Ko seung hyoung

With a dual major in computer science and electrical engineering, I developed a strong passion for artificial intelligence during my undergraduate studies. After completing my bachelor's degree, I pursued a master's degree focused on optical imaging. During this time, I successfully built a single-pixel imaging setup that utilized compressed sensing techniques to acquire images efficiently without a 2D image sensor. Leveraging my programming skills and tools such as Raspberry Pi and DLP, I independently developed all necessary codes for image acquisition. Following the completion of my master's degree, I sought opportunities in the field of artificial intelligence and joined a satellite research institute. Here, I conducted groundbreaking research on enhancing low-resolution images using satellite imagery and artificial intelligence techniques like GANs. This innovative approach allowed me to transform inexpensive or freely available images into high-quality information comparable to that provided by expensive images. Currently pursuing a PhD, my focus lies in medical informatics. I have successfully undertaken several projects in this domain. Firstly, I researched classifying medical network data into normal or offensive categories using a classification model. This project has already been implemented in a real environment. Additionally, as an international researcher, I have studied the construction of an artificial intelligence model to predict cancer recurrence using pathology/CT images of liver transplant patients. Lastly, I am actively developing an artificial intelligence model that monitors real-time traffic data within the hospital network to detect any external attacks. With a strong academic background and expertise in artificial intelligence, I am well-equipped to contribute to cutting-edge advancements in the field while making a significant impact on healthcare and technology.

• Date of Birth: 10/26/92
• Gender: male

Paper

1. Performance Comparison of Machine Learning Algorithms for Network Traffic Security in Medical Equipment Seung hyoung Ko, joon ho park, Da woon wang, eun seok kang, hyun wook han, Korea IT service journal, 2023

2. Development of a deep learning model for predicting recurrence of hepatocellular carcinoma after liver transplantation Ko Seung Hyoung , Cao Jie , Yang Yong-kang , Xi Zhi-feng , Han Hyun Wook , Sha Meng , Xia Qiang Frontiers in Medicine 11

Conference

1. Comparison of Machine Learning Algorithm Performance for Network Traffic Security in the Medical Field Seung hyoung Ko, joon ho park, Da woon wang, eun seok kang, hyun wook han Korean Society of Digital Health 2023(best presentation award)

2. Patient Survival Prediction Analyzing Pathological Images After Liver Transplantation Seung Hyoung Ko, Jie Cao, Yong-kang Yang, Zhi-feng Xi, Hyun Wook Han, Qiang Xia, Meng Sha The Liver week 2024.