (UniSA) in 2007. His dedication to his field was further recognized with a Dean’s Commendation for the quality of his Ph.D. thesis at the University of Adelaide in 2011.

Professional Endeavors

Dr. Kopecki's professional career is marked by several notable appointments. From 2010 to 2012, he served as a Research Officer at the Women’s and Children’s Hospital, where he began to establish his research credentials. His trajectory continued with a National Health and Medical Research Council (NHMRC) Early Career Researcher (ECR) Fellowship at UniSA from 2012 to 2015, during which he also held an honorary research fellowship at Queen Mary University of London. He progressed to the role of Senior Research Fellow at UniSA's Future Industries Institute (FII) from 2015 to 2021. His international engagements included visiting research fellowships at the University of Freiburg (2010), University of Lübeck (2017), and the University of Bath (2020).

Contributions and Research Focus

Dr. Kopecki's research has consistently focused on innovative approaches to wound management and therapy for rare skin diseases, particularly Epidermolysis Bullosa (EB). He has pioneered the development of biofilm-disrupting technologies and stimuli-responsive wound dressings, as well as antimicrobial photodynamic therapy (aPDT). His work also includes the development of antiseptic wound cleansers, medicated hydrogels, and antimicrobial materials for treating infections. His research employs various animal models to answer critical questions about wound infection and skin diseases, contributing significantly to product development and commercialization pathways.

Accolades and Recognition

Dr. Kopecki's contributions to research and patient advocacy have been recognized with numerous awards. Notable among these are the Young Investigator of the Year Award from the Australasian Wound & Tissue Repair Society (AWTRS) in 2016 and the Tall Poppy Award for outstanding scientific achievements in South Australia in 2017. His innovative research has also earned him prestigious grants, including multiple NHMRC Ideas Grants and the Alexander von Humboldt Fellowship for Experienced Researchers (2024-2026).

Impact and Influence

Dr. Kopecki's influence extends beyond his research to impactful patient advocacy. Since 2009, he has been actively involved with DEBRA (an international patient support organization for those affected by EB), where he has held various leadership positions. His efforts have led to significant initiatives, such as the National EB Dressing Scheme in Australia and the In Home Nurse Program, which have greatly improved patient care. His work with DEBRA International during the Ukrainian conflict highlights his commitment to global patient advocacy, providing essential support to EB patients affected by the war.

Legacy and Future Contributions

Dr. Kopecki's legacy is marked by his dedication to improving the lives of those with rare skin diseases through both research and advocacy. His innovative approaches in developing new therapies and his active role in patient support programs have set new standards in the field. Looking forward, Dr. Kopecki aims to continue his pioneering research, focusing on translating his findings into clinical practice to benefit patients worldwide. His ongoing collaborations with industry partners and his involvement in global patient advocacy programs ensure that his work will continue to have a significant impact on the field of wound management and rare skin diseases.

Citations

A total of 1592 citations for his publications, demonstrating the impact and recognition of her research within the academic community.

Emad Alsusa – IoT (Internet of Things) Analytics – Best Researcher Award 

Prof. Emad Alsusa - IoT (Internet of Things) Analytics - Best Researcher Award 

Manchester University - United Kingdom

Author Profile

Early Academic Pursuits

Prof. Emad Alsusa embarked on his academic journey with a solid foundation in Electrical and Electronic Engineering, earning a Bachelor of Science degree with First Class Honors from Salford University in 1995, following which he pursued a PhD in Communication Engineering at the University of Bath, graduating in 2000. His academic excellence was evident even during his foundational year at Salford University, where he was recognized as the Top Student Award recipient.

Professional Endeavors

Alsusa's professional trajectory spans across prestigious institutions and significant roles in academia. He commenced his postdoctoral research at the University of Edinburgh in 2000 and later held various academic positions at the University of Manchester, progressively advancing from Lecturer to his current position as Reader in the Department of Electrical and Electronic Engineering. Noteworthy are his visiting appointments, particularly at Khalifa University in the UAE and the Technical University of Dresden, which reflect his international collaboration and recognition in the field.

Contributions and Research Focus On IoT (Internet of Things) Analytics

As a prolific researcher, Alsusa has made significant contributions to the field of Communication Engineering, evident through his extensive publication record, comprising over 296 peer-reviewed papers and three patents. His research focus encompasses diverse areas such as interference exploitation, adaptive cross-layer techniques for 5G communication systems, networking protocols for energy consumption reduction, and radar systems. Notably, his work on interference exploitation and novel interference management techniques has garnered international attention, leading to collaborations and recognition from esteemed institutions worldwide.

Accolades and Recognition

Prof. Alsusa's contributions have been recognized through numerous accolades, including Best Paper Awards at prestigious conferences such as the IEEE International Symposium on Networks, Computers & Communications, the IEEE International Conference on Wireless Communications & Networking, and the IEEE International Symposium on Power Line Communications. His leadership roles in professional societies, editorships of esteemed journals, and invitations to deliver talks and keynote addresses underscore his prominence in the academic community.

Impact and Influence

Beyond individual achievements, Alsusa has made a profound impact through his mentorship and supervision of numerous research students, with over 32 postgraduate researchers under his guidance. His leadership in research groups and consortia, as well as his involvement in organizing conferences and workshops, highlights his commitment to fostering collaborative research environments and advancing the field collectively.

The IoT Analytics Excellence Award recognizes outstanding achievements in leveraging data insights from connected smart devices to drive innovation and efficiency.

Legacy and Future Contributions

Prof. Emad Alsusa's legacy lies in his multifaceted contributions to Communication Engineering, spanning research, education, and professional service. His pioneering work, combined with his mentorship and leadership, has positioned him as a prominent figure in the field. Looking ahead, Alsusa continues to drive innovation and collaboration, aiming to address emerging challenges in wireless communication systems and leave a lasting impact on academia and industry.

Citations

  • Citations   4505
  • h-index       36
  • i10-index    105

Notable Publication

Zihao Mo – Neural network Neural network compression verification – Best Researcher Award 

Mr. Zihao Mo - Neural network Neural network compression verification - Best Researcher Award 

Augusta university - United States

Author Profile

Early Academic Pursuits

Mr. Zihao Mo embarked on his academic journey with a strong foundation in Electrical Engineering, earning a Bachelor's degree from the University of Missouri - Columbia and a Bachelor of Engineering degree from Southern China University of Technology in 2019. During his undergraduate studies, Mo demonstrated a keen interest in Information Engineering, laying the groundwork for his future endeavors in the realm of technology and computer science.

Driven by a passion for innovation, Mo pursued further academic excellence, obtaining a Master of Science in Electrical and Computer Engineering from the prestigious University of California, San Diego in 2021. Here, he delved deeper into machine learning and data analytics, expanding his skill set and theoretical understanding of these burgeoning fields.

Professional Endeavors

Mr. Mo's professional journey reflects his commitment to the advancement of technology, particularly in the domains of machine learning and data analysis. As a Test Specialist at Digitbridge, Inc., he played a pivotal role in the development and testing of software systems, utilizing his expertise in C# programming and SQL database management. His contributions were instrumental in enhancing the functionality and reliability of WMS, ERP, and Commerce Central systems, showcasing his proficiency in software engineering and quality assurance.

Moreover, Mo's involvement as a Program Committee Member for prestigious conferences such as AAAI and DATA underscores his dedication to academic and research-oriented pursuits. His role in reviewing papers and contributing to the organization of workshops demonstrates his engagement with the scholarly community and his commitment to staying abreast of the latest developments in his field.

Contributions and Research Focus On Neural network 

Mr. Mo's research endeavors have primarily revolved around machine learning, with a focus on neural network compression and optimization techniques. His publications in esteemed journals and conferences elucidate his innovative approaches to addressing challenges in model compression, quantization error computation, and hybrid automaton frameworks. By developing novel methodologies for enhancing the efficiency and effectiveness of convolutional and feedforward neural networks, Mo has made significant contributions to the advancement of machine learning algorithms and techniques.

Accolades and Recognition

Throughout his academic and professional journey, Mo has garnered recognition for his outstanding contributions to the field of computer science and engineering. His publications have been well-received within the academic community, earning him accolades and citations for his pioneering research in neural network compression and optimization. Additionally, his role as a Program Committee Member for prestigious conferences speaks to his expertise and reputation within the research community.

Impact and Influence

Mr. Mo's work has had a tangible impact on both academia and industry, with implications for the development of more efficient and scalable machine learning models. By devising innovative approaches to model compression and quantization, he has paved the way for advancements in edge computing, IoT devices, and other resource-constrained environments. His research has the potential to revolutionize the deployment and implementation of machine learning algorithms across various domains, ultimately benefiting society at large.

Legacy and Future Contributions

As Mo continues to pursue his PhD in Computer and Cyber Science at Augusta University, his research agenda remains focused on pushing the boundaries of machine learning and artificial intelligence. With a steadfast commitment to innovation and excellence, he aims to further explore the intersections of machine learning, cyber-physical systems, and software engineering. Through his ongoing contributions to research, academia, and industry, Mo is poised to leave a lasting legacy in the field of computer science, shaping the future of technology and driving impactful change in the years to come.

Notable Publication

DOI: 10.1016/j.ins.2024.120367

DOI: 10.48550/arXiv.2402.11737

DOI: 10.1109/ICIT58465.2023.10143141

DOI: 10.1109/ICIT58465.2023.10143031

 

Snehashis Majhi – Computer Vision – Best Researcher Award

Mr. Snehashis Majhi - Computer Vision - Best Researcher Award 

Institut National de Recherche en Informatique et en Automatique - France

Author Profile

Early Academic Pursuits

Mr. Snehashis Majhi embarked on his academic journey with a Bachelor of Technology in Computer Science and Engineering from the National Institute of Science and Technology, Berhampur, India. During this time, he delved into the realm of computer vision with his thesis titled "Design and Development of CBIR system using Classification Confidence," under the guidance of Dr. Jatindra Kumar Dash. This early exposure laid the foundation for his future endeavors in research and development.

Professional Endeavors

Mr. Majhi's professional journey commenced with an internship at INRIA, Sophia Antipolis Cedex BP 93, France, where he contributed to the development of a deep learning pipeline for human activity detection in smart home scenarios. This experience provided him with practical insights into real-world applications of deep learning technologies.

Following his internship, Majhi ventured into the field of glaucoma detection during his tenure as a Research Fellow at MNIT Jaipur, India. Here, he developed a deep convolutional neural network for detecting glaucoma diseases in fundus images, showcasing his versatility in applying deep learning techniques to healthcare domains.

Currently serving as a Research Scholar at INRIA Sophia Antipolis, France, Majhi's primary focus lies in developing human-scene centric video abnormality detection methods for smart-city surveillance systems. His research involves collaboration with Toyota Motor Europe and Woven Planet, demonstrating his ability to work on interdisciplinary projects with industry partners.

Contributions and Research Focus

Mr. Majhi's research contributions span various aspects of computer vision and deep learning. Noteworthy among his works is the development of the Human-Scene Network (HSN) and the Outlier-Embedded Cross Temporal Scale Transformer (OE-CTST) for video anomaly detection. These innovations address critical challenges in surveillance systems, showcasing Majhi's expertise in designing novel architectures and algorithms for complex tasks.

His research endeavors also encompass weakly-supervised learning techniques and optimization methods tailored for anomaly detection, underscoring his commitment to advancing the state-of-the-art in video analysis.

Accolades and Recognition

Mr. Majhi's contributions have been recognized through publications in reputable conferences and journals, including IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and International Conference on Neural Information Processing (ICONIP). His papers have received commendable rankings, reflecting the significance and impact of his research in the scientific community.

Impact and Influence

Through his research and academic pursuits, Mr. Majhi has made significant contributions to the fields of computer vision and machine learning. His innovative approaches to video anomaly detection have the potential to enhance surveillance systems' effectiveness, thereby contributing to the advancement of public safety and security measures.

Legacy and Future Contributions

Mr. Majhi's legacy lies in his pioneering work in video anomaly detection and deep learning applications. His research serves as a stepping stone for future advancements in smart-city surveillance, healthcare diagnostics, and beyond. As he continues his academic and professional journey, Majhi is poised to make further contributions to the field, driving innovation and addressing societal challenges through cutting-edge technologies.

Citations

  • Citations   97
  • h-index       5
  • i10-index   4

Notable Publication