UNIST Student Taehyun Yoon Ranks First in Artificial Intelligence Society Competition

Hosted by NeurIPS, Solving Combinatorial Optimization Problems

Conference Presentation · 1000 Canadian Dollar Prize

Yoon Taehyun, a student at the Graduate School of Artificial Intelligence at UNIST, who ranked first in the student category and second globally at a world-renowned artificial intelligence conference competition (front row, left, blue chair), along with fellow lab students.

[Asia Economy Yeongnam Reporting Headquarters Reporter Se-ryeong Lee] Yoon Tae-hyun, a student at the Graduate School of Artificial Intelligence at Ulsan National Institute of Science and Technology (UNIST), ranked first in the student category at a world-renowned artificial intelligence conference competition.

Yoon Tae-hyun took first place in the student category in the Primal Task division at the ‘Machine Learning for Combinatorial Optimization (ML4CO)’ competition hosted by NeurIPS, the most prestigious international conference in the field of artificial intelligence and machine learning, achieving second place globally.

The award ceremony will be held on the 9th at the NeurIPS 2021 conference, where the winning team will have the opportunity to present their results at the conference, and the student competition winning team will receive a prize of 1,000 Canadian dollars.

The Machine Learning for Combinatorial Optimization competition aims to improve the performance of solver programs that solve combinatorial optimization problems with high computational complexity through machine learning.

Combinatorial optimization is a field of industrial engineering and applied mathematics used in industrial sites to find the most efficient methods for transportation routes, scheduling, and more. Recently, attempts to automatically find optimal combinations based on data have increased, drawing growing interest from academia.

The competition was held with 50 teams, including 23 student teams from companies and research institutes worldwide, competing over four months from July to October to improve program performance.

The competition was divided into three categories: Primal Task, Dual Task, and Configuration Task, allowing various approaches.

During the competition, the program’s performance was periodically evaluated and ranked. Initially, Yoon Tae-hyun’s scores were not very high. However, by progressively collecting data, implementing code, repeatedly testing, and trying new approaches, he was recognized for achieving the highest performance improvement.

Yoon Tae-hyun explained, “Earlier this year, I had the opportunity to review related papers in the lab and even implemented unpublished code of a combinatorial optimization algorithm announced by Google DeepMind.”

He added, “I think the intense discussions with my research colleagues to find solutions and the perseverance to keep challenging the problem led to this good result.”

Advisor Professor Lim Sung-bin said, “I am very pleased and proud that the students’ four months of challenges have borne good fruit,” and added, “I feel proud that this competition has helped showcase the skills of UNIST students to the world.”

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