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I am a B.S. candidate at DGIST, double-majoring in Electrical Engineering and Computer Science, and an undergraduate researcher at the Intelligent Radio Sensing Lab (IRS Lab) under Prof. Jae‑Ho Choi. I work on signals that were designed to carry information but can also be read as measurements of the physical world — passive Wi-Fi sensing on software-defined radio, and physics-based drone sensing simulation in NVIDIA Sionna RT.

Research

Currently

Exploring physics-based drone sensing simulation in NVIDIA Sionna RT.

Statement

At IRS Lab that interest takes the form of passive radar sensing, with ambient communication signals as the illuminator rather than a dedicated radar transmitter. I have worked on passive Wi-Fi sensing on a USRP-2921, recovering and analyzing respiration waveforms from the measured signal, and am now exploring physics-based drone sensing simulation in Sionna RT.

  • RF sensing RF & passive sensing — passive Wi-Fi sensing, SDR-based measurement, contactless vital-sign monitoring and drone sensing.
  • Radar DSP Radar & wireless signal processing — cross-ambiguity processing and the Range–Doppler maps it produces, clutter mitigation.
  • Physics · ISAC Physics-based sensing & ISAC — RF propagation simulation and physics-based sensing using communication signals.
  • Learning Learning-based RF sensing — interested in applying machine learning to detection and classification from radar representations.

Publications & Awards

Conference

[1] First page of the JCCI 2025 paper

Real-Time Video Transmission in 5G C-V2X Sidelink: An Empirical Study

D. Lee, M. Kim, Y. Jeong, Y. Jang, Y. Kang, T. Lee, and J.-W. Choi, “Real-Time Video Transmission in 5G C-V2X Sidelink: An Empirical Study (5G C-V2X Sidelink 기반 실시간 영상 전송 성능에 대한 실증 연구).” JCCI, 2025.

Download PDF

Awards

Jul 2026

Kiturami Scholarship (귀뚜라미 장학금)

Kiturami Cultural Foundation

  • One of 50 DGIST recipients, selected by the Student Scholarship Committee through a comprehensive evaluation of undergraduate research-project participants.

Feb 2025

Encouragement Award (장려상)

Winter Conference Idea Contest, Korean Institute of Communications and Information Sciences (KICS)

Experience

Research

Jan 2026Present

Undergraduate Researcher

Intelligent Radio Sensing Lab (IRS Lab), DGIST · Advisor: Prof. Jae‑Ho Choi

  • Passive Wi-Fi sensing. Implemented a passive sensing pipeline on a USRP-2921 with reference and surveillance channels and CAF-based Range–Doppler processing; recovered and analyzed respiration waveforms from measured Wi-Fi signals.
  • Physics-based drone sensing. Currently investigating physics-based RF sensing for drone targets using NVIDIA Sionna RT.

Jan 2025Apr 2025

Undergraduate Researcher

Communication & Signal Processing Lab (CSP Lab), DGIST · Advisor: Prof. Ji‑Woong Choi

  • C-V2X sidelink measurement. Empirical study of real-time video transmission over 5G C-V2X sidelink in a V2I scenario with OBU and RSU hardware, characterizing the link by RSSI, estimated SNR, block error rate (BLER) and throughput.
  • MCS trade-off analysis. Quantified BLER against average throughput across MCS indices, reported in the JCCI 2025 paper.

Teaching

Aug 2026Present

Teaching Assistant

Introduction to Artificial Intelligence, DGIST

Feb 2026Jun 2026

Teaching Assistant

Linear Algebra, DGIST

Education

Feb 2021Present

B.S. Candidate, Electrical Engineering & Computer Science

Daegu Gyeongbuk Institute of Science & Technology (DGIST) · School of Undergraduate Studies

  • Double major. Expected graduation Aug 2027.
  • GPA 3.78 / 4.30.

Military Service

Jul 2022Jan 2024

Mandatory Military Service

Republic of Korea Army · Completed

Projects

USRP-2921PythonRF sensing

Passive Wi-Fi Respiration Sensing

Built a passive Wi-Fi sensing setup with reference and surveillance channels, using ambient Wi-Fi as the illuminator. Applied CAF-based Range–Doppler and phase-based processing to the measured signals to recover and analyze respiration waveforms.

CTCP/IP2nd of 40

Network AI Game Client with RGB LED Matrix

A TCP/IP socket game client in C, using minimax with alpha-beta pruning for real-time decisions and rendering to a 64×64 RGB LED matrix. Placed second of forty teams in the course competition.

Skills

Wireless & RF
Passive radar sensing, SDR-based RF measurements, drone-sensing simulation, C-V2X sidelink analysis.
Signal processing
Cross-ambiguity processing and Range–Doppler mapping, phase-based sensing, clutter and background removal, FFT / STFT.
Instruments
Software-defined radio — USRP X410, USRP-2921.
Simulation
NVIDIA Sionna RT — RF propagation and sensing simulation.
Programming
Python, C/C++, Git, Linux.