Meng-Chieh (Jeremy) Lee

I am an Applied Scientist at Amazon Web Services (AWS). I received my Ph.D. in Computer Science from Carnegie Mellon University, advised by Professor Christos Faloutsos. My current research interests include self-evolving agents, multi-agent orchestration, and retrieval-augmented generation. Please see more in my CV.

News:

• (12/20/2024) Our paper “HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases” has been accepted at ACL 2025!
• (12/20/2024) Our paper “End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection” has been accepted at SDM 2025!
• (01/27/2024) Our papers “NetEffect: Discovery and Exploitation of Generalized Network Effects” and “DiffFind: Discovering Differential Equations from Time Series” have been accepted at PAKDD 2024!
• (01/23/2024) Our paper “Descriptive Kernel Convolution Network with Improved Random Walk Kernel” has been accepted at WWW 2024!
• (01/16/2024) Our paper “NetInfoF Framework: Measuring and Exploiting Network Usable Information” has been accepted for spotlight presentation at ICLR 2024! The blogpost can be found here!

Refereed Publications:

1. Lee, M.C., Zhu, Q., Mavromatis, C., Han, Z., Adeshina, S., Ioannidis, V.N., Rangwala, H., Faloutsos, C., “HybGRAG: Hybrid Retrieval-Augmented Generation on Textual and Relational Knowledge Bases”. Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
2. Deforce, B., Lee, M.C., Baesens, B., Serral Asensio, E., Yoo, J., and Akoglu, L., “TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection”. SIAM International Conference on Data Mining (SDM), 2025.
3. Lee, M.C., Shekhar, S., Yoo, J., and Faloutsos, C., “Discovery and Exploitation of Generalized Network Effects”. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.
4. Posam, L., Shekhar, S., Lee, M.C., and Faloutsos, C., “DiffFind: Discovering Differential Equations from Time Series”. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.
5. Lee, M.C.*, Zhao, L.*, Akoglu, L., “Descriptive Kernel Convolution Network with Improved Random Walk Kernel”. ACM Web Conference (WWW), 2024.
6. Lee, M.C., Yu, H., Zhang, J., Ioannidis, V.N., Song, X., Adeshina, S., Zheng, D., and Faloutsos, C., “NetInfoF Framework: Measuring and Exploiting Network Usable Information”. International Conference on Learning Representations (ICLR), 2024. Spotlight.
7. Cazzolato, M., Vijayakumar, S., Lee, M.C., Vajiac, C., Park, N., Fidalgo, P., Traina, A., and Faloutsos, C., “CallMine: Fraud Detection and Visualization of Million-Scale Call Graphs”. ACM International Conference on Information and Knowledge Management (CIKM), 2023.
8. Yoo, J.*, Lee, M.C.*, Shekhar, S., and Faloutsos, C., “Less is More: SlimG for Accurate, Robust, and Interpretable Graph Mining”. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023.
9. Vajiac, C., Lee, M.C., Kulshrestha, A., Levy, S., Park, N., Olligschlaeger, A., Jones, C., Rabbany, R., and Faloutsos, C., “DeltaShield: Information Theory for Human-Trafficking Detection”. ACM Transactions on Knowledge Discovery from Data (TKDD), 2023.
10. Cazzolato, M., Vijayakumar, S., Zheng, X., Park, N., Lee, M.C., Chau, D.H., Fidalgo, P., Lages, B., Traina, A., and Faloutsos, C., “TGRAPP: Anomaly Detection and Visualization of Large-Scale Call Graphs”. AAAI Conference on Artificial Intelligence (AAAI), 2023.
11. Cazzolato, M., Vijayakumar, S., Zheng, X., Park, N., Lee, M.C., Fidalgo, P., Lages, B., Traina, A., and Faloutsos, C., “TgraphSpot: Fast and Effective Anomaly Detection for Time-Evolving Graphs”. IEEE International Conference on Big Data (BigData), 2022.
12. Vajiac, C., Chau, D.H., Olligschlaeger, A., Mackenzie, R., Nair, P., Lee, M.C., Li, Y., Park, N., Rabbany, R., A., and Faloutsos, C., “TrafficVis: Visualizing Organized Activity and Spatio-Temporal Patterns for Detecting and Labeling Human Trafficking”. IEEE Visualization Conference (IEEE VIS), 2022. Best Paper Honorable Mention.
13. Nair, P., Li, Y., Vajiac, C., Olligschlaeger, A., Lee, M.C., Park, N., A., Chau, D.H., Faloutsos, C., and Rabbany, R., “VisPaD: Visualization and Pattern Discovery for Fighting Human Trafficking”. ACM International World Wide Web Conference (WWW), 2021.
14. Lee, M.C.*, Shekhar, S.*, Faloutsos, C., Hutson, T.N., and Lasemidis, L., “gen2Out: Detecting and Ranking Generalized Anomalies”. IEEE International Conference on Big Data (BigData), 2021.
15. Lee, M.C., Nguyen, H., Berberidis, D., Tseng, V.S., and Akoglu, L., “GAWD: Graph Anomaly Detection in Weighted Directed Graph Databases”. IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), 2021.
16. Vajiac, C., Olligschlaeger, A., Li, Y., Nair, P., Lee, M.C., Park, N., Rabbany, R., A., Chau, D.H., and Faloutsos, C., “TrafficVis: Fighting Human Trafficking through Visualization”. IEEE Visualization Conference (IEEE VIS), 2021. Best Poster Honorable Mention.
17. Lee, M.C.*, Vajiac, C.*, Kulshrestha, A., Levy, S., Park, N., Jones, C., Rabbany, R., and Faloutsos, C., “InfoShield: Generalizable Information-Theoretic HumanTrafficking Detection”. 37th IEEE International Conference on Data Engineering (ICDE), 2021.
18. Lee, M.C., Zhao, Y., Wang, A., Liang, P.J., Akoglu, L., Tseng, V.S., and Faloutsos, C., “AutoAudit: Mining Accounting and Time-Evolving Graphs”. IEEE International Conference on Big Data (BigData), 2020.
19. Lee, M.C., Huang, Y., Ying, J.J.C., Chen, C., and Tseng, V.S., “DeepIdentifier: A Deep Learning-Based Lightweight Approach for User Identity Recognition”. 15th International Conference on Advanced Data Mining and Applications (ADMA), 2019.
20. Huang, Y., Lee, M.C., Tseng, V.S., Hsiao C.J. and Huang C.C., “Robust Sensorbased Human Activity Recognition with Snippet Consensus Neural Networks”. 16th IEEE International Conference on Wearable and Implantable Body Sensor Networks (BSN), 2019.