Dr. Yung-Cheol Byun

Dr. Yung-Cheol Byun received his Ph.D. and MS from Yonsei University in 1995 and 2001 respectively, and BS from Jeju National University in 1993. He worked as a special lecturer in SAMSUNG Electronics in 2000 and 2001. From 2001 to 2003, he was a senior researcher at the Electronics and Telecommunications Research Institute (ETRI). He was promoted to join Jeju National University as an assistant professor in 2003. Now, he is an associate professor in the Computer Engineering Department at the University.
His research interests include the  following areas

  • AI & machine learning
  • Pattern recognition
  • Blockchain 
  • deep learning-based application
  • Big data and knowledge discovery
  • Time series data analysis and prediction
  • mage processing and medical applications
  • Recommendation systems.
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Editorial Roles

  • Soft Computing and Machine Intelligence Journal
    Editor In Chief 
  • Energies (IF: 3.252)
    Guest Editor
    Special Issue "Machine Learning-Based Energy Forecasting and Its Applications"
  • Sensors (IF: 3.847)
    Guest Editor
    Special Issue " Machine Learning as Driving Force for Industry 4.0 and Digital Twin"

All Publications

Year Title Journal IF Download
Year Title Journal IF Download
2023 A Synthetic Data Generation Technique for Enhancement of Prediction Accuracy of Electric Vehicles Demand Sensors 3.84 Link
2022 Designing the Controller-based Urban Traffic Evaluation and Prediction Using Model Predictive Approach Applied Sciences 2.838 Link
2022 Lithium-Ion Battery Estimation in Online Framework Using Extreme Gradient Boosting Machine Learning Approach Mathematics 2.592 Link
2022 Signal Traffic Optimization Using Control Algorithm in Urban Traffic Framework Turkish Journal of Computer and Mathematics Education (TURCOMAT) Scopus Link
2022 Lithium-Ion Battery Health Prediction on Hybrid Vehicles Using Machine Learning Approach Energies 3.252 Link
2022 Improving the Road and Traffic Control Prediction Based on Fuzzy Logic Approach in Multiple Intersections Mathematics 2.592 Link
2022 Prediction of the Battery State Using the Digital Twin Framework Based on the Battery Management System IEEE Access 3.476 Link
2022 XGBoost-Based Remaining Useful Life Estimation Model with Extended Kalman Particle Filter for Lithium-Ion Batteries Sensors 3.847 Link
2022 IncepX-Ensemble: Performance Enhancement Based on Data Augmentation and Hybrid Learning for Recycling Transparent PET Bottles IEEE Access 3.47 Link
2022 Enhancement of Image Classification Using Transfer Learning and GAN-Based Synthetic Data Augmentation Mathematics 2.54 Link
2022 EEG-Based Emotion Classification Using Stacking Ensemble Approach Sensors 3.84 Link
2022 Voting Ensemble Approach for Enhancing Alzheimer’s Disease Classification Sensors 3.84 Link
2022 Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction CMC-Computers, Materials & Continua 3.86 Link
2022 Reduction of Online Fraudulent Activities in Freelancing Sites Using Blockchain and Biometric Electronics 2.69 Link
2022 An Ensemble Architecture Based on Deep Learning Model for Click Fraud Detection in Pay-Per-Click Advertisement Campaign IEEE Access 3.47 Link
2022 Optimal Photovoltaic Panel Direction and Tilt Angle Prediction Using Stacking Ensemble Learning Frontiers in Energy Research 3.85 Link
2022 Electric Kickboard Demand Prediction in Spatiotemporal Dimension Using Clustering-Aided Bagging Regressor Journal of Advanced Transportation 2.24 Link
2022 Multi-Fault Detection and Classification of Wind Turbines Using Stacking Classifier Sensors 3.84 Link
2021 Blockchain-based peer-to-peer energy trading and charging payment system for electric vehicles Sustainability 3.88 Link
2021 Improving the Performance of Single-Intersection Urban Traffic Networks Based on a Model Predictive Controller Sustainability 3.889 Link
2021 Traffic Control Prediction Design Based on Fuzzy Logic and Lyapunov Approaches to Improve the Performance of Road Intersection Processes 3.352 Link
2021 Adaptive Error Curve Learning Ensemble Model for Improving Energy Consumption Forecasting CMC-Comput. Mater. Contin 3.86 Link
2021 Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction Energies 3.25 Link
2021 Analysis of factors affecting machine learning-based energy prediction Proceedings of KIIT Conference
2021 Secure Transactions Management Using Blockchain as a Service Software for the Internet of Things Software Engineering in IoT, Big Data, Cloud and Mobile Computing, Link
2020 A Blockchain-Based Secure Image Encryption Scheme for the Industrial Internet of Things Entropy 2.73 Link
2020 A Data Verification System for CCTV Surveillance Cameras Using Blockchain Technology in Smart Cities Electronics 2.69 Link
2020 IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning Sensors 3.84 Link
2020 Machine Learning Based Hybrid System for Imputation and Efficient Energy Demand Forecasting Energies 3.25 Link
2020 Smart contract centric inference engine for intelligent electric vehicle transportation system Sensors 3.84 Link
2020 Machine learning-based approach to predict energy consumption of renewable and nonrenewable power sources Energies 3.25 Link
2020 Genetic algorithm based optimized feature engineering and hybrid machine learning for effective energy consumption prediction IEEE Access 3.47 Link
2020 Clifford Geometric Algebra-Based Approach for 3D Modeling of Agricultural Images Acquired by UAVs IEEE Access 3.47 Link
2020 Energy efficient computation offloading mechanism in multi-server mobile edge computing—an integer linear optimization approach Electronics 2.69 Link
2020 Performance Enhancement through Communication Offloading for Energy Efficiency on Mobile Cloud Computation IJSTR

Timeline

Aug 2012- Feb 2014

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University of Florida

Visiting Professor.

 2011

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Y4iT congress

Talk in University of Philippines in Manila.
2,500 students attended this Y4IT congress.

2003

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Jeju National University

Promoted to join Jeju National University as an assistant professor in 2003.

2001

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SAMSUNG Electronics

He worked as a special lecturer in SAMSUNG Electronics in 2000 and 2001

2001

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Ph.D. Computer Engineering

Yonsei University, South Korea

Contact us

Phone

0 (800) 123 45 67

Email

yungcheolbyun@gmail.com

Address

Department of Computer Engineering, Jeju National University, Jeju 63243, Korea

Working Hours

9:00 - 18:00

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