KIISE Summer Conference 2025 – Undergraduate Paper Competition
한국정보기술학회 하계종합학술대회, 2025년 11월, 메종글래드 제주
© 2025 KIISE
Sunjun Hwang is an undergraduate researcher at the RAISE Lab, Yonsei University. His academic and research interests are centered on cutting-edge areas within computer science and quantum technology. He is particularly focused on quantum computing, exploring the principles and applications of quantum systems to solve complex computational problems. Additionally, Sunjun is deeply engaged in the study of quantum algorithms, investigating innovative approaches to designing algorithms that leverage quantum mechanics for enhanced computational efficiency. His interest in quantum artificial intelligence reflects his pursuit of integrating quantum computing techniques with AI methodologies to develop advanced intelligent systems. Furthermore, he is involved in artificial intelligence security, focusing on safeguarding AI systems against vulnerabilities. A key aspect of his work includes studying adversarial attacks, where he examines techniques used to manipulate or compromise AI models, aiming to develop robust defenses to enhance the security of intelligent systems.
Wooseok Wang is a member of the Software Department at Yonsei University. His academic and professional interests are focused on several key areas within the realm of computer science. He is particularly engaged in artificial intelligence, where he explores the development and application of intelligent systems to address complex computational challenges. Additionally, Wooseok has a strong interest in natural language processing, investigating techniques to enable machines to understand and generate human language for applications such as text analysis and conversational systems. His work also extends to data analysis, where he applies analytical methods to extract meaningful insights from large and complex datasets, contributing to data-driven decision-making processes.
Jaehoon Lee is a member of the Software Department at Yonsei University. His academic and professional interests are centered on advanced domains within computer science. He is particularly focused on artificial intelligence, where he investigates the development and application of intelligent systems to address sophisticated computational problems. Additionally, Jaehoon is engaged in data analysis, employing analytical techniques to derive meaningful insights from complex datasets to support informed decision-making. His work also includes federated learning, where he explores methods to train machine learning models across decentralized devices while preserving data privacy, contributing to the advancement of secure and collaborative AI systems.