Abhijeet Sahu is a cyber-physical systems researcher focused on leveraging artificial intelligence techniques in secure grid control through adaptive resilience metric quantification. Sahu earned his Ph.D. in electrical engineering from the electrical and computer engineering department at Texas A&M University in College Station, Texas, with a thesis titled, Addressing Uncertainty in Cyber-Physical Power Systems–Modeling to Integration in a Cyber-Physical Energy Management System. His research focuses on the use of Bayesian inferencing and reinforcement learning for control under uncertainties. Other interests include network security, cyber-physical modeling, and artificial intelligence for cyber-physical security in power distribution and transmission systems. He has worked as a network engineer at National Thermal Corporation Limited in India.

Research Interests

Reinforcement learning

ICS network security

Grid resilience

Wireless communication

Education

Ph.D., Electrical Engineering, Texas A&M University, College Station, TX

M.S., Electrical Engineering, Texas A&M University, College Station, TX

B.S., Electronics and Communication Engineering, National Institute of Technology, Rourkela, India

Professional Experience

Graduate Research Intern, NREL (2021–2022)

Software Development Intern, Real Time Power, Inc.  (2017)

Assistant Manager (IT and Communication), National Thermal Power Corporation Ltd., India (2011–2015)

Associations and Memberships

Member, IEEE Communications Society

Member, IEEE Power and Energy Society

Featured Work

A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks, IEEE Power and Energy Society General Meeting, (2022)

Generalized Contingency Analysis Based on Graph Theory and Line Outage Distribution Factor, IEEE Systems (2022)

Graph Neural Networks Based Detection of Stealth False Data Injection Attacks in Smart Grids, IEEE Systems(2022)

Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach, MDPI Sensors (2022)

Design and Evaluation of a Cyber-Physical Testbed for Improving Attack Resilience of Power Systems, IET Cyber-Physical Systems: Theory & Application (2021)

Man-in-the-Middle Attacks and Defense in a Power System Cyber-Physical Testbed, IET Cyber-Physical Systems: Theory & Application (2021)

Multi-Source Multi-Domain Data Fusion for Cyberattack Detection in Power Systems, IEEE Access (2021)

A3D: Attention-Based Auto-Encoder Anomaly Detector for False Data Injection Attacks, Electric Power Systems Research (2020)

Data Processing and Model Selection for Machine Learning-Based Network Intrusion Detection, IEEE International Workshop Technical Committee on Communications Quality and Reliability, (2020)

Modeling AMI Network for Real-Time Simulation in NS-3, 2016 Principles, Systems and Applications of IP Telecommunications (2016)

Awards and Honors

Chevron Scholarship (2021)

Powell Fellowship (2019 and 2020)