Recent News

(2026.March)

해킹 탐지를 위한 AI 기반 뇌파 인증 프로토콜 개발

  • 발표저널: Biocybernetics and Biomedical Engineering

    (SCI(E) 저널 Q1 등급 (Top-Tier); 공동1저자)

  • 논문명: "AI-Powered Computer Interface Using Evoked Potentials for XR Biometric Authentication and Individual Neural Profiling"

(2026.April)

동공 트래킹을 위한 차세대 양자 컴퓨팅 뉴로모픽 AI 반도체 개발

  • 발표저널: ACS Nano

    (나노 과학 분야 세계 최상위 권위지, 공동1저자)

  • 논문명: "Event-Driven Neuromorphic Gaze Decoding via e-Skin Electrooculography"

(2026.Aug; Accepted)

로그 데이터 품질 관리를 위한 웹기반 AI 툴 발표

  • 발표저널: Journal of Data and Information Quality

    (AI - 데이터 품질 분야 Top-Tier SCI(E) 저널; 공동저자)

  • 논문명: "PraeclarusPDQ: A Reference Architecture for Process Data Quality Management"

(2026.May)

차세대 로그 데이터 OCED에 대한 8개 오류 패턴 세계 최초 발표

  • 발표저널: Information Systems

    (정보시스템 - 프로세스 마이닝 분야 Top-Tier SCI(E) 저널; 공동저자)

  • 논문명: "Object-Centric Event-Data Imperfection Patterns"

Publications

International peer-reviewed Conferences and Workshops

[C13] Hassan Shayan, Lakshy Chaudhary, Jonghyeon Ko, Han-Gue Jo, Zero-Shot Perception Modules for Robotic Manipulation: A Comparative Study Across Open-Weights Vision-Language Models. The 15th International Conference on Smart Media & Applications (2026)

[C12] Youngjin Kim, Marco Comuzzi, Moe Wynn and Jonghyeon Ko, A Predictive Process Monitoring Framework Leveraging Enabled Activities via Translucent Event Logs. ASPAI Conference (2026)

[C11] J. Ko*, M. Wynn, M. Comuzzi, F. Maggi, A Reinforcement Learning Framework for Event Log Anomaly Detection and Repair. In International Conference on Process Mining (2025)

[C10] Comuzzi, M., Kim, S., Ko, J., Salamov, M., Cappiello, C., & Pernici, B. (2024). On the Impact of Low-Quality Activity Labels in Predictive Process Monitoring. In International Conference on Process Mining (pp. 201-213).

[C9] J. Ko, F. Maggi, M. Montali, R. Penaloza, and R. pereira (2023) “Plan Recognition as Probabilistic Trace Alignment”, 5th International Conference on Process Mining (ICPM 2023).

[C8] J. Ko,A. Gianola, F. Maggi, M. Montali, and S. Winkler (2023) “Approximating Multi-Perspective Trace Alignment Using Trace Encodings”, 21stInternationalConferenceonBusinessProcessManagement(BPM2023).

[C7] J. Ko*and M. Comuzzi (2022) “Pattern-based Reconstruction of Anomalous Traces in Business Process Event Logs”, In: International Workshop on Computational Intelligence for Process Mining (CI4PM) co-located with the IEEE World Congress on Computational Intelligence (WCCI 2022), p. 18-22.

[C6] J. Ko*and M. Comuzzi (2021) “Business Process Event Log Anomaly Detection based on Statistical Leverage”, Proc. 1th ITalian forum on Business Process Management held in conjunction with BPM 2021.

[C5] J. Ko*and M. Comuzzi (2020) “Online anomaly detection using statistical leverage for streaming business process events”, In: Process Mining Workshops: ICPM 2020 International Workshops, Padua, Italy, October 5–8, 2020, Revised Selected Papers. Springer Nature, 2021. p. 193.

[C4] J. Ko*, J. Lee, and M. Comuzzi (2020) “AIR-BAGEL: An Interactive Root cause-Based Anomaly Generator for Event Logs”, 2ndInt.Conf.onProcessMining(ICPM)–DemonstrationTrack,pp.35-38

[C3] J. Kim, J. Ko, and S. Lee (2019) “Process discovery and deviation analysis of purchase order handling process”, 9thInternationalBusinessProcessIntelligenceChallenge.

[C2] M. Comuzzi, J. Ko, and S. Lee (2019) “Predicting Outpatient Process Flows to Minimise the Cost of Handling Returning Patients: A Case Study”, Proceedings of the 2nd International Workshop on Process-Oriented Data Science for Healthcare 2019 in conjunction with International Conference on Business Process Management- PODS4H19, pp 557-569.

[C1] J. Ko*and M. Comuzzi (2017) “Fuzzy Analytic Network Process for evaluating ERP post-implementation alternatives”, 2017 IEEE International Conference on Fuzzy Systems - FUZZ-IEEE 2017, pp. 1-6.

International Journals (first/corresponding author with *)

(D1=JCR Top 10% and Q1=Top 25% in Red)

[J17] J. Ko* et al. (Under review) Non-Contact Neuromorphic Emotion Inference via Gaze Interaction, Journal: ACS Nano (IF: 17.3, JCR D1-상위 6%)

[J16] M. Comuzzi, S. Kim,J. Ko, C. Cappiello, M. Salamov, B. Pernici. (Under review) On the Impact of Low-Quality Activity Labels on Data-Driven Process Analytics, Journal: International Journal of Data Science and Analytics (IF: 2.9, JCR Q3)

[J15] S. Sadeghianasl, D. Fischer, M. Wynn, …, J. Ko. (2026) PraeclarusPDQ: A Reference Architecture for Process Data Quality Management, Journal: Journal of Data and Information Quality (IF: 5.0, JCR Q2)

[J14] S. Sadeghianasl, M. Wynn, R. Andrews, W. Aalst, J. Ko. (2026) Object-Centric Event-Data Imperfection Patterns, Journal: Information Systems (IF: 4.0, JCR Q2)

[J13] S. Jeong, H. W. Ko, J.-H. Kang, J. Ko* (co-first), …, and S. Mun.(2026) Event-Driven Neuromorphic Gaze Decoding via e-Skin Electrooculography, Journal: ACS Nano (IF: 17.3, JCR D1-상위 6%)

[J12] S. Jeong, J. Ko* (co-first), S. Park, J. Ha, M. S. Chae, L. Kim, S. Mun.(2026) AI-Powered Computer Interface Using Evoked Potentials for XR Biometric Authentication and Individual Neural Profiling, Journal: Biocybernetics and Biomedical Engineering (IF: 6.6, JCR Q1)

[J11] J. Ko*, M. Comuzzi, F. Maggi. (2025) Detecting and Repairing Anomaly Patterns in Business Process Event Logs, Journal: Data & Knowledge Engineering (IF: 3.9, JCR Q2)

[J10] S. Mun, S. Jeong, J. Ko, J. Kang, S. Bae, Y. Choi. (2025), Advanced AI computing enabled by 2D material-based neuromorphic devices, Journal: npj Unconventional Computing – Nature

[J9] M. Comuzzi, J. Ko, F. Maggi. (2025) A Language to Model and Simulate Data Quality Issues in Process Mining, Journal of Data and Information Quality (IF: 5.0, JCR Q2)

[J8] Gianola, A., Ko, J., Maggi, F. M., Montali, M., & Winkler, S. (2025). Approximate conformance checking: Fast computation of multi-perspective, probabilistic alignments. Information Systems, 129, 102510. (IF: 4.0, JCR Q2)

[J7] O. Yessenbayev, D. C. D. Nguyen, T. Jeong,K. J.Kang,H. R.Kim, J.Ko, ... & Comuzzi, M. (2024). Combining blockchain and IoT for safe and transparent nuclear waste management: A prototype implementation. Journal of Industrial Information Integration, 39, 100596. (IF: 11.2, JCR D1-상위 1%)

[J6] S. Jeong*,J.Ko, S. Lee,J.Kang, Y. Kim,S. Y.Park & S. Mun. (2024). Optimizing lane departure warning system towards AI-centered autonomous vehicles. Sensors, 24(8), 2505. (IF: 4.0, JCR Q2)

[J5] J. Ko*and M. Comuzzi (2023) “A Systematic Review of Anomaly Detection for Business Process Event Logs”, Business & Information Systems Engineering, 65(4), 441-462. (IF: 12.2, JCR D1-상위 1%)

[J4] J. Ko*and M. Comuzzi (2022) “Keeping our rivers clean: Information-theoretic online anomaly detection for streaming business process events”, Information Systems, 101894. (IF: 4.0, JCR Q2)

[J3] J. Ko*and M. Comuzzi (2021) “Detecting anomalies in business process event logs using statistical leverage”, Information Sciences, 549, 53-67. (IF: 5.9, JCR D1-상위 5%)

[J2] B. Tama, M. Comuzzi and J. Ko(2020) “An empirical investigation of different classifiers, encoding and ensemble schemes for next event prediction using business process event logs”, ACM Transactions on Intelligent Systems and Technology, 11(6), 1-34. (IF: 10.7, JCR D1-상위 9%)

[J1] H. Nguyen, S. Lee, J. Kim, J. Koand M. Comuzzi (2019) “Autoencoders for Improving Quality of Process Event Logs”, Expert Systems with Applications, 131, 132-147. (IF: 9.4, JCR Q1)