Milda Zizyte
Carnegie Mellon University, John Brown University, Brown University
Papers
5
Total Citations
73
H-Index
3
About
Milda Zizyte is a researcher at the forefront of ensuring the safety and reliability of autonomous and robotic systems. Her primary research areas include robustness testing, fault diagnosis, and software engineering education for robotics. Zizyte’s most impactful work, “Robustness testing of autonomy software” (52 citations), addresses the critical challenge of ensuring autonomous systems behave safely under unexpected inputs—a cornerstone for deploying robots in human-interactive environments. She has also pioneered novel testing oracles, such as detecting execution anomalies to assess autonomy software robustness, and developed active learning omnivariate decision trees to create human-interpretable descriptions of system failures, aiding in complex debugging. Beyond testing, Zizyte investigates the software engineering skills taught in robotics degree programs, revealing gaps in current curricula. Her recent work on misconceptions in linear temporal logic (LTL) aims to improve how engineers specify and verify robot behavior. With a growing citation record and contributions spanning both technical innovation and educational reform, Zizyte is shaping a future where autonomous systems are not only capable but demonstrably safe.
Research Focus
Key Achievements
Top Papers
- 1Robustness testing of autonomy software52 citations · 2018
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- 5Misconceptions in Finite-Trace and Infinite-Trace Linear Temporal Logic3 citations · 2024