Students from the Faculty and Graduate School of Science and Engineering Receive the Student Encouragement Award at the 83rd National Convention of the Information Processing Society of Japan

Eiji Shinkawa, a fourth-year student (at the time) in the Department of Information Systems Engineering, Atsumi Laboratory, and Kento Sunada, a student in the Torii Laboratory, along with Ryuichi Minagawa, a first-year master's student (at the time) in the Graduate School of Science and Engineering, Department of Information Systems Engineering, Torii Laboratory, received the Student Encouragement Award at the 83rd National Convention of the Information Processing Society of Japan, held online from March 18 to 20, 2021.

The Information Processing Society of Japan (IPSJ) was established in 1960 with the aim of contributing to the development of academia, culture, and industry by promoting academic research and technology related to information processing, particularly in computers and communications.

Shinkawa presented his research entitled “Prediction of Drug–Protein Interactions Using Neural Networks Incorporating Glycan Information” (tentative translation), Sunada presented “Pattern Analysis of Password Spray Attacks Using Honeypots and Countermeasures” (tentative translation), and Minagawa presented “Can Text Reflected in Glasses Be Read?” (tentative translation).

Shinkawa, who received the Student Encouragement Award, commented:
“I am very honored to receive this award for my first conference presentation. I presented the usefulness of glycan information in predicting drug–protein interactions based on the results of a neural network model I developed. Throughout the research, I received extensive support from Professor Atsumi and senior members of the laboratory. In addition, data was kindly provided by Professor Kinoshita’s laboratory at our university, and I had many discussions regarding glycans and drug discovery. I will continue to strive in my research, always remembering my gratitude to these individuals.”

Sunada said:
“I am not good at presenting in front of people, and I originally participated in the conference to gain experience. I never expected to receive an award. In my presentation, I analyzed the patterns of password spray attacks—a recently emerged type of password cracking—by deploying honeypots in Japan, the U.S., and India, and proposed countermeasures. I will continue to challenge myself in conference presentations and strive to achieve results.”

Minagawa added:
“I am very pleased to receive this award and sincerely grateful to Professor Torii for guiding me in this research. In my presentation, I used deep learning to recognize characters reflected in blue-light glasses and discussed the associated information leakage risks. I will continue to make efforts to become a professional who can contribute to society.”