Anna Scaglione

Anna Scaglione is a Professor in the Department of Electrical and Computer Engineering at Cornell University's College of Engineering, based at Cornell Tech. She rejoined the faculty in September 2021 after holding professorial positions at Arizona State University, UC Davis, and earlier at Cornell (2001–2008). She earned her M.Sc. in 1995 and Ph.D. in 1999 from Cornell University.

Research Interests: Her work centers on statistical signal processing with applications in communication networks, electric power systems, intelligent infrastructure, and network science. Key areas include graph signal processing, federated learning, differential privacy, reinforcement learning for energy systems, and cyber-physical security in smart grids. She integrates machine learning, optimization, and control theory to address challenges in modern power systems and IoT.

The 15 most recent publications (2021–2025) reveal a dominant trend in privacy-preserving and AI-driven solutions for power systems. Her research emphasizes federated learning, graph neural networks, differential privacy, and reinforcement learning applied to grid stability, cybersecurity, and distributed energy management. There is a strong focus on graph signal processing for power grid modeling and anomaly detection, as well as synthetic data generation and secure transactive energy platforms.

• IEEE Fellow (2011)
• IEEE Signal Processing Transactions Best Paper Award (2000)
• IEEE Donald G. Fink Prize Paper Award (2013)
• IEEE Signal Processing Society Young Author Best Paper Award (2013, with Lin Li)
• IEEE Smart Grid Communications Technical Committee Technical Achievement Award (2020)
• IEEE SPS Distinguished Lecturer (2019–2020)

Dr. Scaglione has advised students including Lin Li, whose work earned a best paper award. She has secured significant research grants related to smart grid security, privacy, and optimization. Her editorial leadership includes Editor-in-Chief of IEEE Signal Processing Letters (2012–2013) and Deputy Editor-in-Chief of IEEE Transactions on Control of Networked Systems. She has served on IEEE technical committees, steering committees, and as General or Technical Chair for major conferences such as SPAWC, SmartGridComm, and GlobalSIP.

She leads research in smart grid signal processing, secure distributed energy systems, and privacy-aware machine learning for infrastructure. Her team develops frameworks like Grid-GSP (Graph Signal Processing for power grids), SoDa (synthetic solar data), and CIGAR (cybersecurity via inverter reconfiguration). She is involved in blockchain-based transactive energy platforms and resilient simulation environments for critical infrastructure.