JYJung

Professor Jae-Yoon Jung #

jung9.jpg[http] Jae-Yoon JUNG (정재윤, 鄭在倫)(http://bpm.khu.ac.kr/wiki/wiki.php/JYJung)
Professor, Dept. of Industrial & Management Systems Engineering (IE), KHU, 2018.9~present
Dean of Information Service and Strategy, KHU, 2021.9~present
Director of Digital Transformation (DX) Initiative, KHU, 2024.11~2025.10
Adjunct Professor, Dept. of Artificial Intelligence (AI), KHU, 2022.9~present
Adjunct Professor, Dept. of Big Data Analytics (BDA), KHU, 2020.9~present
Adjunct Professor, Dept. of Software Convergence (SWCon), KHU, 2017.3~present
Department Head, BDA, KHU, 2021.9~2022.8, 2024.3~2025.2
Graduate Program Director, IE, KHU, 2018.2~2020.1
Director, Graduate Program for Smart Manufacturing Intelligence (SMI), KHU, 2017.3~2020.2
Department Head, IE, KHU, 2015.2~2018.1
Associate/Assistant Professor, IE, KHU, 2007.9~2018.8
Ph.D./M.S./B.S., Industrial Engineering, Seoul National University, 2005, 2001, 1999
(Office) 430-Ho, Eng. Bld., (Tel) +82-31-201-2537, (E-mail) jyjung_at_khu.ac.kr
(Lab) http://iai.khu.ac.kr/wiki/wiki.php/JYJung
(Personal) http://web.khu.ac.kr/~jung
[https]Curriculum vitae(https://drive.google.com/file/d/1MgIE0Cbr949q1uHZRneCGj181f_i7KKq/) [https]Google scholar(https://scholar.google.com/citations?user=iuRrCpIAAAAJ&hl=en) [https]Scopus profile(https://www.scopus.com/authid/detail.uri?authorId=55575978400) [https]pure(https://khu.elsevierpure.com/en/persons/jae-yoon-jung/publications/) [https]orcid(https://orcid.org/0000-0002-4850-6284)

Dr. Jae-Yoon Jung (정재윤, 鄭在倫) is a professor in the department of industrial and management systems engineering at Kyung Hee University (KHU), Korea, and also an adjunct professor of the department of artificial intelligence, the department of the department of big data analytics (BDA), and the department of software convergence (SWCon), KHU. He is leading Industrial AI Lab at KHU.
He received the B.S., M.S., and Ph.D. degrees in Industrial Engineering at Seoul National University (SNU), in 1999, 2001, and 2005, respectively. In SNU, he was supervised by prof. Suk-Ho Kang and Yeongho Kim in Intelligent Manufacturing Systems Lab. After that, he visited the Process Mining Group at Eindhoven University of Technology (TU/e) in the Netherland, supervised by prof. Wil van der Aalst. Before joining in KHU, he worked for u-Computing Innovation Center (uCIC), directed by Prof. Jinwoo Park, and he also studied in the Information Management Lab. at SNU, supervised by prof. Jonghun Park. His current research interests include Industrial AI, Big Data Analytics, Process Mining, and Smart Factory.

Education #

  • Ph.D., Dept. of Industrial Engineering, Seoul National University, 2005
    (Thesis: Design and Analysis of B2B Collaborative Process Using Process Choreography and Workflow Clustering)
  • M.S., Dept. of Industrial Engineering, Seoul National University, 2001
    (Thesis: Development of Object-Oriented Workflow Management Systems Using Run-time Encapsulation)
  • B.S., Dept. of Industrial Engineering, Seoul National University, 1999

Professional Experience #

  • 2021.9~present, Dean, Information Services and and Strategy, KHU
  • 2020.9~2021.8, 2024.3~2025.2, Department Head, Department of Big Data Analytics (BDA), KHU
  • 2018.2~2020.1, Graduate Program Director, Department of Industrial and Management Engineering (IE), KHU
  • 2017.3~2020.2, Director of Smart Factory Program, KHU
  • 2015.2~2018.1, Department Head, Department of IE, KHU
  • 2013.11~2014.8, Visiting Scholar, Industrial & Systems Engineering, Georgia Institute of Technology
  • 2013.9~2018.8, Associate Professor, Department of IE, KHU
  • 2007.9~2013.8, Assistant Professor, Department of IE, KHU

  • 2006.12~2007.8, Senior Researcher, u-Computing Innovation Center, Seoul National University
  • 2005.12~2006.11, Visiting Scholar, Process Mining Group, Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, The Netherlands
  • 2005.9~2005.11, Senior Researcher, Automation & Systems Research Institute (ASRI), Seoul National University

Memberships #

  • Member of IEEE (Institute of Electrical and Electronics Engineers)
  • Member of IEICE (Institute of Electrics, Information and Communication Engineers)
  • Member of IEEE Task Force on Process Mining
  • Member of EPTS (Event Process Technical Society)

  • Board/Liftetime member of SEBS (Society for e-Business Studies), 2010/2008~present
  • Board/Lifetime member of KIIE (Korean Institute of Industrial Engineers), 2015/2008~present
  • Lifetime member of KMIS (Korean Society of Management Information Systems), 2008~present
  • Board member of KBDS (Korea Bigdata Society), 2013~present
  • Board member of KASA (Korean Auto-Vehicle Safety Association), 2016~2020

Academic Activities #

Honors and Awards #

  • Best Paper Award, SEBS 2025 Spring , KISM 2023 Spring, CDE 2023 Winter, CDE 2022 Winter
  • Best Paper Award, International Conference on Innovation Convergence Technology (ICICT2021).
  • Best Paper Award, SEBS 2021 Spring, SEBS 2020 Fall
  • Merit of Smart Manufacturing Industry, Award of Minister of Trade, Industry and Energy (MOTIE), 2019.
  • Award of President of Korea Smart Manufacturing Association, the 2st Smart Factory Excellent Paper Contest, 2019.
  • Award of President of Korea Electronics Technology Institute, the 2st Smart Factory Excellent Paper Contest, 2019.
  • Grand Prize (Award of President of Korea Institute of Industrial Technology), the 9th Industrial Convergence Paper Contest, 2019.
  • Best Paper Award, SEBS 2019 Fall
  • Award of President of Korea Smart Manufacturing Association, the 1st Smart Factory Excellent Paper Contest, 2018.
  • Award of President of Korea Smart Factory Foundation, the 1st Smart Factory Excellent Paper Contest, 2018.
  • Outstanding Master’s Paper Award, the Korean Institute of Industrial Engineers Conference, 2018.
  • Best Paper Award, The 6th International Conference on Big Data Applications and Services (BigDAS 2018).
  • Best Paper Award, SEBS 2018 Spring
  • Best Paper Award, The 12th International Conference on Innovative Computing, Information and Control (ICICIC 2017)
  • Best Paper Award, 2016 Korea Big Data Society Fall Conference.
  • Best Paper Award, 2015 Korean Enterprise Architecture Society Conference.
  • Outstanding Master’s Paper Award, the Korean Institute of Industrial Engineers Conference, 2015.

Selected Papers #

  • Explainable AI
    1. Josue Obregon and Jae-Yoon Jung*, "RuleCOSI+: Rule Extraction for Interpreting Classification Tree Ensembles", Information Fusion, Vol. 89, Jan. 2023, 355-381. (SCIE, IF=17.564, 0.45%(1/109), CS/T&M) (Ack: Engy, OCC). [https]link(https://www.sciencedirect.com/science/article/pii/S1566253522001129) [https]pdf(https://www.sciencedirect.com/science/article/pii/S1566253522001129/pdfft?md5=0b58e19ec75339e444a7354d6b745245&pid=1-s2.0-S1566253522001129-main.pdf) [https]pdf(https://drive.google.com/file/d/1qYXTT5mcOtSKSo9bXY6R_lpeID5BnILc/)
    2. Josue Obregon, Aekyung Kim, and Jae-Yoon Jung*, "RuleCOSI: Combination and Simplification of Production Rules from Boosted Decision Trees for Imbalanced Classification", Expert Systems with Applications, Vol. 126, Jul 2019, pp. 64-82. (SCIE, IF=4.292, 8%, OR/MS) [https]link(https://doi.org/10.1016/j.eswa.2019.02.012) [https]pdf(https://drive.google.com/file/d/1FwMrNQXNCo_6g0U9O52n47DEN5oURglI/view?usp=sharing)
    3. Donghyun Park, Hoonseok Park, Sangyeon Kim, Sanghyun Choo, Chang S. Nam, Sangwon Lee, and Jae-Yoon Jung*, "Spatio-temporal explanation of 3D-EEGNet for motor imagery EEG classification using permutation and saliency", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, Nov 2023, pp. 4504-4513. (SCIE, IF=4.9, 5.1%, Reh) (Ack: EEG, AIC). [https]link(https://ieeexplore.ieee.org/document/10310256/) [https]pdf(https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10310256)
  • Smart Manufacturing
    1. Young-Suk Han and Jae-Yoon Jung, "Imitation learning of job dispatching data combining classification and ranking", CAIE, submitted 241010. (SCIE, IF=6.7, 11.5%(20/169), CS/IA)
    2. Seohyun Choi, Young Ha Joo, Hoonseok Park, Younkook Kang, Ri Choe, and Jae-Yoon Jung*, "Travel Time Prediction for Line-to-line Transfers in a Semiconductor Fab: A Case Study", RCIM, under revision 240416. (SCIE, IF=10.4, 5.9%, CS/IA)
    3. Aekyung Kim, Jae-Yoon Jung*, "Multi-objective Scheduling Using Deep Reinforcement Learning, JIM, under revision 0705. (Ack: AIC, OCC)
    4. Josue Obregon and Jae-Yoon Jung*, "Rule-based Visualization of Faulty Process Conditions in the Die-casting Manufacturing", Journal of Intelligent Manufacturing, vol. 35, no. 2, Feb 2024, pp. 521-537. (SCIE, IF=8.3, 15.5%, CS/AI) (Ack: Engy, OCC). [https]doi(https://doi.org/10.1007/s10845-022-02057-1) [https]pdf(https://link.springer.com/content/pdf/10.1007/s10845-022-02057-1.pdf) [https]pdf(https://drive.google.com/file/d/1yjpCUGbqupA6AqWsd3XvMl3cUeMKtSBz/)
    5. Josue Obregon, Jihoon Hong, Jae-Yoon Jung*, "Rule-based Explanations Based on Ensemble Machine Learning for Detecting Sink Mark Defects in the Injection Moulding Process", Journal of Manufacturing Systems, Vol. 60, Jul. 2021, pp. 392-405 (SCIE, IF=8.633, 0.6%, OR/MS). [https]link(https://www.sciencedirect.com/science/article/pii/S0278612521001382?via%3Dihub)
    6. Aekyung Kim, Kyuhyup Oh, Jae-Yoon Jung*, and Bohyun Kim, "Imbalanced Classification of Manufacturing Quality Conditions Using Cost-Sensitive Decision Tree Ensembles", International Journal of Computer Integrated Manufacturing, Vol. 31, No. 8, Aug 2018, pp. 701-717. (SCIE, IF=2.090, 38%, OR/MS) [http]link(http://www.tandfonline.com/doi/full/10.1080/0951192X.2017.1407447) [http]pdf(http://www.tandfonline.com/eprint/9JwDxaSmfSsizDnrzsSC/full)
  • Smart Energy
    1. Jimin Kim, Josue Obregon, Hoonseok Park, Jae-Yoon Jung*, "Multi-step day-ahead photovoltaic power forecasting using transformer networks with pretrained recurrent neural networks", Renewable and Sustainable Energy Reviews, vol. 200, Aug 2024, 114479. (SCIE, IF=15.9, 3.3%(2/46), GSST) (Ack: Engy, AIC). [https]doi(https://doi.org/10.1016/j.rser.2024.114479) [https]pdf(https://drive.google.com/file/d/1hJVdAMS5wv9u6UhlNA2Y_rj3V2Ub0K8K/view?usp=drive_link)
    2. Josue Obregon, Yu-Ri Han, Chang Won Ho, Devanadane Mouraliraman, Chang Woo Lee*, and Jae-Yoon Jung*, "Convolutional Autoencoder-based SOH Estimation of Lithium-ion Batteries Using Electrochemical Impedance Spectroscopy", Journal of Energy Storage, Vol. 60, Apr. 2023, 106680. (SCIE, IF=8.907, 19.0%, E&F) (Ack: Engy, AIC). [https]link(https://www.sciencedirect.com/science/article/pii/S2352152X23000774) [https]pdf(https://drive.google.com/file/d/1PcnCnPpboJztMafFdJLYtpLfWpZdWUd6/)
    3. Berny Carrera, Min Kyu Sim*, and Jae-Yoon Jung, "PVHybNet: A Hybrid Framework for Predicting Photovoltaic Power Generation Using Both Weather Forecast and Observation Data", IET Renewable Power Generation, Vol. 14, No. 12, Sep. 2020, pp. 2192-2201. (SCIE, IF=3.894, 21%, EEE) [https]link(https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-rpg.2018.6174) [https]pdf(https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-rpg.2018.6174)
  • Data Mining
    1. YeonJun In and Jae-Yoon Jung*, "Simple Averaging of Direct and Recursive Forecasts via Partial Pooling Using Machine Learning", International Journal of Forecasting, Vol. 38, No. 4, Oct. 2022, pp. 1386-1399. (SSCI, IF=7.022, 6.2%(24/379), Econo) [https]link(https://www.sciencedirect.com/science/article/pii/S0169207021001813) [https]pdf(https://drive.google.com/file/d/1iwTewGKMoyxPBM1QGUUFbFjnR0V_5y7L/)
    2. Hoonseok Park and Jae-Yoon Jung*, "SAX-ARM: Deviated Event Pattern Discovery from Multivariate Time-Series Using Symbolic Aggregate Approximation and Association Rule Mining", Expert Systems with Applications, Vol. 141, Mar 2020, 112950. (SCIE, IF=5.452, 1.8%, OR/MS)
    3. Bitzel Cortez, Berny Carrera, Young-Jin Kim, and Jae-Yoon Jung*, "An Architecture for Emergency Event Prediction Using LSTM Recurrent Neural Networks", Expert Systems with Applications, Vol. 97, May 2018, pp. 315-324. (SCIE, IF=3.928, 3%, OR/MS) [http]link(http://www.sciencedirect.com/science/article/pii/S0957417417308606) [https]pdf(https://ac.els-cdn.com/S0957417417308606/1-s2.0-S0957417417308606-main.pdf?_tid=7a175d9c-e6fe-11e7-ad42-00000aab0f6b&acdnat=1513936810_8ee150967c2d415218f873f9ad50ff39)
    4. Kwanho Kim, Kyuhyup Oh, Yeong Kyu Lee, SungHo Kim, and Jae-Yoon Jung*, "An Analysis on Movement Patterns between Zones Using Smart Card Data in Subway Networks", International Journal of Geographical Information Science, Vol. 28, No. 9, Sep 2014, pp. 1781-1801. [http]pdf(http://web.khu.ac.kr/~jung/paper/Jung_IJ_2014_IJGIS.pdf)
  • Process Mining
    1. Josue Obregon, Minseok Song, and Jae-Yoon Jung*, "InfoFlow: Mining Information Flow Based on User Community in Social Networking Services", IEEE Access, Vo. 7, Apr 2019, pp. 48024-48036. (SCIE, IF=4.098, 14%, CS/IS) [https]link(https://ieeexplore.ieee.org/document/8681519?arnumber=8681519) [https]pdf(https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8681519)
    2. Jae-Yoon Jung, Kwanho Kim, Dongmin Shin, and Jonghun Park, "FlowWiki: A Wiki Based Platform for Ad-hoc Collaborative Workflows", Knowledge-Based Systems, Vol. 24, No. 1, Feb 2011, pp. 154-165. [http]pdf(http://web.khu.ac.kr/~jung/paper/Jung_IJ_201102_KBS.pdf)
    3. Jae-Yoon Jung, Chang-Ho Chin, and Jorge Cardoso, "An Entropy-based Uncertainty Measure of Process Models", Information Processing Letters, Vol. 111, No. 3, Jan 2011, pp. 135-141. [http]pdf(http://web.khu.ac.kr/~jung/paper/Jung_IJ_201101_IPL.pdf)
    4. Jae-Yoon Jung, Joonsoo Bae, and Ling Liu, "Hierarchical Clustering of Business Process Models", International Journal of Innovative Computing, Information and Control, Vol. 12, No. 5, Dec 2009, pp. 4501-4511. [http]pdf(http://web.khu.ac.kr/~jung/paper/Jung_IJ_200912_IJICIC.pdf)
    5. Jae-Yoon Jung, Wonchang Hur, Suk-Ho Kang, and Hoontae Kim, "Business Process Choreography for B2B Collaboration", IEEE Internet Computing, Vol. 8, No. 1, Jan/Feb 2004, pp. 37-45. [http]pdf(http://web.khu.ac.kr/~jung/paper/Jung_IJ_200306_IEEEIC.pdf)
  • Brain-Computer Interaction
    1. Donghyun Park, Hoonseok Park, Sangyeon Kim, Sanghyun Choo, Chang S. Nam, Sangwon Lee, and Jae-Yoon Jung*, "Spatio-temporal explanation of 3D-EEGNet for motor imagery EEG classification using permutation and saliency", IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 31, Nov 2023, pp. 4504-4513. (SCIE, IF=4.9, 5.1%, Reh) (Ack: EEG, AIC). [https]link(https://ieeexplore.ieee.org/document/10310256/) [https]pdf(https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10310256)
    2. Sanghyun Choo, Hoonseok Park, Sangyeon Kim, Donghyun Park, Jae-Yoon Jung, Sangwon Lee, and Chang S. Nam*, "Effectiveness of Multi-Task Deep Learning Framework for EEG-based Emotion and Context Recognition", Expert Systems with Applications, vol. 227, Oct 2023, 120348. (SCIE, IF=8.5, 6.4%, OR/MS) (Ack: EEG, etc.)[https]link(https://doi.org/10.1016/j.eswa.2023.120348) [https]pdf(https://www.sciencedirect.com/science/article/pii/S0957417423008503/pdfft?md5=93b0a87825134dc63c2de87b7dd63950&pid=1-s2.0-S0957417423008503-main.pdf)
    3. Sangyeon Kim, Sanghyun Choo, Donghyun Park, Hoonseok Park, Chang S. Nam, Jae-Yoon Jung, and Sangwon Lee*, "Designing an XAI Interface for BCI Experts: A Contextual Design for Pragmatic Explanation Interface Based on Domain Knowledge in a Specific Context", International Journal of Human-Computer Studies, vol. 174, Jun 2023, 103009. (SSCI, IF=5.4, 11.9%, Ergo) (Ack: EEG, etc). [https]link(https://www.sciencedirect.com/science/article/pii/S1071581923000150) [https]pdf(https://www.sciencedirect.com/science/article/pii/S1071581923000150/pdfft?md5=c43d7a6ff62416f94cb62fc20b7ce6c6&pid=1-s2.0-S1071581923000150-main.pdf)

    • [http]Full list of publications(http://iai.khu.ac.kr/wiki/wiki.php/Publications)
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