SOOJEONG LEE

 

 

Contact information: Computer Engineering (Data Science), Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, in Korea

Email:leesoo86@sejong.ac.kr;leesoo8637@gmail.com

Tel:+82 2 6935 2480, office: Deyang AI center, Room 423

Mobile: +82 10 9770 1213

Research Interest: Deep & Machine Learnings, and Uncertainty Estimation for Biomedical processing

 

EMPLOYMENT HISTORY

 

EDUCATION

Ph. D. in Computer Engineering, Kwangwoon University, Seoul, in Korea,      2004~2008

M.Sc. in Computer Engineering, Kwangwoon University, Seoul, in Korea,      1997~2000

B.Sc. in Computer Science, Korea National Open University, Seoul, in Korea,   1992~1997

RESEARCH EXPERIENCE

Active research projects

Bio-signal processing & Machine Learning

■      Uncertainty Reduction Method for Measuring Robust Biometric Signals in Smart Healthcare Devices, Sejong University, 2019-2020

International research collaboration

■      Bio-Signal Processing Technique based on AI technique for Future Wearable Device

ü  Respiratory rate estimation, University of Ottawa, Canada

ü  Continuous blood pressure estimation, Carleton University, Canada

ü  Breast cancer detection, Federal University of Uberlandia, Brazil

 

Completed R&D projects (partial list)

■      Biometric Signal Processing Technology based on Deep Learning (PI), National Research Foundation of Korea, Nov. 2016.- Oct. 2019

■      Algorithm for PPG signal-based Blood Pressure Measurement, Samsung Electronics, July 2018~2019

■      Development of free-running embedded natural language speech for robots, Korea Industrial Technology Evaluation Agency, Aug. 2017~2019

■      Deep learning-based voice and bio signal processing technology development using wearable smart device, National Research Foundation of Korea, Sep. 2017~2019

 

■      Noise Reduction Based on Optimal Algorithm for HD-Voice Target (PI), National Research Foundation of Korea, 2013-2016

 

■      QoS Core Technique Develop of VoLTE:4G LTE based Packet for Speech communication

■      Remote Object Monitoring of Bio-Signals, Ontario Centres of Excellence (Canada)

■      Robust Blood Pressure Measurement, Natural Science and Engineering Research Council (Canada), 2009~2011

■      Hearing aid system for headset using blue-tooth, 2006

■      Adaptive Beam-forming and blind source separation for speech recognition in car environments, 2004~2005

■      Speech enhancement for speech recognition in non-stationary noisy environments, 2011

 

ADDITIONNAL EXPERIENCE

■      Military service: Republic of Korea Marine Cops (ROKMC), 1987-1990

■      Staff:  Korea National Open University, in Seoul, 1993-2000

■      Reviewer: IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Sensors Journal, IEEE ACCESS, ACM Transactions on Computing for Healthcare, IEEE Journal of Biomedical and Health Informatics, SENSORS, The journal Mobile Networks and Applications, Math. Probl. Eng., Journal of Systems Architecture, Journal of sensors, Computers and Electrical Engineering, Applied Science, Applied Acoustics.

 

AWARDS AND RECOGNITIONS

■      Acoustical society of Korea 2006 and 2008 conference outstanding presentation

■      The educational mmultimedia content contest for vocational trainees, Bronze Award, in Korea, 2002

■      License: Engineer Information Processing, Human Resources Development Service of Korea, 2003

■      Vocational training teacher (information technology) in Korea, 2002

■      Wireless communications engineer in Korea, 2003

 

GRANTS

■      Biometric Signal Processing Technology based on Deep Learning (PI), National Research Foundation of Korea, Nov. 2016.- Oct. 2019

■      Noise Reduction Based on Optimal Algorithm for HD-Voice Target (PI) National Research Foundation of Korea, 2013-2016

■      Postdoc. Fellow ship, $40,000/year, University of Ottawa, Ontario, Canada, 2009~2011

 

STUDENT SUPERVISION

■      Ph. D. Jihwan Park, Co-supervision with Prof. Joon-Hyuk, Chang, Frequency-Domain Nonlinear Acoustic Echo Reduction Techniques Using Single-Channel Microphone and Multi-Channel Microphones, 2018

■      Ph. D. Bong-ki Lee, Co-supervision with Prof. Joon-Hyuk, Chang, Deep Neural Networks Based Packet Loss Concealment and Speech Bandwidth Extension Techniques for Digital Speech Transmission, 2017

■      M.S. Hyeji Seo, Acoustic Echo and Background Noise Suppression Algorithm Based on Deep Neural Network, 2017

 

TEACHING EXPERIENCE

■      Instructor, Capston Design, Sejong University, 2019

■      Instructor, Engineering Mathematics, Sejong University, 2019

■      Instructor, Data Structures Sejong University, 2020

■      Instructor, Engineering Mathematics, Sejong University, 2020

 

RESEARCH CONTRIBUTIONS

Ph. D. THESIS “Speech enhancement based on variance of spectral power in time-frequency for speech recognition in non-stationary noisy environments,”, Kwangwoon University in Korea (Seoul), 2008.02. Supervisor: Soonhyob, Kim

 

INTERNATIONAL JOURNAL PAPERS

 

[31] K.Haseeb, S.Lee, G. Jeon, EBDS: An energy-efficient big data-based secure framework

using Internet of Things for green environment, Environmental Technology & Innovation, vol. 20, pp.1-12, Sep. 2020 (IF:3.356, Top 33.2 %)  

 

[30] S. Lee, C.-H. Son, M. K. Albertini, and H. C. Fernandes, Multi-phases and various feature extraction and selection methodology for ensemble gradient boosting in estimating respiratory rate, IEEE ACCESS, vol. 8, pp. 125648-125658, July 2020 (IF: 3.745, Top 22.4 %)

[29] E. Chaves, C. B. Concalves, M. K. Albertini, S. Lee, G. Jeon, H. C. Fernandes, Evaluation of transfer learning of pre-trained CNNs applied to breast cancer detection on infrared images, Applied Optics, vol. 59 (17), pp. E23-E28, 2020 (IF: 1.961)

[28] S. Lee, H. Dajani, S. Rajan, G. Lee, V.  Groza, Uncertainty in Blood pressure measurement estimated using ensemble-based recursive methodology, SENSORS, vol. 20 (7), 2108, Apr. 2020 (IF:3.275, Top 23.4%)  

[27] S. Lee, and G. Lee, Support vector regression based recursive ensemble methodology for confidence interval estimation in blood pressure measurements, Journal of Sensors, vol. 2020, Article ID 7360702, pp. 1-8, Apr.  2020 (IF:1.595) 

[26] S. Lee, and G. Lee, Ensemble methodology for confidence interval in oscillometric blood pressure measurements, Journal of Medical Systems, 44, 91, Mar. 2020 (IF: 3.058, Top 22.5%)

[25] S. Lee, G. Lee, and G. Jeon, Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates, SENSORS, vol. 19, pp.1-15, May 2019 (IF:3.275, Top 23.4%)

[24] S. Lee, and J.-H. Chang, Dempster-Shafer fusion for Blood Pressure Classifier, Applied Science, vol. 9, no. 96, pp. 1-13, Jan. 2019 (IF:2.474, Top 35.2%)

[23] S. Lee, and G. Jeon, Mimic Big Data and Low Power Infrastructure-based Small Blood Pressure Measurement for Internet of Things, Journal of Internet Technology, vol. 20, no. 1, pp. 315-322, Jan. 2019 (IF:0.935)

[22] S. Lee, A. Ahmad, and G. Jeon, Combining Bootstrap Aggregation with Support Vector Regression for Small Blood Pressure Measurement, Journal of Medical Systems, vol. 42, pp. 1-7, Apr. 2018 (IF: 3.058, Top 22.5%)

[21] S. Lee, and J.-H. Chang, Spectral Difference for Statistical Model-Based Speech Enhancement in Speech Recognition, Multimedia Tools and Applications, vol. 76, no. 23, pp. 24917-24929, Dec. 2017 (IF:2.313, Top 31.5%)

[20] S. Lee, and J.-H. Chang, Deep Learning Ensemble with Asymptotic Techniques Based on Bootstrap for Oscillometric Blood Pressure Estimation, Computer Methods and Programs in Biomedicine, vol. 151, pp. 1-13, Nov. 2017 (IF:3.632, Top 14.8%)

[19] S. Lee, and J.-H. Chang, Deep Boltzmann Regression with Mimic Features for Oscillometric Blood Pressure Estimation, IEEE Sensors Journal, vol. 17, no. 18, pp. 5982-5993, Set. 2017 (IF:3.073, Top 28.1%)

[18] S. Lee, and J.-H. Chang, Deep Belief Networks Ensemble for Blood Pressure Estimation, IEEE ACCESS, vol. 5, pp. 9962-9972, June 2017 (IF: 3.745, Top 22.4 %)

[17] S. Lee, and J.-H. Chang, Oscillometric Blood Pressure Estimation Based on Deep Learning, IEEE Transactions on Industrial Informatics, vol. 13, no. 2, pp. 461-472, Apr. 2017 (IF:9.112, Top 4.16%) 

[16] S. Lee, S. Rajan, G. Jeon, J-.H. Chang, H. Dajani, and V. Groza, Oscillometric blood pressure estimation by combining nonparametric bootstrap with Gaussian mixture model, Computers in Biology and Medicine, vol. 85, pp. 112-124, June 2017 (IF:3.434, Top13.6 %)

[15] S. Lee, C.-H. Park, and J.-H. Chang, Improved Gaussian mixture regression based on pseudo feature generation using bootstrap in blood pressure estimation, IEEE Transactions on Industrial Informatics, vol. 12, no. 6, pp. 2269-2280, Dec. 2016 (IF:9.112, Top 4.16%) 

[14] S. Lee, and G. Lee, Noise estimation and suppression using nonlinear function with a priori speech absence probability in speech enhancement, Journal of Sensors, vol. 2016, ID 5352437, 7 pages. May 2016 (IF:1.595)

[13] S. Lee and J.-H. Chang, On using multivariate polynomial regression model with spectral difference for statistical model-based speech enhancement, Journal of Systems Architecture, vol. 64, pp. 76-85, Mar. 2016 (IF:2.552, Top 27.8%) 

[12] S. Lee, S. Rajan, C.-H. Park, J-.H. Chang, H. Dajani, and V. Groza, Estimated confidence interval from single pressure measurement based on algorithmic fusion, Computers in Biology and Medicine, vol. 62, pp. 154-163, Jul. 2015 (IF:3.434, Top13.6 %)

[11] C.-H. Park, S. Lee, and J.-H. Chang, Shrinkage-based biased SNR estimator using pilot and data symbols for linearly modulated signals, IET Communications, vol. 9, pp. 1388-1395, Jun. 2015 (IF:1.664) 

[10] C.-H. Park, S. Lee, and J.-H. Chang, Robust closed-form time-of-arrival source localization based on α-trimmed mean and Hodges-Lehmann estimator under NLOS environments, Signal Processing, vol. 111, pp. 113-123, Jun. 2015 (IF:4.384, Top 16.9%)

[9] S. Lee, G. G Jeon, and S. kang, Two-step pseudomaximum amplitude-based confidence interval estimation for oscillometric blood pressure measurements, BioMed Research International, vol. 2015, article ID 920206, pp. 1-9, Oct. 5. 2015 (IF:2.276)

[8] S. Lee, Improved confidence interval estimation for oscillometric blood pressure measurement by combining bootstrap-after-jackknife function with non-Gaussian models, Mathematical Problems in Engineering, vol. 2014, article ID 231925, pp. 1-10, Nov. 27. 2014 (IF:1.009)

[7] S. Lee, C. Lim, and J.-H. Chang, A new a priori SNR estimator based on multiple linear regression technique for speech enhancement, Digital Signal Processing, vol. 30, No. 7, pp. 154-164, Jul. 2014 (IF:2.872, Top 38.3%)

[6] C. Lim, S. Lee, J.-H. Choi, and J.-H. Chang, Efficient implementation of statistical model based voice activity detection using Taylor series approximation, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, vol. e97-a, no 3, pp. 865-868, Mar. 2014 (IF:0.334)  

[5] S. Lee, J-H. Chang, S. W. Nam, C. S. Lim, S. Rajan, H. Dajani, and V. Groza, Oscillometric blood pressure estimation based on maximum am employing Gaussian mixture regression, IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 12, pp. 3387-3389, Dec. 2013 (IF:3.658, Top 14.1%)

[4] S. Lee, G. G. Jeon, and G. S. Lee, On using maximum amplitude a posteriori probability based on a Bayesian model for oscillometric blood pressure estimation, SENSORS, vol. 13. no. 10, pp. 13609-13623, Oct. 2013 (IF:3.275, Top 23.4%),

[3] S. Lee, M. Bolic, V. Groza, H. Dajani, and S. Rajan, Confidence interval estimation for oscillometric blood pressure measurements using bootstrap approaches, IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 10, pp. 3405-3415, Oct. 2011 (IF:3.658, Top 14.1%)

[2] S. Lee and S. H. Kim, Noise estimation based on standard deviation and sigmoid function using a posteriori signal to noise ratio in nonstationary noisy environments, International Journal of Control Automation and Systems, vol.6, no.6. pp. 818-827, Dec. 2008 (IF:2.733, Top 49.2%)

[1] S. Lee, K. H. Choi and Soonhyob Kim, A conventional beamformer using post-filter for speech enhancement, Springer-Verlag, LNAI vol.4413, pp.188-197, Dec. 2007

 

DOMESTIC JOURNAL PAPERS

 

[10] Yong Kook Lee, Im Bong Lee, Joon Hyuk Chang, Soo Jeong Lee*, On employing nonparametric bootstrap technique in oscillometric blood pressure measurement for confidence interval estimation, Journal of Korea Multimedia Society, vol. 17, pp. 200-207, Feb. 2014

 

[9] Soojeong Lee, Gangseong Lee, and Soonhyob Kim, Noise-Biased Compensation of Minimum Statistics Method using a Nonlinear Function and A Priori Speech Absence Probability for Speech Enhancement”, THE JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, vol.28, (1), 2009.01.30

 

[8] Soojeong Lee, Soonhyob Kim, Noise estimation and suppression based on normalized variance of time-frequency for speech enhancement, The Institute of Electronics Engineers of Korea, vol.46, SP (1), 2009.01.15, (Korean).

 

[7] Soojeong Lee, Soonhyob Kim, Adaptive Threshold for Speech Enhancement in Highly Nonstationary Noisy Environments, THE JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, vol.27, (7), pp.386-393, 2008.10.30, (English).

 

[6] Soojeong Lee and Soonhyob Kim, Noise Suppression Using Normalized Time-Frequency bins Average and Modified Gain Function for Speech enhancement in Non-Stationary Noisy Environments, THE JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, vol.27, (1)E, pp.1-9, 2008 (English).

 

[5] Soojeong Lee, Kyehyeon Shin and Soonhyob Kim, Optimization of Detection Method Using a Moving Average Estimator for Speech Enhancement, IEEK, The Institute of

electronics Engineers of Korea, vol.44, SP (3), pp. 97-104, 2007, (Korean).

 

[4] Soojeong Lee and Soonhyob Kim, Noise reduction using the standard deviation of the time-frequency bin and modified gain function for speech enhancement in stationary and nonstationary noisy environments, THE JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, vol.26, (4) E, pp. 39-48, 2007, (English).

 

[3] Soojeong Lee, Eunkyong Lee, GabKeun Choi and Soonhyob Kim, Performance Improvement of Continuous Digits Speech Recognition Using the Transformed Successive State Splitting and Demi-syllable Pair, Journal of Korea Multimedia Society, vol. 9, (1), pp. 2332, 2006, (Korean).

 

[2] Soojeong Lee, Chansik Ahn, Jongmu Yun and Soonhyob Kim, A New Least Mean Square Algorithm Using a Running Average Process for Speech Enhancement, THE JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, vol.25, (3) E, pp. 123-130, 2006, (English).

 

[1] Soojeong Lee, GabKeun Choi and Soonhyob Kim, A method of the crosstalk cancellation for sound reproduction of 5.1 channel speaker system”, IEEK, The Institute of Electronics Engineers of Korea, vol.42, SP (4), pp. 159-166, 2005, (Korean).

 

INTERNATIONAL CONFERENCE PAPERS

 

[8] Soojeong Lee, Miodrag Bolic, Voicu Z Groza, Hilmi R Dajani, and Sreeraman Rajan, Determination of Blood Pressure Using Bayesian Approach, IEEE 2011 Instrumentation and Measurement Technology Conference (I2MTC), pp.1-5, 2011, China.

[7] Soojeong Lee, Miodrag Bolic, Voicu Z Groza, Hilmi R Dajani, and Sreeraman Rajan, Confidence interval estimation for blood pressure measurements with nonparametric bootstrap approach, IEEE International workshop on Medical Measurements and Applications (MeMeA) 2010, from April 30-May 1, in Ottawa, Canada.

 

[6] Soojeong Lee and Soonhyob Kim, Noise reduction using the standard deviation of the time-frequency bin and modified gain function for speech enhancement in stationary and nonstationary noisy environments, 2008 Congress on Image and Signal Processing (CISP 2008), from 27 - 30 May 2008, in Sanya, Hainan, China.

 

[5] Soojeong Lee and Soonhyob Kim, Speech enhancement using gain function of noisy power estimates and linear regression, FBIT 2007, Frontiers in the Convergence of Bioscience and Information Technologies, IEEE Computer Society, 2007.

 

[4] Soojeong Lee and Soonhyob Kim, Speech enhancement using masking of noisy power estimates, FBIT 2007, Frontiers in the Convergence of Bioscience and Information Technologies, IEEE Computer Society, 2007.

 

[3] Soojeong Lee and Soonhyob Kim, Noise reduction algorithm using linear regression estimator thresholds for speech enhancement, ITC-CSCC 2007, The 22nd International Technical Conference on Circuits and Systems, Computers and Communications.

 

[2] Soojeong Lee, Chansik Ahn and Soonhyob Kim, Running Average LMS using Detection Algorithm for Speech Enhancement, WESPAC, The 9thWestern Pacific Acoustics Conference, pp. 204-211, 2006.

 

[1] Soojeong Lee, Kiho Choi and Soonhyob Kim, A conventional Beam-former using postfilter for speech enhancement, ICHIT, International Conference on Hybrid Information Technology, pp, 2006.

 

PATENT

 

전광길, 이수정

2-단계 의사최대진폭추정 기반의 신뢰구간 추정을 포함하는 오실로메트릭 혈압측정 방법, code: 10-1738850, Korea, May 17, 2017

G. Jeon and S. Lee, An oscillometric blood pressure measurement method comprising confidence interval estimation based on two-stage pseudo maximum amplitude estimation, code: 10-1738850, Korea, May 17, 2017