Prof. Dr. Cheolhee Yoon, Korean National Police University, South Korea
Prof. Dr. Cheolhee Yoon is a distinguished researcher, professor, and ICT project manager with over 20 years of experience in artificial intelligence, digital forensics, and autonomous vehicle technology. His career spans academia, law enforcement, and high-level technology policy, with expertise in AI-driven autonomous driving, cybersecurity, and machine learning. He has held faculty positions at prestigious institutions like Yonsei University and Dongguk University, contributing to AI, deep learning, and programming. Dr. Yoon has also played a crucial role in enhancing cybercrime investigation capabilities internationally. His work integrates advanced AI algorithms to improve object recognition and real-time processing in autonomous systems. His contributions have led to groundbreaking advancements in AI-driven transportation and digital security.
Professional Profile 🌍
Scopus
Suitability for Best Scholar Award 🏆
Dr. Cheolhee Yoon is an exemplary candidate for the Best Scholar Award due to his extensive contributions to AI, digital forensics, and autonomous vehicle research. His work in applying Convolutional Neural Networks (CNNs) to improve real-time object detection has significantly advanced autonomous driving technology. As a professor and researcher, he has mentored students in AI, deep learning, and cybersecurity while actively participating in international collaborations. His hands-on experience in digital forensics and ICT systems in law enforcement has had a tangible impact on cybersecurity measures. With multiple research publications and contributions to AI-driven smart mobility, Dr. Yoon’s work aligns perfectly with the award’s vision of recognizing outstanding scholarly achievements.
Education 🎓
Dr. Yoon’s academic journey reflects his deep commitment to technological advancements. He earned his Bachelor’s degree in Software Information Systems from Hansung University, Seoul (2004), followed by a Master’s degree in Digital Forensics from Korea University (2016). His Ph.D. in Technology Policy from Yonsei University (2023) focused on AI-driven solutions for autonomous vehicles. His multilingual proficiency and international training in the UK and China further strengthened his research acumen. Additionally, his certifications in Cisco networking, cybersecurity, and Java programming have complemented his academic expertise, making him a well-rounded scholar in AI, digital security, and autonomous systems.
Experience 💼
Dr. Yoon has over two decades of professional experience spanning law enforcement, academia, and ICT systems. He served in the Korean Police Agency’s ICT team (2005–2007), troubleshooting and managing advanced systems. His tenure at the Korean National Police University (2017) involved leading AI-based digital forensic research. As a professor at Yonsei University and Dongguk University (2019–present), he has taught courses on AI, deep learning, machine learning, and programming. He also worked on international cybercrime training programs, enhancing digital investigation capabilities. His industry expertise includes IBM server management, cybersecurity frameworks, and AI applications in autonomous driving, contributing to real-world technological advancements.
Awards and Honors 🏅
Dr. Yoon has received multiple accolades for his contributions to AI and cybersecurity. He was honored for his work in AI-based digital forensic research and awarded for developing an AI-driven road safety system that improved real-time object recognition in autonomous driving. His recognition includes excellence awards from the Korean Police Agency for ICT innovations and multiple best paper awards at international AI and digital security conferences. His contributions to cybersecurity training programs in the Philippines and Bangladesh CID Center further showcase his global impact. His expertise in AI-driven law enforcement solutions has earned him widespread recognition in both academia and industry.
Research Focus 🔬
Dr. Yoon’s research spans AI applications in autonomous vehicles, digital forensics, and cybersecurity. His work on Convolutional Neural Networks (CNNs) has improved vehicle and pedestrian detection in self-driving cars. He has also contributed to AI-based forensic tools for cybercrime investigations, optimizing data retrieval and fraud detection algorithms. His interdisciplinary approach combines AI, cybersecurity, and digital forensics to enhance autonomous systems’ safety and reliability. His work also explores reinforcement learning models for vehicle decision-making and AI-driven solutions for real-time road condition analysis. His groundbreaking research continues to drive innovation in AI-powered transportation and digital security.
Publication Top Notes 📊
Leveraging Cyberattack News Tweets for Advanced Threat Detection and Classification using Ensemble of Deep Learning Models with Wolverine Optimization Algorithm