Research output per year
Research output per year
Personal profile
In Korean
이석진 교수(IT대학 전자공학부)
Education
o (2006) B.A., Seoul National University, Seoul, Republic of Korea
o (2008) M.A., Seoul National University, Seoul, Republic of Korea
o (2012) Ph.D., Seoul National University, Seoul, Republic of Korea
o (2008) M.A., Seoul National University, Seoul, Republic of Korea
o (2012) Ph.D., Seoul National University, Seoul, Republic of Korea
Professional Experience
o (2020~Present) Associate Professor, Kyungpook National University, Daegu, Republic of Korea
o (2018~2020) Assistant Professor, Kyungpook National University, Daegu, Republic of Korea
o (2014~2018) Assistant Professor, Kyonggi University, Gyeonggi-do, Republic of Korea
o (2012~2014) Senior Researcher, LG Electronics, Seoul, Republic of Korea
o (2018~2020) Assistant Professor, Kyungpook National University, Daegu, Republic of Korea
o (2014~2018) Assistant Professor, Kyonggi University, Gyeonggi-do, Republic of Korea
o (2012~2014) Senior Researcher, LG Electronics, Seoul, Republic of Korea
Research Interests
Acoustic Signal Processing, Adaptive Signal Processing, Array Signal Processing, Source Separation, Audio/Music Signal Processing, Signal processing for underwater acoustics, Deep Learning for acoustic signals, Music Information Retrieval
Major Research Achievements
o Development of acoustic signal processing and separation techniques based on nonnegative matrix factorization
o Development of feature extraction methods utilizing the signal characteristics for deep learning-based acoustic scene classifcation and sound event detection models
o Developing the deep learning-based compression methods for acoustic signals
o Research on the compressive sensing-based underwater acoustic signal processing techniques
o Reproduction of acoustic wavefield and binaural sound signals for immersive sound system
o Development of feature extraction methods utilizing the signal characteristics for deep learning-based acoustic scene classifcation and sound event detection models
o Developing the deep learning-based compression methods for acoustic signals
o Research on the compressive sensing-based underwater acoustic signal processing techniques
o Reproduction of acoustic wavefield and binaural sound signals for immersive sound system
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Wave field synthesis for a moving point source under the near-field assumption
Jeon, I. & Lee, S., 1 Jan 2026, In: Journal of the Acoustical Society of America. 159, 1, p. 25-43 19 p.Research output: Contribution to journal › Article › peer-review
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A study on two stage acoustic classification neural network training algorithm from pretrained models for small scale data environments
Shin, S., Kim, M. & Lee, S., 2025, In: Journal of the Acoustical Society of Korea. 44, 3, p. 270-280 11 p.Research output: Contribution to journal › Article › peer-review
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Comparison of Three DFT-Based Fine Frequency Estimation Methods Using Synthetic Vibrato Tone Models
Pang, H. S., Lim, J. S. & Lee, S., 1 Sep 2025, In: IEICE Transactions on Information and Systems. E108.D, 9, p. 1155-1158 4 p.Research output: Contribution to journal › Article › peer-review
Open Access -
L1-노름과 주요화최소화 기법을 활용한 비음수 행렬 분해 기반 능동소나 잔향제거 개선 방법
Translated title of the contribution :Improvement of non-negative matrix factorization-based active sonar reverberation suppression method using L1-norm and majorization-minimization Research output: Contribution to journal › Article › peer-review
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Noise Suppression Method With Low-Complexity Noise Estimation Model and Heuristic Noise-Masking Algorithm for Real-Time Processing of Robot Vacuum Cleaners
Shin, S., Kim, M., Jeon, I., Song, J. M., Park, Y., Son, J. & Lee, S., 2025, In: IEEE Access. 13, p. 789-801 13 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations