POSTECH Department of Electrical Engineering student Park Hanjun(Undergraduate, Class of 2021, Advisor: Na Dong-yeop) has been selected as a recipient of the 2026 IEEE ComSoc Student Travel Grant Award which supports the 2026 IEEE Wireless Communications and Networking Conference (WCNC). With this award, student Park Hanjun will receive full support totaling 1,000 dollars for conference registration fees, travel and accommodation expenses.

IEEE WCNC 2026 is a flagship international conference in the field of communications, bringing together researchers from around the world, and is scheduled to be held in Malaysia from April 13 to 16, 2026. This travel grant is organized by the IEEE Communications Society, and is a program that selects and supports students who publish papers and give oral presentations at the conference through a rigorous review process. Competitive selection is made among students, and decisions are based on a comprehensive evaluation of the student's research achievements and academic history, and contributions to the conference. In particular, as the selection is made from a large number of applicants, this award is considered a significant achievement that externally recognizes research capabilities. It is a very rare case for an undergraduate student to independently produce research results at a prestigious international conference and receive an award, and it is expected to set a positive precedent encouraging global research among undergraduate students.

Student Park Hanjun will present the paper “Low-Overhead CSI Feature for Fingerprint Localization” (Authors: Hanjun Park, Pere Garau Burguera, Hanan Al-Tous, Olav Tirkkonen) at the IEEE WCNC 2026 conference. This research is the result of a collaborative study conducted by student Park Hanjun during his short-term study abroad and visiting researcher period at the Communications Theory Group at Aalto University in Finland, with support from POSTECH and the Department of Electrical Engineering. This study proposed a new low-overhead Channel State Information (CSI) feature extraction technique that can significantly reduce data transmission volume (communication overhead) and computational complexity while maintaining high indoor positioning accuracy in wireless communication environments.