Graduate Students of Chosun University Stand Out with Consecutive Awards at Autumn Academic Conference

Department of Advanced Materials Engineering: An Kyungbin, Jeong Junho, Lee Hyunji

[Asia Economy Honam Reporting Headquarters Reporter Yoon Jamin] Graduate students at Chosun University stood out by winning consecutive awards at the Autumn Academic Conference.

According to Chosun University on the 3rd, Kyungbin Ahn, a doctoral student in the Department of Advanced Materials Engineering (advisor Heejin Jang), and Junho Jeong, a master's student (advisor Heesu Kim), received the Excellent Student Oral Presentation Award at the 2022 Autumn Academic Conference of the Korean Institute of Metals and Materials.

Kyungbin Ahn received the award for his research titled "Effect of Heat Treatment Conditions on the Corrosion Resistance of Ti-6Al-4V Alloy Manufactured by DED Process." This study evaluated the corrosion properties of 3D-printed metals used as biomaterials, identified the chemical stability of the materials, and proposed methods to enhance material characteristics.

Additionally, by being selected as an MTDI scholarship recipient, he demonstrated excellent academic achievement and research results in the field of corrosion prevention of metals manufactured by 3D printing, recognizing his potential as a promising researcher in the future.

Junho Jeong received the excellence award for his research presentation titled "Machine Learning for Grain Size Measurement of Colored Microstructures."

This study applied recently spotlighted artificial intelligence and machine learning technologies to the analysis of microscopic images of materials and proposed a method to evaluate the average grain size of materials through machine learning.

Also, Hyunji Lee, a master's student in the same department (advisor Heesu Kim), received the "KOFWST-KIM Young Researcher Award."

She was honored for her paper titled "Visualization of Intermediate Layers in Convolutional Neural Networks for Cast Iron Microstructure Analysis," submitted to the Journal of the Korean Institute of Metals and Materials.

This paper is a study that classifies microscopic images of metals using machine learning and systematically examines the basis on which computers analyze microscopic structures.

This content was produced with the assistance of AI translation services.