Biography

I am currently on the academic job market :)

I am a Ph.D. candidate in Industrial Engineering at the H. Milton Stewart School of Industrial and Systems Engineering, expected to graduate in May, 2021. I am co-adviced by Prof. Nagi Gebraeel and Prof. Kamran Paynabar. I received my M.S. degree in Statistics from Georgia Tech in 2020, and my B.S. in Automotive Engineering from Tsinghua University, Beijing, China, in 2015.

My research interests include cybersecurity for Cyber-Physical Systems (CPS) / Industrial Control Systems (ICS), machine learning, sensor-based anomaly detection, complex system modeling, and reliability engineering. I am currently working on "Online Detection Against Cyberattacks in CPS" as my Ph.D. thesis.

Publications

Journal Papers Published or Accepted

Detection and Differentiation of Replay Attack and Equipment Faults in SCADA Systems

Dan Li, Nagi Gebraeel, and Kamran Paynabar
IEEE Transactions on Automation Science and Engineering (Early Access), DOI: 10.1109/TASE.2020.3013760.
  2019 IISE Annual Meeting Energy System Best Student Paper Award
  2019 IISE Annual Meeting Data Analytics and Information Systems Best Student Paper Award (Runner-up)

A Degradation-Based Detection Framework Against Covert Cyberattacks on SCADA Systems

Dan Li, Kamran Paynabar, and Nagi Gebraeel
IISE Transactions, DOI: 10.1080/24725854.2020.1802537.
  2020 IISE Annual Meeting Data Analytics and Information Systems Best Student Paper Award (Finalist)
  2020 Georgia Tech IISP Cybersecurity Summit Best Student Poster Award (Second Prize)

An Adaptive Sampling Strategy for Online Monitoring and Diagnosis of High-dimensional Streaming Data
Ana María Estrada Gómez, Dan Li, and Kamran Paynabar
Tentatively Accepted: Technometrics

Journal Papers Under Review

Blockchain Based Decentralized Cyber Attack Detection for Large Scale Power Systems
Paritosh Ramanah, Dan Li, and Nagi Gebraeel
IEEE Transactions on Industrial Informatics

Online Detection of Inter-turn Winding Faults in Single-Phase Distribution Transformers Using Smart Meter Data
Kavya Ashok, Dan Li, Deepak Divan, and Nagi Gebraeel
(Major Revision) IEEE Transactions on Smart Grid

An Online Approach to Cyberattack Detection and Localization in Smart Grid
Dan Li, Nagi Gebraeel, Kamran Paynabar, and A.P. Sakis Meliopoulos
IEEE Transactions on Smart Grid

Conference Papers Published or Accepted

Distribution Transformer Health Monitoring Using Smart Meter Data

Kavya Ashok, Dan Li, Deepak Divan, and Nagi Gebraeel
2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2020, pp. 1-5, DOI: 10.1109/ISGT45199.2020.9087641.

Deep Learning based Covert Attack Identification for Industrial Control Systems
Dan Li, Paritosh Ramanah, Nagi Gebraeel, and Kamran Paynabar
2020 IEEE International Conference on Machine Learning and Applications (ICMLA)

In Preparation

Manifold Learning for Failure Mode Classification

Teaching

ISYE 3770 Statistics and Applications

Chap 1: Introduction   Slides     Video
Chap 2: Probability   Slides     Video1     Video2
Chap 3: Descrete Random Variables and Distributions   Slides     Video1     Video2
Chap 4: Continuous Random Variables and Distributions   Slides     Video1     Video2     Video3
Chap 5: Joint Distributions   Slides     Video1     Video2

Recent Work

Data-Driven Online Detection Against Cyberattacks In Cyber-Physical Systems: Part I

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Data-Driven Online Detection Against Cyberattacks In Cyber-Physical Systems: Part II

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Data-Driven Online Detection Against Cyberattacks In Cyber-Physical Systems: Part III

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Manifold Learning for Failure Mode Classification

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