Corina Pasareanu

Corina Pasareanu is a Principal Scientist at Carnegie Mellon University's CyLab Security and Privacy Institute and serves as a Technical Professional Leader for Data Science at NASA Ames Research Center through KBR. She holds a PhD in Computer Science from Kansas State University (2001), an MS (1995) and BS (1994) from the University Politehnica of Bucharest.

Her research focuses on formal methods for trustworthy AI, including model checking, symbolic execution, compositional verification, and probabilistic software analysis. She pioneers techniques for verifying autonomous systems, neural networks, and cryptographic applications, with emphasis on safety-critical domains like autonomous vehicles and aerospace systems.

Recent publications demonstrate strong focus on AI safety verification, including adversarial robustness of large language models, vision-based autonomous systems, and neural network interpretability. Her work integrates formal methods with machine learning to address security challenges in emerging AI technologies.

Awards and honors:

• ACM Fellow (2023)
• IEEE ASE Fellow
• ETAPS Test of Time Award (2021)
• ASE Most Influential Paper Award (2018)
• ESEC/FSE Test of Time Award (2018)
• ISSTA Retrospective Impact Paper Award (2018)

She leads major projects funded by DARPA, NSF, AWS, and NASA including:

• Trinity: Neurosymbolic Learning and Reasoning (DARPA)
• Proving Timing Side Channel Absence (AWS)
• Safety of Shared Control in Autonomous Driving (AAIP)
• Verifiable Federated Learning (CyLab)

She advises PhD students at CMU and co-leads the CyLab Security and Privacy Institute's research initiatives.