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Dohyun Park

Photo of Dohyun Park

Address:

4800 Oak Grove Drive

Pasadena, CA 91109

Curriculum Vitae:

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Member of:

Planetary Interiors and Geophysics

Professional Experience

  • NASA Postdoctoral Program Fellow, Jet Propulsion Laboratory (JPL) | 2026 – Present
  • Postdoctoral Fellow, Daegu Gyeongbuk Institute of Science and Technology (DGIST) | 2025 – 2026
  • Postdoctoral Researcher, Pusan National University | 2025
  • Summer Research Intern, Electronics and Telecommunications Research Institute (ETRI) | 2018

Research Interests

Passive radar, radar signal processing, planetary remote sensing, machine learning.

Selected Awards

  • Best Paper Award, Brain Korea 21 Program at Pusan National University | 2025
  • First Place, MathWorks MATLAB AI Student Challenge | 2024
  • Best Paper Award, Korean Institute of Communications and Information Sciences | 2021

Selected Publications

  • D.-H. Park, M.-W. Jeon, and H.-N. Kim, "Activity-dependent resolution adjustment for radar-based human activity recognition," Signal Processing, vol. 243, Art. no. 110456, Jun. 2026.
  • M.-W. Jeon, D.-H. Park, and H.-N. Kim, "RTDNet: Modulation-conditioned attention network for robust denoising of LPI radar signals," Electronics, vol. 15, no. 2, Art. no. 386, Jan. 2026.
  • S.-Y. Kwon, D.-H. Park, and H.-N. Kim, "IPFSCNN: A time–frequency fusion CNN for wideband spectrum sensing," Sensors, vol. 25, no. 23, Art. no. 7134, Nov. 2025.
  • D.-H. Park, M.-W. Jeon, J. Jeong, I. Sim, S. Yun, J. Seo, and H.-N. Kim, "Noise-aware ensemble learning for efficient radar modulation recognition," IEEE Internet of Things Journal, vol. 12, no. 14, pp. 28937–28949, Jul. 2025.
  • M. Cheong, J. Kim, D.-H. Park, and H.-N. Kim, "Temporal-feature-based classification of active sonar targets in a deep-water environment," IEEE Transactions on Aerospace and Electronic Systems, vol. 60, no. 5, pp. 7380–7392, Oct. 2024.
  • J. D. Ruikar, D.-H. Park, S.-Y. Kwon, and H.-N. Kim, "HCTC: Hybrid convolutional transformer classifier for automatic modulation recognition," Electronics, vol. 13, no. 19, Art. no. 3969, Oct. 2024.
  • D.-H. Park, G.-H. Park, J.-H. Park, J.-H. Bang, D. Kim, and H.-N. Kim, "Interference suppression for an FM-radio-based passive radar via deep convolutional autoencoder," IEEE Transactions on Aerospace and Electronic Systems, vol. 60, no. 1, pp. 106–118, Feb. 2024.
  • D.-H. Park, M.-W. Jeon, D.-M. Shin, and H.-N. Kim, "LPI radar detection based on deep learning approach with periodic autocorrelation function," Sensors, vol. 23, no. 20, Art. no. 8564, Oct. 2023.
  • J.-H. Bang, D.-H. Park, W. Lee, D. Kim, and H.-N. Kim, "Accurate estimation of LPI radar pulse train parameters via change point detection," IEEE Access, vol. 11, pp. 12796–12807, 2023.
  • D.-H. Park, J.-H. Bang, J.-H. Park, and H.-N. Kim, "A fast and accurate convolutional neural network for LPI radar waveform recognition," in Proceedings of the 19th European Radar Conference (EuRAD), pp. 89–92, Sep. 2022.
  • J.-H. Bang, D.-H. Park, and H.-N. Kim, "Improved TOA and pulse width estimation for wideband signal in electronic warfare systems," in Proceedings of the 19th European Radar Conference