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Dan Li

Dan Li

Assistant Professor
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Department

Industrial & Systems Engineering

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  • PhD 2021, Georgia Institute of Technology
  • MS 2020, Georgia Institute of Technology
  • MS 2015, Tsinghua University

  • 2024 College of Engineering and Applied Sciences, Clemson University, Dean’s Professorship
  • 2023 IISE Transactions, Data Science, Quality, and Reliability Focus, Best Application Paper Award
  • 2021 Quality Control and Reliability Engineering, IISE Annual Conference, Best Student Paper Finalist
  • 2021 Data Analytics and Information Systems (DAIS), IISE Annual Conference, Best Track Paper Award
  • 2021 The NYU Tandon School of Engineering, Tandon Faculty First Look Fellowship
  • 2020 DAIS, IISE Annual Conference, Best Student Paper Finalist
  • 2020 NSF I-Corps Program, Venturelab, Student Travel Grant
  • 2019 Energy Systems, IISE Annual Conference, Best Student Paper Award
  • 2019 DAIS, IISE Annual Conference, Best Student Paper Runner-up
  • 2019 Student Poster Competition, Georgia Tech Cybersecurity Summit, Best Student Poster (Second Prize)
  • 2015 Tsinghua University, Outstanding Thesis Award
  • 2011 Tsinghua University, Undergraduate Fellowship

  • Xie, X., Xian, X., Li, D., & Wang, A. (2024). Adversarial Client Detection via Non-parametric Subspace Monitoring in the Internet of Federated Things. IISE Transactions(just-accepted), 1--23.
  • Aftabi, N., Li, D., & Sharkey, T. C. (2024). An Integrated Cyber-Physical Framework for Worst-Case Attacks in Industrial Control Systems. IISE Transactions(just-accepted), 1--26.
  • Kokhahi, A., & Li, D. (2024). GLHAD: A Group Lasso-Based Hybrid Attack Detection and Localization Framework for Multistage Manufacturing Systems. Journal of Computing and Information Science in Engineering, 24(7).
  • Aftabi, N., Li, D., & Ramanan, P. (2023). A Variational Autoencoder Framework for Robust, Physics-Informed Cyberattack Recognition in Industrial Cyber-Physical Systems. arXiv preprint arXiv:2310.06948.
  • Li, D., Gebraeel, N., Paynabar, K., & Meliopoulos, A. (2022). An Online Approach to Cyberattack Detection and Identification in Smart Grid. IEEE Transactions on Power Systems(Accepted).
  • Li, D., Paynabar, K., & Gebraeel, N. (2021). A degradation-based detection framework against covert cyberattacks on SCADA systems. IISE Transactions, 53(7), 812--829.
  • Estrada Gómez, A. M., Li, D., & Paynabar, K. (2020). An Adaptive Sampling Strategy for Online Monitoring and Diagnosis of High-dimensional Streaming Data. Technometrics(tentatively-accepted).
  • Ramanan, P., Li, D., & Gebraeel, N. (2020). Decentralized Blockchain based Cyber Attack Detection on Large Scale Power Systems. IEEE Transactions on Industrial Informatics(Submitted).
  • Li, D., Ramanan, P., & Gebraeel, N. (2020). Deep Learning based Covert Attack Identification for Industrial Control Systems. IEEE International Conference on Machine Learning and Applications (ICMLA).
  • Li, D., Gebraeel, N., & Paynabar, K. (2020). Detection and differentiation of replay attack and equipment faults in SCADA systems. IEEE Transactions on Automation Science and Engineering, 18(4), 1626--1639.

  • I SY E 890 - Pre-Dissertator's Research (Spring 2025)
  • I SY E 890 - Pre-Dissertator's Research (Fall 2024)