Larry Pileggi

Department Head Professor, Electrical and Computer Engineering Carnegie Mellon University

  • Pittsburgh PA

Larry Pileggi is a specialist in the automation of integrated circuits, and developing software tools for the optimization of power grids.

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Biography

Lawrence Pileggi is the Coraluppi Head and Tanoto Professor of electrical and computer engineering at Carnegie Mellon University, and has previously held positions at Westinghouse Research and Development and the University of Texas at Austin. Pileggi and fellow CMU researchers Lujo Bau and Vyas Sekar are calling on the research and policy communities to develop more comprehensive and accurate grid evaluation frameworks and datasets, and for updating threat models and grid resiliency requirements to match cyber attackers realistic capabilities.

He received his Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University in 1989. He has consulted for various semiconductor and EDA companies, and was co-founder of Fabbrix Inc., Extreme DA, and Pearl Street Technologies. His research interests include various aspects of digital and analog integrated circuit design, and simulation, optimization and modeling of electric power systems.

He has received various awards, including Westinghouse corporation’s highest engineering achievement award, a Presidential Young Inves­tigator award from the National Science Foundation, Semiconductor Research Corporation (SRC) Technical Excellence Awards in 1991 and 1999, the FCRP inaugural Richard A. Newton GSRC Industrial Impact Award, the SRC Aristotle award in 2008, the 2010 IEEE Circuits and Systems Society Mac Van Valkenburg Award, the ACM/IEEE A. Richard Newton Technical Impact Award in Electronic Design Automation in 2011, the Carnegie Institute of Technology B.R. Teare Teaching Award for 2013, and the 2015 Semiconductor Industry Association (SIA) University Researcher Award. He is a co-author of "Electronic Circuit and System Simulation Methods," McGraw-Hill, 1995 and "IC Interconnect Analysis," Kluwer, 2002. He has published almost 400 conference and journal papers and holds 40 U.S. patents. He is a fellow of IEEE.

Areas of Expertise

Integrated Circuits
Power Systems
Secure Hardware
Energy Grid Security

Media Appearances

Power Shift: How CMU Is Leading America’s Energy Evolution

CMU News  online

2025-07-11

From reimagining AI data centers to modernizing and securing the electric grid, CMU researchers are working on practical solutions to pressing challenges in how the U.S. produces, moves and secures energy.

Lujo Bauer, Larry Pileggi and Vyas Sekar are calling on the research and policy communities to develop more comprehensive and accurate grid evaluation frameworks and datasets, and for updating threat models and grid resiliency requirements to match cyber attackers realistic capabilities.

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Useless High-Voltage Power Lines Risk Sparking California Fires

Bloomberg  online

2025-02-21

A high-voltage transmission line can transfer electricity to a nearby idled line through a process called electromagnetic induction. The magnetic field generated by a current on the energized line creates a current on other, nearby lines, said Larry Pileggi, a professor of electrical engineering at Carnegie Mellon University. A surge of current could increase the size of the magnetic field, Pileggi said.

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AI meets opera: A new blended class at CMU yields insights on music and flow

Pittsburgh Post-Gazette  online

2024-04-20

The partnership was a natural fit for a multidisciplinary campus, said Larry Pileggi, who leads CMU’s Department of Electrical and Computer Engineering.

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Spotlight

1 min

Power Shift: How CMU Is Leading America’s Energy Evolution

Carnegie Mellon University, long known for its prowess in computer science and engineering, is now emerging as a key innovator within America’s energy landscape. As AI models grow more powerful, so too does their appetite for energy, straining an aging and outdated grid and prompting urgent questions about infrastructure, security and access. From reimagining AI data centers to modernizing and securing the electric grid, CMU researchers are working on practical solutions to pressing challenges in how the U.S. produces, moves and secures energy. Learn what CMU experts have to say about their Work That Matters.

Larry PileggiZico KolterDimitrios SkarlatosGranger MorganAudrey Kurth CroninVyas Sekar

Social

Industry Expertise

Education/Learning
Electrical Engineering

Accomplishments

Phil Kaufman Award for Pioneering Contributions

2024

Semiconductor Industry Association (SIA) University Researcher Award

2015

Carnegie Institute of Technology B.R. Teare Teaching Award

2013

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Education

Carnegie Mellon University

Ph.D.

Electrical and Computer Engineering

1989

University of Pittsburgh

M.S.

Electrical Engineering

1984

University of Pittsburgh

B.S.

Electrical Engineering

1983

Articles

Large Scale Bilevel Optimization for NK SCOPF Using Adversarial Robustness

IEEE Transactions on Power Systems

2025

Ensuring a secure dispatch against multiple simultaneous outages has long been desired to maintain grid security in the presence of severe events, such as extreme weather phenomena. Traditionally denoted as N-k security constrained optimal power flow (N-k SCOPF), this problem is intractable to solve due to its size being combinatorial in the number of simultaneous outages and due to the non-convex nature of the AC network constraints. This hinders the use of N-k SCOPF for operating realistic-scale systems. In this paper, we introduce a methodology to scalably solve an AC-feasible dispatch that improves security over simultaneous outages. Our methodology poses N-k SCOPF as a bilevel optimization problem and solves it using an adversarial robustness approach.

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Contingency analysis with warm starter using probabilistic graphical model

Electric Power Systems Research

2024

Cyberthreats are an increasingly common risk to the power grid and can thwart secure grid operations. We propose to extend contingency analysis to include cyberthreat evaluations. However, unlike the traditional N-1 or N-2 contingencies, cyberthreats (eg, MadIoT) require simulating hard-to-solve Nk (with k≫ 2) contingencies in a practical amount of time. Purely physics-based power flow solvers, while being accurate, are slow and may not solve Nk contingencies in a timely manner, whereas the emerging data-driven alternatives are fast but not sufficiently generalizable, interpretable, and scalable. To address these challenges, we propose a novel conditional Gaussian Random Field-based data-driven method that performs fast and accurate evaluation of cyberthreats. It achieves speedup of contingency analysis by warm-starting simulations, ie, improving starting points, for the physical solvers.

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Generalized smooth functions for modeling steady-state response of controls in transmission and distribution

Electric Power Systems Research

2022

The promise of renewables and the consequent fluctuations in the power grid necessitate a robust simulation framework to capture the steady-state behavior of new controls. However, standard non-differentiable models of control mechanisms produce divergence and/or numerical oscillations in large power flow simulations. In this paper, we describe a methodology that introduces two generalized class C1 smooth basis functions to model the steady-state of various controls in power flow for transmission and three-phase distribution as well as optimization settings. These models are accompanied by homotopy methods and limiting techniques in the simulation engine that ensure scalable and robust convergence.

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