| 2026 | SAC | DyCAD: Dynamic Collaborative Online Anomaly Detection for Multivariate Time Series using Adaptive Clustering. | Ming-Chang Lee, Jia-Chun Lin, Sokratis K. Katsikas |
| 2025 | ICAART | RePAD3: Advanced Lightweight Adaptive Anomaly Detection for Univariate Time Series of Any Pattern. | Ming-Chang Lee, Jia-Chun Lin, Sokratis K. Katsikas |
| 2024 | IC3K | Comparative Analysis of Real-Time Time Series Representation Across RNNs, Deep Learning Frameworks, and Early Stopping. | Ming-Chang Lee, Jia-Chun Lin, Sokratis K. Katsikas |
| 2024 | ICICS | Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-Time Lightweight Time Series Anomaly Detection. | Ming-Chang Lee, Jia-Chun Lin, Sokratis K. Katsikas |
| 2024 | ICICS | Investigating the Privacy Risk of Using Robot Vacuum Cleaners in Smart Environments. | Benjamin Ulsmg, Jia-Chun Lin, Ming-Chang Lee |
| 2024 | ICPRAM | Evaluation of K-Means Time Series Clustering Based on Z-Normalization and NP-Free. | Ming-Chang Lee, Jia-Chun Lin, Volker Stolz |
| 2024 | SEC | GAD: A Real-Time Gait Anomaly Detection System with Online Adaptive Learning. | Ming-Chang Lee, Jia-Chun Lin, Sokratis K. Katsikas |
| 2023 | COMPSAC | NP-Free: A Real-Time Normalization-free and Parameter-tuning-free Representation Approach for Open-ended Time Series. | Ming-Chang Lee, Jia-Chun Lin, Volker Stolz |
| 2023 | FIT | An Explainable Deep Learning-based Approach for Multivariate Time Series Anomaly Detection in IoT. | Aafan Ahmad Toor, Jia-Chun Lin, Ernst Gunnar Gran, Ming-Chang Lee |
| 2023 | ICSoft | Impact of Deep Learning Libraries on Online Adaptive Lightweight Time Series Anomaly Detection. | Ming-Chang Lee, Jia-Chun Lin |
| 2023 | ICSoft | RoLA: A Real-Time Online Lightweight Anomaly Detection System for Multivariate Time Series. | Ming-Chang Lee, Jia-Chun Lin |
| 2021 | AINA | How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection? | Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran |
| 2021 | COMPSAC | SALAD: Self-Adaptive Lightweight Anomaly Detection for Real-time Recurrent Time Series. | Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran |
| 2020 | AINA | DALC: Distributed Automatic LSTM Customization for Fine-Grained Traffic Speed Prediction. | Ming-Chang Lee, Jia-Chun Lin |
| 2020 | AINA | RePAD: Real-Time Proactive Anomaly Detection for Time Series. | Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran |
| 2020 | COMPSAC | ReRe: A Lightweight Real-Time Ready-to-Go Anomaly Detection Approach for Time Series. | Ming-Chang Lee, Jia-Chun Lin, Ernst Gunner Gan |
| 2020 | EuroPar | Distributed Fine-Grained Traffic Speed Prediction for Large-Scale Transportation Networks Based on Automatic LSTM Customization and Sharing. | Ming-Chang Lee, Jia-Chun Lin, Ernst Gunnar Gran |
| 2019 | ICCD | Adaptive Write Interference Management with Efficient Mapping for Shingled Recording Disks. | Ming-Chang Lee, Li-Pin Chang, Sung-Ming Wu, Wei-Shang Yui |
| 2018 | AINA | EasyChoose: A Continuous Feature Extraction and Review Highlighting Scheme on Hadoop YARN. | Ming-Chang Lee, Jia-Chun Lin, Olaf Owe |
| 2018 | AINA | Modeling and Simulation of Spark Streaming. | Jia-Chun Lin, Ming-Chang Lee, Ingrid Chieh Yu, Einar Broch Johnsen |
| 2016 | FASE | ABS-YARN: A Formal Framework for Modeling Hadoop YARN Clusters. | Jia-Chun Lin, Ingrid Chieh Yu, Einar Broch Johnsen, Ming-Chang Lee |
| 2015 | COMPSAC | ReMBF: A Reliable Multicast Brute-Force Co-allocation Scheme for Multi-user Data Grids. | Ming-Chang Lee, Fang-Yie Leu, Ying-Ping Chen |
| 2014 | AINA | Cache Replacement Algorithms for YouTube. | Ming-Chang Lee, Fang-Yie Leu, Ying-Ping Chen |
| 2014 | ICMLC | Inference and diagnosis model based on Bayesian network and rough sets theory. | Jui-Fang Chang, Jung-Fang Cheng, Ming-Chang Lee |
| 2013 | AINA | Deriving Job Completion Reliability and Job Energy Consumption for a General MapReduce Infrastructure from Single-Job Perspective. | Jia-Chun Lin, Fang-Yie Leu, Ming-Chang Lee, Ying-Ping Chen |
| 2009 | ICA3PP | A Divide-and-Conquer Strategy and PVM Computation Environment for the Matrix Multiplication. | Ming-Chang Lee |
| 2005 | KES | Statistical Data Analysis for Software Metrics Validation. | Ming-Chang Lee |