Meng-Chieh (Jeremy) Lee

Meng-Chieh (Jeremy) Lee

CSD PhD Student at CMU

Meng-Chieh (Jeremy) Lee

I am a fourth-year Ph.D. student in Computer Science Department at Carnegie Mellon University. My advisors are Professor Christos Faloutsos and Professor Leman Akoglu. My research interests include graph mining, data mining and anomaly detection. I am interested in solving real-world applications, and have been working on several projects with both academia and industry. Please see more in my CV.

News:

Refereed Publications:

  1. 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.
  2. 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.
  3. Lee, M.C.*, Zhao, L.*, Akoglu, L., “Descriptive Kernel Convolution Network with Improved Random Walk Kernel”. ACM Web Conference (WWW), 2024.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.