Publication trends (based on Research Studies until 2025. 08)

Book

• Hyunsoo Lee, “System Optimization”, ISBN 979-11-91003-08-6, KIT Press, Gumi, Korea, 2021
• Backchoon Sung, Dokyong Kim, Ohoon Kwon, Hyunsoo Lee and Siyoung Lim, “Textbook of the 4th Industrial Revolution”, ISBN 979-11-96636-91-3, Mirang Communication, Daegu, Korea, 2020
• Hyunsoo Lee, “Computer Aided Design Theory and Practice for 3D Printing”, ISBN 978-89-98338-67-1 (93550), ChaosBook, Seoul, Korea, 2015
• Taesung Kim and Hyunsoo Lee, “Operations Management Information Systems”, ISBN 978-89-98338-51-0 (93200), ChaosBook, Seoul, Korea, March, 2014
• Hyunsoo Lee, “Android Programming and Mobile UX Design”, ISBN 978-89-6220-168-0 (93560), Bomungak, Seoul, Korea, February, 2013

 

Book chapters

• Hyunsoo Lee and Amarnath Banerjee, “Design, Simulation and Dynamic Control of Large Scale Manufacturing Process with Different Forms of Uncertainties”, Contemporary Issues in System Science and Engineering, Mengchu Zhou,(Eds.), IEEE Press Series on Systems Science and Engineering, Hoboken, NY, 2015

 

Patent

• KEPCO E&C and Hyunsoo Lee, “Building energy control system ”, Korean Intellectual Property Office, Patent Registration No. 10-2744374, December,2024
• KEPCO E&C and Hyunsoo Lee, “A system and method for managing scheduling of power plant based on artificial neural network ”, Korean Intellectual Property Office, Patent Registration No. 1027007120000, August,2024
• Taesung Kim and Hyunsoo Lee, “Disaster Safety Management System for Smart Factory ”, Korean Intellectual Property Office, Patent Registration No. 10-2019-0140753, December,2019
• Taesung Kim, Woochang Cha and Hyunsoo Lee, “System for Providing Traffic Accident Information ”, Korean Intellectual Property Office, Patent Registration No. 1016820480000, November, 2016
• Taesung Kim, Sungho Jang, Jonghwan Lee and Hyunsoo Lee, “Patch for Fever Alleviation”, Korean Intellectual Property Office, Patent Registration No. 1013630850000, January, 2014
• Sungho Jang , Taesung Kim, Hyunsoo Lee and Suna Kim, “Heating and Cooling System for Personal Clothing Microclimate and the Clothing using the System”, Korean Intellectual Property Office, Patent Registration No. 1013440330000, December, 2013

 

International journal papers (Selected) - [Full Publication]

• Sangmin Park, and Hyunsoo Lee, “Predictive supply chain disruption control framework using casual network-based multi-stream deep learning ”, Computers & Industrial Engineering (SCI), Vol. 207, DOI: https://doi.org/10.1016/j.cie.2025.111312, 2025.
• Eunseo Oh, and Hyunsoo Lee, “Quantum mechanics-based deep learning framework considering near-zero variance data ”, Applied Intelligence (SCIE), Vol. 2024, DOI: https://doi.org/10.1007/s10489-024-05465-3, 2024.
• Jaeuk Jang, and Hyunsoo Lee, “Effective hydrogen supply chain management framework considering nonlinear multi-stage process uncertainties ”, Applied Energy(SCIE), Vol. 367, DOI: https://doi.org/10.1016/j.apenergy.2024.123328, 2024.
• Eunseo Oh, and Hyunsoo Lee, “Quantum mechanics-based missing value estimation framework for industrial data ”, Expert Systems With Applications (SCIE), Vol 236, DOI: https://doi.org/10.1016/j.eswa.2023.121385, 2024.
• Hyunsoo Lee, “Physics-based cooperative robotics digital twin framework for contactless delivery motion planning”, International Journal of Advanced Manufacturing Technology (SCIE), DOI:https://doi.org/10.1007/s00170-023-11956-3, 2023, pp.1-16.
• Jaeuk Jang, and Hyunsoo Lee, “Spatial graph structure estimation of nanoparticles using centroid-to-contour distance analysis and deep encoder framework ”, Journal of Nanoparticle Research (SCIE), Vol. 25, Article No. 117, 2023, pp. 1-16.
• Ahtesham Bakht, Alarm Nawaz, Moonyoung Lee, and Hyunsoo Lee, “Ingredient analysis of biological wastewater using hybrid multi-stream deep learning framework ”, Computers & Chemical Engineering (SCIE), Vol. 168, Article No. 108038, 2022,pp. 1-15.
• Hyunsoo Lee, Heungjo An, and Dong-Wook Lee, “Time-staged Photoelastic Image Prediction using Multi-stage Convolutional Autoencoders ”, Engineering Applications of Artificial Intelligence (SCIE),  Vol. 16, Article No. 105265, 2022, pp. 1-14.
• Maryam Khairunissa and Hyunsoo Lee, “Effective Quantum Mechanics Embedded Nanoparticle Occlusion Analysis Framework ”, Journal of Nanoparticle Research (SCIE),  Vol. 24, Article No. 133, 2022, pp. 1-20.
• Eunseo Oh, and Hyunsoo Lee, “Effective Route Generation Framework using Quantum Mechanism-based Multi-directional and Parallel Ant Colony Optimization ”, Computers & Industrial Engineering (SCI),  Vol. 169, Article No. 108308, 2022, pp. 1-12.
• Hyunsoo Lee, Seong Dae Kim, and Mohammad Aman Ullah Al Amin, “Control Framework for Collaborative Robot using Imitation Learning-based Teleoperation from Human Digital Twin to Robot Digital Twin ”, Mechatronics (SCI),  Vol. 85, No. 2022, pp. 1-11.
• Hyunsoo Lee, Seokyoun Han, Keejun Park, Hoyoung Lee and Taesoo Kwon, “Real-time Hybrid Deep Learning-based Train Running Safety Prediction Framework of Railway Vehicle ”, Machines (SCIE), Vol. 9, No. 7, 2021, pp.1-18.
• Firda Rahmadani and Hyunsoo Lee, “Hybrid Deep Learning-based Epidemic Prediction Framework of COVID-19: South Korea Case ”, Applied Sciences (SCIE), Vol. 10, No. 23, 2020, pp.1-21.
• Hyunsoo Lee, Seokyoun Han and Keejun Park, “Generative Adversarial Network-based Missing Data Handling and Remaining Useful Life Estimation for Smart Train Control and Monitoring Systems ”, Journal of Advanced Transportation (SCIE) , Vol. 2020, No. 1, 2020, pp. 1-15.
• Jinbae Kim and Hyunsoo Lee, “Cooperative Multi-agent Interaction and Evaluation Framework considering Competitive Networks with Dynamic Topology Changes ”, Applied Sciences (SCIE) , Vol. 10, No. 17, 2020,  pp. 1-16.
• Eunseo Oh and Hyunsoo Lee, “An Imbalanced Data Handling Framework for Industrial Big Data using Gaussian Process Regression-based Generative Adversarial Network ”, Symmetry (SCIE) , Vol. 12, No. 4, 2020, pp. 1-19.
• Hyunsoo Lee, “Development of Real-Time Sketch-based On-the-Spot Process Modeling and Analysis System ”, Journal of Manufacturing Systems (SCIE), Vol. 54, No. C, 2020, pp. 215-226. 
• Hyunsoo Lee, “Development of Sustainable Recycling Investment Framework considering Uncertain Demand and Nonlinear Recycling Cost ”, Sustainability (SCIE) , Vol. 11, No. 14, 2019. pp.1-18.
• Hyunsoo Lee, “Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers using Industrial Internet of Things and Cloud System ”, Processes (SCIE) , Vol. 7, No. 127, 2019, pp. 1-18.
• Hyunsoo Lee and Woochang Cha, “Virtual Reality based Ergonomic Modeling and Evaluation Framework for Nuclear Power Plant Operation and Control ”, Sustainability (SCIE) , Vol. 11, No. 9, 2019, pp. 1-16.
• Hyunsoo Lee, “Real-time Manufacturing Modeling and Simulation Framework using Augmented Reality and Stochastic  Network Analysis ”, Virtual Reality (SCIE), Vol. 23, No. 1, 2019, pp. 85-99.
• Sanghyun Choo and Hyunsoo Lee , “Learning Framework of Multimodal Gaussian-Bernoulli RBM Handling Real-value Input Data”, Neurocomputing (SCIE), Vol. 275, No. 1, 2018, pp. 1813-1822.
• Hyunsoo Lee, “Framework and Development of Fault Detection Classification using IoT Device and Cloud Environment”, Journal of Manufacturing Systems (SCIE), Vol. 43, No. 2, 2017, pp. 257-270.
• Hyunsoo Lee, “Human Crowd Evacuation Framework and Analysis using Look-ahead based Reinforcement Learning Algorithm”, International Journal of Digital Human, Vol. 1, No. 3, 2016, pp. 248-262.
• Hyunsoo Lee, “Cooperative NURBS Surface Modeling Framework using Partial Control Algorithm and Concurrent Protocol”, International Journal of Collaborative Enterprise, Vol. 4, No. 4, December, 2014, pp. 320-336.
• Taesung Kim, Saejae Lee and Hyunsoo Lee, “Topology Modeling and Dynamic Reconstruction for NP-Complete Complexity Problem Embedded Supply Chain Network”, International Journal of Logistics and SCM Systems, Vol. 7, No. 1, September, 2013, pp.39-46.
• HyunSoo Lee and Amarnath Banerjee, “An Executable Modelling and Simulation Framework for NP-Complete Problems and Different Forms of Uncertainties”, International Journal of Services Operations and Informatics (SCOPUS), Vol. 7, No. 1, August, 2012, pp.1-17.
• HyunSoo Lee and Amarnath Banerjee, “Executable Design and Control Framework Using Reconfigurable Manufacturing Holons and Its Evolution Algorithm”, International Journal of Production Research (SCI), Vol. 49, No. 5, March, 2011, pp.  1405-1423.
• Hyun Soo Lee and Amarnath Banerjee, “A self-configurable large-scale virtual manufacturing environment for collaborative designers”, Virtual Reality (SCIE), Vol. 15, No. 1, March, 2011, pp.21-40.
• Hyun Soo Lee, Jonghyun Kim and Amarnath Banerjee, “Collaborative Intelligent CAD Framework Incorporating Design History Tracking Algorithm”, Computer-Aided Design (SCI), Vol. 42, No. 12, December, 2010, pp. 1125-1142.
• Hyun Soo Lee, Josie R. Williams, Kathy Mechler, Tracy L. Adams, R. Kim Clay, Tammy Wilemon, Robert Morrow and Amarnath Banerjee, “Streamlining Physician Peer Review Process and Capacity Prediction Using Simulation”, International Journal of Collaborative Enterprise, Vol. 1, No. 3/4, 2010, pp. 273-292.
• Hyun Soo Lee, Bikram Sharda and Amarnath Banerjee, “A Closed-loop Control Architecture for CAM Accounting for Shop Floor Uncertainties”, Journal of Manufacturing Systems (SCIE), Vol. 27, No. 4, 2008, pp. 166-175.
• S.H. Suh, D.H. Chung, B.E. Lee, J.H. Cho, S.U. Cheon, H.D. Hong and H.S. Lee, “Developing an Integrated STEP-Compliant CNC Prototype”, Journal of Manufacturing Systems (SCIE), Vol. 21,No. 5, 2002, pp. 350-362.

International proceedings & Presentation (Within 5 years) - [Full Publication]

• Hyunsoo Lee and Amarnath Banerjee, “Quantum embedding framework of industrial data for quantum deep learning ”, Winter Simulation Conference 2023, San Antonio, Texas, USA, December 10-13, 2023, pp. 2956-2965. 
• Eunseo Oh and Hyunsoo Lee , “Diesel engine defect prediction framework using Quantum Mechanics-based neural network ”, INFORMS Annual Meeting (INFORMS 20223), Phoenix, Arizona, USA, October 18, 2023, [Presentation]
• Hyunsoo Lee , “Quantum Deep Learning-based Fault Detection and Classification ”, INFORMS Annual Meeting (INFORMS 2022), Indianapolis Convention Center, Indianapolis, USA, October 18, 2022, [Presentation]
• Eunseo Oh and Hyunsoo Lee , “Hydrogen Liquefaction Process Specific Energy Consumption Prediction Framework using Quantum Mechanics-based Deep Learning ”, INFORMS Annual Meeting (INFORMS 2022), Indianapolis Convention Center, Indianapolis, USA, October 17, 2022, [Presentation]
• Seongdae Kim, Hyunsoo Lee and Mohammad Aman UllahAl Amin , “Human Motion to Collaborative Two-arm Robot Through Digital Twin Models ”, ASME 2021 International Mechanical Engineering Congress and Exposition (IMECE2021), Virtual Conference, USA, November 2, 2021, pp. 70721.

Domestic Journal papers (Within 5 years) - [Full Publication]

• Eunseo Oh and Hyunsoo Lee, “Gas turbine energy yield prediction framework using neural network based on quantum mechanics”, Journal of Korean Institute of Intelligent Systems, 2024, [Accepted].    
• Junpyo Hong and Hyunsoo Lee , “Quantum dense coding transfer framework of phase damping channel system using weak measurement and correction rotation ”, Journal of the Korean Institute of Industrial Engineers, Vol. 50, No. 3, 2024, pp. 202-210.    
• Jaeuk Jang and Hyunsoo Lee, “Hydrogen supply chain network operation framework using Nonlinear Multi-stage Stochastic Programming with weighted scenario method”, Journal of Korean Institute of Intelligent Systems, Vol. 34, No. 2, 2024, pp. 174-181.    
• Eunseo and Hyunsoo Lee, “Quantum mechanics-based fault prediction framework of semiconductor manufacturing processes ”, Journal of Korean Institute of Intelligent Systems, Vol. 33, No. 5, 2023, pp. 399-405.    
• Jaeuk Jang and Hyunsoo Lee, “Three-dimensional Nanoparticle Structure Estimation Framework using Auto Encoder-based Spatial Graph ”, Journal of Korean Institute of Intelligent Systems, Vol. 33, No. 2, 2023, pp. 173-180.    
• Eunseo Oh and Hyunsoo Lee, “Missing Value Estimation Framework using Quantum Mechanics-based Generative Adversarial Network ”, Journal of Korean Institute of Intelligent Systems, Vol. 32, No. 6, 2022, pp. 457-463.
• Ahtesham Bakht, Alam Nawaz, Moonyoung Lee and Hyunsoo Lee, “Hybrid Multi-stream Deep Learning-based Nutrient Estimation Framework in Biological Wastewater Treatement ”, Journal of Korean Institute of Intelligent Systems, Vol. 32, No. 3, 2022, pp. 209-217.    
• Hyunsoo Lee, Eunseo Oh, Byungun Yoon and Ki-Tae Shin , “Industrial Engineering Sustainability Analysis focusing on Programs and Affiliated Professors ”, Journal of the Korean Institute of Industrial Engineers, Vol. 48, No. 3, 2022, pp. 289-297.   
• Ahtesham Bakht and Hyunsoo Lee, “Deep Learning Framework for Spatial Crowdedness Estimation and Comparison Analysis with Machine Learning ”, Journal of Korean Institute of Intelligent Systems, Vol. 32, No. 1, 2022, pp. 76-85.   
• Rahmawati and Hyunsoo Lee, “Denosied Concrete Crack Detection Framework using Deep Auto Encoder ”, Journal of Korean Institute of Intelligent Systems, Vol. 31, No. 6, 2021, pp. 519-526.   
• Youngki Jo and Hyunsoo Lee, “Electricity Demand Forecasting Framework using Modified Attention-based LSTM ”, Journal of Korean Institute of Intelligent Systems, Vol. 30, No. 3, 2020, pp. 242-250.   
• Firda Rahmadani and Hyunsoo Lee, “ODE-based Epidemic Network Simulation of Viral Hepatitis A and Kernel Support Vector Machine based Vaccination Effect Analysis  ”, Journal of Korean Institute of Intelligent Systems, Vol. 30, No. 2, 2020, pp. 106-112.   

Domestic proceedings (Within 2 years) - [Full Publication]

• Adela Safitri Novrizal and Hyunsoo Lee , “Disruption-responsive stochastic programming control framework of the cement industry  ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session H7, H7.1, pp. 1-24, Jeju, June 20, 2025.    
• Tagir Salakhov and Hyunsoo Lee , “Uncertain trajectory prediction using GAT and KAN  ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session E6, E6.2, pp. 1-24, Jeju, June 19, 2025.    
• Jinhwan Kim and Hyunsoo Lee , “Federated learning framework using correlation-based attention mechanism in imbalanced data environment   ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session E6, E6.1, pp. 1-24, Jeju, June 19, 2025.    
• Lutfiana Sausan and Hyunsoo Lee , “Task offloading in mobile edge computing using deep reinforce learning ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session E6, E6.4, pp. 1-24, Jeju, June 19, 2025.    
• Adela Safitri Novizal and Hyunsoo Lee , “Disruption-based stochastic programming control framework for the cement industry ”, Proceedings of KIIS Spring Conference,Vol. 35, No. 1, pp. 99-100, Gumi, April 25, 2025.    
• Tagir Salakhov and Hyunsoo Lee , “Stochastic trajectory prediction framework for human-driven vehicles in mixed traffic environments ”, Proceedings of KIIS Spring Conference,Vol. 35, No. 1, pp. 125-126, Gumi, April 25, 2025.    
• Lutfiana Sausan and Hyunsoo Lee , “Quantum scheduling: Grover algorithm for graph coloring with constraints ”, Proceedings of KIIS Spring Conference,Vol. 35, No. 1, pp. 94-95, Gumi, April 25, 2025.    
• Jinhwan Kim and Hyunsoo Lee , “Federated learning framewwork using loss-based dynamic attention mechanism ”, Proceedings of KIIS Spring Conference,Vol. 35, No. 1, pp. 34-35, Gumi, April 25, 2025.    
• Raghda Mansouur Kamel Noureldin and Hyunsoo Lee , “Modeling and Estimation of EV Battery Thermal System Dynamics using a Physics Inspired Neural Network Approach ”, Proceedings of KIIS Spring Conference,Vol. 35, No. 1, pp. 31-32, Gumi, April 25, 2025.    
• Raghda Mansouur Kamel Noureldin and Hyunsoo Lee , “Electric vehicle battery performance analysis and enhancement framework uusing physics-informed neuural network ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session F11, F11.4, pp. 1-24, Yeosu, May 03, 2024.    
• Sangmin Park and Hyunsoo Lee , “Enhancing supply chain resilience using graph-based multi-stream deep learning and casual networks ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session H05, H05.1, pp. 1-24, Yeosu, May 03, 2024.    
• Jaeuk Jang and Hyunsoo Lee , “Stochastic optimization of the hydrogen supply chain network considering progressive uncertainty and solution methodology based on scenario sampling ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session H01, H01.2, pp. 1-24, Yeosu, May 03, 2024.    
• Jinhwan Kim and Hyunsoo Lee , “Multiple industrial edge-based federated learning framework uusing multi-stream deep learning ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session C02, C2.6, pp. 1-24, Yeosu, May 02, 2024.    
• Eunseo Oh and Hyunsoo Lee , “Efficient path generation framework using quantuum computing-based HHL and Grover algorithm ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session A01, A1.1, pp. 1-24, Yeosu, May 02, 2024.    
• Lutfiana Sausan and Hyunsoo Lee , “Enhanced quantum approximate algorithm for the traveling salesmand problem ”, Proceedings of KIIE Spring Conference,Vol. 1, No. 1, Session A10, A10.3, pp. 1-24, Yeosu, May 02, 2024.    
• Hyunsoo Lee , “BWhen intelligent systems meet quantum computing  ”, Proceedings of Korean Institute of Intelligent Systems, 2024, Vol. 34, No. 1, 2024, pp. 154-156.    
• Raghda Mansour Kamel Noureldin and Hyunsoo Lee , “Battery pack control and simulation using machine learning-based EV battery pack enhancement ”, Proceedings of Korean Institute of Intelligent Systems, 2024, Vol. 34, No. 1, 2024, pp. 212-213.    
• Sangmin Park and Hyunsoo Lee , “A graph-based multi-stream framework for responding to dynamic supply chain changes ”, Proceedings of Korean Institute of Intelligent Systems, 2024, Vol. 34, No. 1, 2024, pp. 115-116.    
• Jaeuk Jang and Hyunsoo Lee , “Hydrogen supply chain design considering uncertainties in hydrogen demand and renewable energy supply and sampling based modified Benders decomposition ”, Proceedings of Korean Institute of Intelligent Systems, 2024, Vol. 34, No. 1, 2024, pp. 146-147.    
• Jinhwan Kim and Hyunsoo Lee , “Enhanced federated learning framework in distrubuted industrial environments utilizing multi-output stream deep learning ”, Proceedings of Korean Institute of Intelligent Systems, 2024, Vol. 34, No. 1, 2024, pp. 113-114.