Maria Christakis

Maria Christakis is a Full Professor at the Faculty of Informatics, Vienna University of Technology, where she leads the Software Engineering Research Unit and the Rigorous Software Engineering Group at the Information Systems Engineering Institute. Her work bridges theoretical foundations with practical tools for reliable software development.

Her research focuses on Program Analysis, Formal Methods, Software Verification, and Test Generation. She develops techniques for automatic test generation, program analysis, and software verification to enhance software robustness while improving developer experience. Key innovations include metamorphic testing frameworks, soundness testing for program analyzers, and verification tools for smart contracts and machine learning systems.

Christakis' recent publications reveal strong trends in zero-knowledge circuit testing, smart contract security, machine learning verification, and action-policy testing. Her work combines formal methods with practical engineering solutions, particularly for blockchain systems, neural networks, and program analyzers. She emphasizes sustainability in testing through projects like GreenBench.

• Amazon Research Award (2023) for Testing Dafny for Unsoundness and Brittleness Bugs
• Facebook Faculty Research Award for Program Analysis
• Google Research Scholar Award for Metamorphic Specification and Testing
• Best Presentation Award at ESEC/FSE'20
• Distinguished Paper Award at ICSE'16

She actively mentors PhD and Master's students through projects like Circuzz, Sherlock, and Nomos. Her group receives substantial funding from the Austrian Science Fund (FWF), European Commission, Amazon Research Awards, and Google Research Scholar program. Current major projects include the Structured Doctoral Program on Automated Reasoning (FWF-funded) and the Amazon Research Award project on Dafny testing.

Christakis leads the AGI Labs team building AI agents and contributes to Amazon Nova foundation models. Her group maintains strong industry collaborations with Amazon (through Amazon Research Awards and Amazon Scholars program), MPI-SWS, and Microsoft Research.